DiffModeler(seq)

Job ID : d867aeb65edd60c236050c55139eedff

DiffModeler is a computational tool using a diffusion model to automatically build full protein complex structure from cryo-EM maps at 0-20A resolution. If you encounter any questions for the modeled structure, feel free to email dkihara@purdue.edu, wang3702@purdue.edu and zhu773@purdue.edu!

DiffModeler started
Listing 'VESPER_CUDA'...
ssutils'...
existed
pre-compile VESPER to accelerate!
Origin: (0., 0., 0.)
Previous voxel size: 1.0
nx : 183
ny : 183
nz : 183
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 183
my : 183
mz : 183
cella : (183., 183., 183.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.011068494990468025
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 0
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (0., 0., 0.)
map : b'MAP '
machst : [68 65 0 0]
rms : 1.0117650032043457
nlabl : 1
label : [b'::::EMDATABANK.org::::EMD-6824::::' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
single_chain_pdb created
read chain info from fasta: defaultdict(<class 'list'>, {'A,B,C,D': ['M', 'A', 'T', 'P', 'A', 'G', 'R', 'R', 'A', 'S', 'E', 'T', 'E', 'R', 'L', 'L', 'T', 'P', 'N', 'P', 'G', 'Y', 'G', 'T', 'Q', 'V', 'G', 'T', 'S', 'P', 'A', 'P', 'T', 'T', 'P', 'T', 'E', 'E', 'E', 'D', 'L', 'R', 'R', 'R', 'L', 'K', 'Y', 'F', 'F', 'M', 'S', 'P', 'C', 'D', 'K', 'F', 'R', 'A', 'K', 'G', 'R', 'K', 'P', 'C', 'K', 'L', 'M', 'L', 'Q', 'V', 'V', 'K', 'I', 'L', 'V', 'V', 'T', 'V', 'Q', 'L', 'I', 'L', 'F', 'G', 'L', 'S', 'N', 'Q', 'L', 'V', 'V', 'T', 'F', 'R', 'E', 'E', 'N', 'T', 'I', 'A', 'F', 'R', 'H', 'L', 'F', 'L', 'L', 'G', 'Y', 'S', 'D', 'G', 'S', 'D', 'D', 'T', 'F', 'A', 'A', 'Y', 'T', 'Q', 'E', 'Q', 'L', 'Y', 'Q', 'A', 'I', 'F', 'Y', 'A', 'V', 'D', 'Q', 'Y', 'L', 'I', 'L', 'P', 'E', 'I', 'S', 'L', 'G', 'R', 'Y', 'A', 'Y', 'V', 'R', 'G', 'G', 'G', 'G', 'P', 'W', 'A', 'N', 'G', 'S', 'A', 'L', 'A', 'L', 'C', 'Q', 'R', 'Y', 'Y', 'H', 'R', 'G', 'H', 'V', 'D', 'P', 'A', 'N', 'D', 'T', 'F', 'D', 'I', 'D', 'P', 'R', 'V', 'V', 'T', 'D', 'C', 'I', 'Q', 'V', 'D', 'P', 'P', 'D', 'R', 'P', 'P', 'D', 'I', 'P', 'S', 'E', 'D', 'L', 'D', 'F', 'L', 'D', 'G', 'S', 'A', 'S', 'Y', 'K', 'N', 'L', 'T', 'L', 'K', 'F', 'H', 'K', 'L', 'I', 'N', 'V', 'T', 'I', 'H', 'F', 'Q', 'L', 'K', 'T', 'I', 'N', 'L', 'Q', 'S', 'L', 'I', 'N', 'N', 'E', 'I', 'P', 'D', 'C', 'Y', 'T', 'F', 'S', 'I', 'L', 'I', 'T', 'F', 'D', 'N', 'K', 'A', 'H', 'S', 'G', 'R', 'I', 'P', 'I', 'R', 'L', 'E', 'T', 'K', 'T', 'H', 'I', 'Q', 'E', 'C', 'K', 'H', 'P', 'S', 'V', 'S', 'R', 'H', 'G', 'D', 'N', 'S', 'F', 'R', 'L', 'L', 'F', 'D', 'V', 'V', 'V', 'I', 'L', 'T', 'C', 'S', 'L', 'S', 'F', 'L', 'L', 'C', 'A', 'R', 'S', 'L', 'L', 'R', 'G', 'F', 'L', 'L', 'Q', 'N', 'E', 'F', 'V', 'V', 'F', 'M', 'W', 'R', 'R', 'R', 'G', 'R', 'E', 'I', 'S', 'L', 'W', 'E', 'R', 'L', 'E', 'F', 'V', 'N', 'G', 'W', 'Y', 'I', 'L', 'L', 'V', 'T', 'S', 'D', 'V', 'L', 'T', 'I', 'S', 'G', 'T', 'V', 'M', 'K', 'I', 'G', 'I', 'E', 'A', 'K', 'N', 'L', 'A', 'S', 'Y', 'D', 'V', 'C', 'S', 'I', 'L', 'L', 'G', 'T', 'S', 'T', 'L', 'L', 'V', 'W', 'V', 'G', 'V', 'I', 'R', 'Y', 'L', 'T', 'F', 'F', 'H', 'K', 'Y', 'N', 'I', 'L', 'I', 'A', 'T', 'L', 'R', 'V', 'A', 'L', 'P', 'S', 'V', 'M', 'R', 'F', 'C', 'C', 'C', 'V', 'A', 'V', 'I', 'Y', 'L', 'G', 'Y', 'C', 'F', 'C', 'G', 'W', 'I', 'V', 'L', 'G', 'P', 'Y', 'H', 'V', 'K', 'F', 'R', 'S', 'L', 'S', 'M', 'V', 'S', 'E', 'C', 'L', 'F', 'S', 'L', 'I', 'N', 'G', 'D', 'D', 'M', 'F', 'V', 'T', 'F', 'A', 'A', 'M', 'Q', 'A', 'Q', 'Q', 'G', 'H', 'S', 'S', 'L', 'V', 'W', 'L', 'F', 'S', 'Q', 'L', 'Y', 'L', 'Y', 'S', 'F', 'I', 'S', 'L', 'F', 'I', 'Y', 'M', 'V', 'L', 'S', 'L', 'F', 'I', 'A', 'L', 'I', 'T', 'G', 'A', 'Y', 'D', 'T', 'I', 'K', 'H', 'P', 'G', 'G', 'T', 'G', 'T', 'E', 'K', 'S', 'E', 'L', 'Q', 'A', 'Y', 'I', 'E', 'Q', 'C', 'Q', 'D', 'S', 'P', 'T', 'S', 'G', 'K', 'F', 'R', 'R', 'G', 'S', 'G', 'S', 'A', 'C', 'S', 'L', 'F', 'C', 'C', 'C', 'G', 'R', 'D', 'S', 'P', 'E', 'D', 'H', 'S', 'L', 'L', 'V', 'N']})
match candidate: A,B,C,D [['7sq9_D', 0.0], ['7sq9_C', 0.0], ['7sq9_B', 0.0], ['7sq9_A', 0.0], ['7sq8_D', 0.0], ['7sq8_C', 0.0], ['7sq8_B', 0.0], ['7sq8_A', 0.0], ['7sq7_D', 0.0], ['7sq7_C', 0.0], ['7sq7_B', 0.0], ['7sq7_A', 0.0], ['7sq6_D', 0.0], ['7sq6_C', 0.0], ['7sq6_B', 0.0], ['7sq6_A', 0.0], ['5ye5_D', 0.0], ['5ye5_C', 0.0], ['5ye5_B', 0.0], ['5ye5_A', 0.0], ['5ye2_D', 0.0], ['5ye2_C', 0.0], ['5ye2_B', 0.0], ['5ye2_A', 0.0], ['5ye1_D', 0.0], ['5ye1_C', 0.0], ['5ye1_B', 0.0], ['5ye1_A', 0.0], ['5ydz_D', 0.0], ['5ydz_C', 0.0]]
A-B-C-D created
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
A-B-C-D existed
remain waiting assign chain number 51
1 matched single chain structure
continue PDB+AFDB search for remained 1 chains
match candidate: A,B,C,D [['AFDB:AF-Q99J21-F1', 0.0], ['7sq9_D', 0.0], ['7sq9_C', 0.0], ['7sq9_B', 0.0], ['7sq9_A', 0.0], ['7sq8_D', 0.0], ['7sq8_C', 0.0], ['7sq8_B', 0.0], ['7sq8_A', 0.0], ['7sq7_D', 0.0], ['7sq7_C', 0.0], ['7sq7_B', 0.0], ['7sq7_A', 0.0], ['7sq6_D', 0.0], ['7sq6_C', 0.0], ['7sq6_B', 0.0], ['7sq6_A', 0.0], ['5ye5_D', 0.0], ['5ye5_C', 0.0], ['5ye5_B', 0.0], ['5ye5_A', 0.0], ['5ye2_D', 0.0], ['5ye2_C', 0.0], ['5ye2_B', 0.0], ['5ye2_A', 0.0], ['5ye1_D', 0.0], ['5ye1_C', 0.0], ['5ye1_B', 0.0], ['5ye1_A', 0.0], ['5ydz_D', 0.0]]
A-B-C-D existed
DB search finished! Match relationship {'A,B,C,D': 'AFDB:AF-Q99J21-F1'}
A-B-C-D existed
A-B-C-D.pdb': ['A', 'B', 'C', 'D']}
infer_diffusion created
Input created
map density range: 0.000000 9.673442
map hist log percentage 98: 9.044668
detected mode mapc 1, mapr 2, maps 3
Origin: [4.0, 4.0, 14.0]
given contour 3.000000
revised contour 0.331687
In total we prepared 216 boxes as input
dataset loading finished with 216 boxes!
loading model message: <All keys matched successfully>
diffusion_box created
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 created
sample_1 created
sample_2 created
sample_3 created
sample_4 created
sample_5 created
sample_6 created
sample_7 created
sample_8 created
sample_9 created
sample_10 created
54] data_time 0.605634 (0.605634) train_time 32.304988 (32.304988) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.017869 (0.311752) train_time 27.127182 (29.716085) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003547 (0.209017) train_time 27.377767 (28.936646) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.005496 (0.158136) train_time 27.472472 (28.570602) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003776 (0.127264) train_time 27.754642 (28.407410) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.008470 (0.107465) train_time 27.735171 (28.295370) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004805 (0.092800) train_time 28.615813 (28.341148) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004084 (0.081710) train_time 27.725131 (28.264145) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.005445 (0.073236) train_time 27.837150 (28.216702) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004774 (0.066390) train_time 27.930904 (28.188122) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.002964 (0.060624) train_time 27.915715 (28.163357) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.005073 (0.055995) train_time 28.205101 (28.166836) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004422 (0.052028) train_time 27.896351 (28.146030) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.007620 (0.048856) train_time 27.950527 (28.132065) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003542 (0.045835) train_time 28.015908 (28.124321) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003526 (0.043190) train_time 28.509765 (28.148412) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.008708 (0.041162) train_time 28.015835 (28.140613) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.006668 (0.039246) train_time 28.043658 (28.135227) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004917 (0.037439) train_time 28.271747 (28.142412) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.005382 (0.035836) train_time 28.119467 (28.141265) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004498 (0.034344) train_time 28.837273 (28.174408) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004823 (0.033002) train_time 28.265862 (28.178565) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004781 (0.031775) train_time 28.319047 (28.184673) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003566 (0.030600) train_time 28.580114 (28.201149) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003553 (0.029518) train_time 28.191743 (28.200773) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.005987 (0.028613) train_time 28.388916 (28.208009) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003767 (0.027692) train_time 28.316422 (28.212025) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004082 (0.026849) train_time 28.148103 (28.209742) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.011323 (0.026314) train_time 28.132942 (28.207094) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.002353 (0.025515) train_time 28.205407 (28.207037) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.002729 (0.024780) train_time 28.750786 (28.224578) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004964 (0.024161) train_time 28.746338 (28.240883) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.002925 (0.023517) train_time 28.265947 (28.241642) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.002280 (0.022893) train_time 28.141327 (28.238692) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.005183 (0.022387) train_time 28.261488 (28.239343) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.007259 (0.021967) train_time 28.248370 (28.239594) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003822 (0.021476) train_time 28.391758 (28.243706) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.007399 (0.021106) train_time 28.856377 (28.259829) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003640 (0.020658) train_time 28.559749 (28.267519) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.029424 (0.020877) train_time 28.561262 (28.274863) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.031618 (0.021139) train_time 28.180188 (28.272554) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.005479 (0.020766) train_time 28.257170 (28.272188) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.005000 (0.020399) train_time 28.319090 (28.273278) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004058 (0.020028) train_time 28.301240 (28.273914) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003885 (0.019669) train_time 28.498660 (28.278908) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003847 (0.019325) train_time 28.122757 (28.275514) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004823 (0.019017) train_time 28.225833 (28.274457) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004320 (0.018711) train_time 28.312161 (28.275242) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.002495 (0.018380) train_time 28.158278 (28.272855) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.004927 (0.018111) train_time 28.233936 (28.272077) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003666 (0.017827) train_time 28.451049 (28.275586) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.008868 (0.017655) train_time 28.396598 (28.277913) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.005276 (0.017422) train_time 28.244156 (28.277276) loss 0.000000 (0.000000)
infer: t: 0 t now: 1.0 gamma t tensor([6.1654e-09], device='cuda:0')
infer: t: 1 t now: 0.99 gamma t tensor([0.0002], device='cuda:0')
infer: t: 2 t now: 0.98 gamma t tensor([0.0010], device='cuda:0')
infer: t: 3 t now: 0.97 gamma t tensor([0.0022], device='cuda:0')
infer: t: 4 t now: 0.96 gamma t tensor([0.0040], device='cuda:0')
infer: t: 5 t now: 0.95 gamma t tensor([0.0062], device='cuda:0')
infer: t: 6 t now: 0.94 gamma t tensor([0.0089], device='cuda:0')
infer: t: 7 t now: 0.9299999999999999 gamma t tensor([0.0121], device='cuda:0')
infer: t: 8 t now: 0.92 gamma t tensor([0.0157], device='cuda:0')
infer: t: 9 t now: 0.91 gamma t tensor([0.0199], device='cuda:0')
infer: t: 10 t now: 0.9 gamma t tensor([0.0245], device='cuda:0')
infer: t: 11 t now: 0.89 gamma t tensor([0.0296], device='cuda:0')
infer: t: 12 t now: 0.88 gamma t tensor([0.0351], device='cuda:0')
infer: t: 13 t now: 0.87 gamma t tensor([0.0411], device='cuda:0')
infer: t: 14 t now: 0.86 gamma t tensor([0.0476], device='cuda:0')
infer: t: 15 t now: 0.85 gamma t tensor([0.0545], device='cuda:0')
infer: t: 16 t now: 0.84 gamma t tensor([0.0619], device='cuda:0')
infer: t: 17 t now: 0.83 gamma t tensor([0.0696], device='cuda:0')
infer: t: 18 t now: 0.8200000000000001 gamma t tensor([0.0778], device='cuda:0')
infer: t: 19 t now: 0.81 gamma t tensor([0.0865], device='cuda:0')
infer: t: 20 t now: 0.8 gamma t tensor([0.0955], device='cuda:0')
infer: t: 21 t now: 0.79 gamma t tensor([0.1049], device='cuda:0')
infer: t: 22 t now: 0.78 gamma t tensor([0.1147], device='cuda:0')
infer: t: 23 t now: 0.77 gamma t tensor([0.1249], device='cuda:0')
infer: t: 24 t now: 0.76 gamma t tensor([0.1355], device='cuda:0')
infer: t: 25 t now: 0.75 gamma t tensor([0.1464], device='cuda:0')
infer: t: 26 t now: 0.74 gamma t tensor([0.1577], device='cuda:0')
infer: t: 27 t now: 0.73 gamma t tensor([0.1693], device='cuda:0')
infer: t: 28 t now: 0.72 gamma t tensor([0.1813], device='cuda:0')
infer: t: 29 t now: 0.71 gamma t tensor([0.1935], device='cuda:0')
infer: t: 30 t now: 0.7 gamma t tensor([0.2061], device='cuda:0')
infer: t: 31 t now: 0.69 gamma t tensor([0.2189], device='cuda:0')
infer: t: 32 t now: 0.6799999999999999 gamma t tensor([0.2320], device='cuda:0')
infer: t: 33 t now: 0.6699999999999999 gamma t tensor([0.2454], device='cuda:0')
infer: t: 34 t now: 0.6599999999999999 gamma t tensor([0.2591], device='cuda:0')
infer: t: 35 t now: 0.65 gamma t tensor([0.2730], device='cuda:0')
infer: t: 36 t now: 0.64 gamma t tensor([0.2871], device='cuda:0')
infer: t: 37 t now: 0.63 gamma t tensor([0.3014], device='cuda:0')
infer: t: 38 t now: 0.62 gamma t tensor([0.3159], device='cuda:0')
infer: t: 39 t now: 0.61 gamma t tensor([0.3306], device='cuda:0')
infer: t: 40 t now: 0.6 gamma t tensor([0.3454], device='cuda:0')
infer: t: 41 t now: 0.5900000000000001 gamma t tensor([0.3604], device='cuda:0')
infer: t: 42 t now: 0.5800000000000001 gamma t tensor([0.3756], device='cuda:0')
infer: t: 43 t now: 0.5700000000000001 gamma t tensor([0.3908], device='cuda:0')
infer: t: 44 t now: 0.56 gamma t tensor([0.4062], device='cuda:0')
infer: t: 45 t now: 0.55 gamma t tensor([0.4217], device='cuda:0')
infer: t: 46 t now: 0.54 gamma t tensor([0.4372], device='cuda:0')
infer: t: 47 t now: 0.53 gamma t tensor([0.4528], device='cuda:0')
infer: t: 48 t now: 0.52 gamma t tensor([0.4685], device='cuda:0')
infer: t: 49 t now: 0.51 gamma t tensor([0.4842], device='cuda:0')
infer: t: 50 t now: 0.5 gamma t tensor([0.4999], device='cuda:0')
infer: t: 51 t now: 0.49 gamma t tensor([0.5156], device='cuda:0')
infer: t: 52 t now: 0.48 gamma t tensor([0.5313], device='cuda:0')
infer: t: 53 t now: 0.47 gamma t tensor([0.5469], device='cuda:0')
infer: t: 54 t now: 0.45999999999999996 gamma t tensor([0.5625], device='cuda:0')
infer: t: 55 t now: 0.44999999999999996 gamma t tensor([0.5781], device='cuda:0')
infer: t: 56 t now: 0.43999999999999995 gamma t tensor([0.5936], device='cuda:0')
infer: t: 57 t now: 0.43000000000000005 gamma t tensor([0.6089], device='cuda:0')
infer: t: 58 t now: 0.42000000000000004 gamma t tensor([0.6242], device='cuda:0')
infer: t: 59 t now: 0.41000000000000003 gamma t tensor([0.6393], device='cuda:0')
infer: t: 60 t now: 0.4 gamma t tensor([0.6544], device='cuda:0')
infer: t: 61 t now: 0.39 gamma t tensor([0.6692], device='cuda:0')
infer: t: 62 t now: 0.38 gamma t tensor([0.6839], device='cuda:0')
infer: t: 63 t now: 0.37 gamma t tensor([0.6984], device='cuda:0')
infer: t: 64 t now: 0.36 gamma t tensor([0.7127], device='cuda:0')
infer: t: 65 t now: 0.35 gamma t tensor([0.7268], device='cuda:0')
infer: t: 66 t now: 0.33999999999999997 gamma t tensor([0.7407], device='cuda:0')
infer: t: 67 t now: 0.32999999999999996 gamma t tensor([0.7544], device='cuda:0')
infer: t: 68 t now: 0.31999999999999995 gamma t tensor([0.7678], device='cuda:0')
infer: t: 69 t now: 0.31000000000000005 gamma t tensor([0.7809], device='cuda:0')
infer: t: 70 t now: 0.30000000000000004 gamma t tensor([0.7937], device='cuda:0')
infer: t: 71 t now: 0.29000000000000004 gamma t tensor([0.8063], device='cuda:0')
infer: t: 72 t now: 0.28 gamma t tensor([0.8186], device='cuda:0')
infer: t: 73 t now: 0.27 gamma t tensor([0.8305], device='cuda:0')
infer: t: 74 t now: 0.26 gamma t tensor([0.8421], device='cuda:0')
infer: t: 75 t now: 0.25 gamma t tensor([0.8534], device='cuda:0')
infer: t: 76 t now: 0.24 gamma t tensor([0.8643], device='cuda:0')
infer: t: 77 t now: 0.22999999999999998 gamma t tensor([0.8749], device='cuda:0')
infer: t: 78 t now: 0.21999999999999997 gamma t tensor([0.8851], device='cuda:0')
infer: t: 79 t now: 0.20999999999999996 gamma t tensor([0.8949], device='cuda:0')
infer: t: 80 t now: 0.19999999999999996 gamma t tensor([0.9044], device='cuda:0')
infer: t: 81 t now: 0.18999999999999995 gamma t tensor([0.9134], device='cuda:0')
infer: t: 82 t now: 0.18000000000000005 gamma t tensor([0.9220], device='cuda:0')
infer: t: 83 t now: 0.17000000000000004 gamma t tensor([0.9302], device='cuda:0')
infer: t: 84 t now: 0.16000000000000003 gamma t tensor([0.9380], device='cuda:0')
infer: t: 85 t now: 0.15000000000000002 gamma t tensor([0.9454], device='cuda:0')
infer: t: 86 t now: 0.14 gamma t tensor([0.9523], device='cuda:0')
infer: t: 87 t now: 0.13 gamma t tensor([0.9588], device='cuda:0')
infer: t: 88 t now: 0.12 gamma t tensor([0.9648], device='cuda:0')
infer: t: 89 t now: 0.10999999999999999 gamma t tensor([0.9703], device='cuda:0')
infer: t: 90 t now: 0.09999999999999998 gamma t tensor([0.9754], device='cuda:0')
infer: t: 91 t now: 0.08999999999999997 gamma t tensor([0.9801], device='cuda:0')
infer: t: 92 t now: 0.07999999999999996 gamma t tensor([0.9842], device='cuda:0')
infer: t: 93 t now: 0.06999999999999995 gamma t tensor([0.9879], device='cuda:0')
infer: t: 94 t now: 0.06000000000000005 gamma t tensor([0.9911], device='cuda:0')
infer: t: 95 t now: 0.050000000000000044 gamma t tensor([0.9938], device='cuda:0')
infer: t: 96 t now: 0.040000000000000036 gamma t tensor([0.9960], device='cuda:0')
infer: t: 97 t now: 0.030000000000000027 gamma t tensor([0.9978], device='cuda:0')
infer: t: 98 t now: 0.020000000000000018 gamma t tensor([0.9990], device='cuda:0')
infer: t: 99 t now: 0.010000000000000009 gamma t tensor([0.9997], device='cuda:0')
sample_0 existed
sample_1 existed
sample_2 existed
sample_3 existed
sample_4 existed
sample_5 existed
sample_6 existed
sample_7 existed
sample_8 existed
sample_9 existed
sample_10 existed
54] data_time 0.003717 (0.017168) train_time 28.241844 (28.276620) loss 0.000000 (0.000000)
diffusion_map created
sample_0 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 5.861870765686035
dmean : 1.4313220977783203
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.7296587824821472
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:14:35 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 4.592210292816162
dmean : 0.06188596785068512
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3304797410964966
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:14:36 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_1 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 5.8275628089904785
dmean : 1.400522232055664
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.7295108437538147
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:14:42 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 4.618310451507568
dmean : 0.0615927092730999
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.32935506105422974
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:14:44 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_10 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.9428282976150513
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.33314061164855957
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:14:51 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.003317667171359062
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.19815903902053833
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:14:54 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_2 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 5.2690582275390625
dmean : 1.0227315425872803
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.7088481187820435
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:01 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 4.780116558074951
dmean : 0.05542745068669319
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.30735382437705994
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:03 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_3 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 4.949211120605469
dmean : 0.6001322269439697
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.6558945178985596
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:11 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 4.638291358947754
dmean : 0.04608859494328499
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2773066759109497
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:14 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_4 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 4.529139041900635
dmean : 0.17498838901519775
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.5846114158630371
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:20 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 4.266767501831055
dmean : 0.03645225614309311
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2551235258579254
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:21 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_5 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 3.896991729736328
dmean : -0.21391423046588898
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.511201024055481
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:27 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 3.69305419921875
dmean : 0.02704656310379505
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.24210549890995026
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:29 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_6 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 3.1401891708374023
dmean : -0.5341581106185913
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.44897449016571045
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:37 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 2.9976673126220703
dmean : 0.0179600827395916
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.23392941057682037
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:37 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_7 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 2.3630118370056152
dmean : -0.7629141211509705
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.4041561782360077
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:46 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 2.2776284217834473
dmean : 0.009769725613296032
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.22645223140716553
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:49 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_8 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.6758396625518799
dmean : -0.8921569585800171
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3734668791294098
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:55 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.63656485080719
dmean : 0.0032750738319009542
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.21662306785583496
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:15:57 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
sample_9 created
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.185791015625
dmean : -0.9368425607681274
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.34887105226516724
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:16:04 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -3.22467303276062
dmax : 9.673441886901855
dmean : 0.07801550626754761
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 1.0845046043395996
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 15:34:40 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.1761480569839478
dmean : -0.0010334791149944067
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.20466069877147675
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:16:05 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
trace_backbone.mrc
nx : 177
ny : 177
nz : 166
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 177
my : 177
mz : 166
cella : (177., 177., 166.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.003317667171359062
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (4., 4., 14.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.19815903902053833
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:14:54 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.013942674733698368
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.4121454358100891
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:16:08 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
structure_modeling created
diffusion.mrc
The recording mode in the mrc file:2
XYZ dim:103,102,114
section in unit cell:0,0,0
sampling along X,Y,Z axis of unit cell:103,102,114
cell dimensions in angstroms:103.000000,102.000000,114.000000
Cell angles in degree:90,90,90
axis mode:(1,2,3)
density statistics:min(-1.000000),max(1.000004),mean(-0.013943)
space group number:1
extended data:0
origin state:(41.000000,42.000000,29.000000)
density data shape:
(114, 102, 103)
min density:0.000000
max density:1.000004
number of voxels: 1197684
width of x,y,z:(1.000000,1.000000,1.000000)
order mode:1
useful points: 93655
in total chain useful percentage 0.078197
after normalizing pho dens min 0.0000 max 1.0000
Origin: [41.0, 42.0, 29.0]
detected mode mapc 1, mapr 2, maps 3
LDP_1 created
carry on mean shifting jobs
useful points 93655
set up filters
fmaxd=2.000000
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
finishing meanshifting with 93655 points
here we get the density range 0.964779
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
merging finishing with 22361 left
Origin: (41., 42., 29.)
Previous voxel size: (1., 1., 1.)
nx, ny, nz 103 102 114
nxs,nys,nzs 0 0 0
mx,my,mz 103 102 114
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.013942674733698368
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.4121454358100891
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:16:08 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.0149502754211426
dmean : 0.015903860330581665
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.1258232295513153
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:16:20 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
in total 2 isolated grid points
diffusion.mrc
The recording mode in the mrc file:2
XYZ dim:103,102,114
section in unit cell:0,0,0
sampling along X,Y,Z axis of unit cell:103,102,114
cell dimensions in angstroms:103.000000,102.000000,114.000000
Cell angles in degree:90,90,90
axis mode:(1,2,3)
density statistics:min(-1.000000),max(1.000004),mean(-0.013943)
space group number:1
extended data:0
origin state:(41.000000,42.000000,29.000000)
density data shape:
(114, 102, 103)
min density:0.000000
max density:1.000004
number of voxels: 1197684
width of x,y,z:(1.000000,1.000000,1.000000)
order mode:1
useful points: 93655
in total chain useful percentage 0.078197
after normalizing pho dens min 0.0000 max 1.0000
Origin: [41.0, 42.0, 29.0]
detected mode mapc 1, mapr 2, maps 3
LDP_2 created
carry on mean shifting jobs
useful points 93655
set up filters
fmaxd=4.000000
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
93655
finishing meanshifting with 93655 points
here we get the density range 1.996585
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
merging finishing with 12329 left
Origin: (41., 42., 29.)
Previous voxel size: (1., 1., 1.)
nx, ny, nz 103 102 114
nxs,nys,nzs 0 0 0
mx,my,mz 103 102 114
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.013942674733698368
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.4121454358100891
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:16:08 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.026919886469841003
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2809206247329712
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:16:32 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
in total 7 isolated grid points
WARNING: Use StructureBlurrer.gaussian_blur_real_space_box()to blured a map with a user defined defined cubic box
A created
fit_experiment_0 created
vesper_simu_output_0.out
top global fitting score 54.31
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.013103239238262177
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.11436166614294052
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.013103239238262177
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.11436166614294052
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:18:55 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
B created
fit_experiment_0 created
vesper_simu_output_0.out
top global fitting score 53.62
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.010681496933102608
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.10337524116039276
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.010681496933102608
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.10337524116039276
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:21:07 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
C created
fit_experiment_0 created
vesper_simu_output_0.out
top global fitting score 52.93
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.008136896416544914
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.09033361822366714
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.008136896416544914
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.09033361822366714
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:23:20 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
D created
fit_experiment_0 created
vesper_simu_output_0.out
top global fitting score 52.59
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.005833171308040619
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.07656863331794739
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.005833171308040619
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.07656863331794739
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:25:33 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
structure_assembling created
Initial Score Pool Constructed
current acceptable score is 50.00
400 remained to assemble structures
iterative fitting, still remains:
{'A': 0, 'B': 0, 'C': 0, 'D': 0}
iterative_A created
score 54.31: local refinment!
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : 0.0006575935403816402
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2106841802597046
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 67
ny : 62
nz : 99
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 67
my : 62
mz : 99
cella : (67., 62., 99.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : 0.0023947113659232855
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (75., 81., 38.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3586081266403198
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:25:35 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
iterative_A existed
WARNING: Use StructureBlurrer.gaussian_blur_real_space_box()to blured a map with a user defined defined cubic box
#0.pdb score:55.52
before vesper local fitting score: 54.31
after vesper local fitting score: 55.52
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.017232997342944145
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3826636075973511
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.017232997342944145
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3826636075973511
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:28:44 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563406944274902
dmean : 0.022049186751246452
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2542229890823364
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563406944274902
dmean : 0.022049186751246452
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2542229890823364
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:28:46 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
#0.pdb remove because of the overlap too big 0.75
#1.pdb remove because of the overlap too big 0.8413793103448276
#5.pdb remove because of the overlap too big 0.13620689655172413
#6.pdb remove because of the overlap too big 0.6706896551724137
#7.pdb remove because of the overlap too big 0.11206896551724138
#3.pdb remove because of the overlap too big 0.12241379310344827
#4.pdb remove because of the overlap too big 0.12241379310344827
#3.pdb remove because of the overlap too big 0.13275862068965516
#8.pdb remove because of the overlap too big 0.11724137931034483
#9.pdb remove because of the overlap too big 0.1810344827586207
#10.pdb remove because of the overlap too big 0.1103448275862069
#11.pdb remove because of the overlap too big 0.10689655172413794
#12.pdb remove because of the overlap too big 0.07413793103448275
#13.pdb remove because of the overlap too big 0.13620689655172413
#5.pdb remove because of the overlap too big 0.12413793103448276
#14.pdb remove because of the overlap too big 0.11551724137931034
#16.pdb remove because of the overlap too big 0.11551724137931034
#17.pdb remove because of the overlap too big 0.11551724137931034
#7.pdb remove because of the overlap too big 0.11724137931034483
#18.pdb remove because of the overlap too big 0.1310344827586207
#19.pdb remove because of the overlap too big 0.11551724137931034
#20.pdb remove because of the overlap too big 0.10862068965517241
#21.pdb remove because of the overlap too big 0.0706896551724138
#22.pdb remove because of the overlap too big 0.11206896551724138
#23.pdb remove because of the overlap too big 0.506896551724138
#24.pdb remove because of the overlap too big 0.1103448275862069
#25.pdb remove because of the overlap too big 0.16551724137931034
#8.pdb remove because of the overlap too big 0.11379310344827587
#26.pdb remove because of the overlap too big 0.0896551724137931
#27.pdb remove because of the overlap too big 0.1706896551724138
#9.pdb remove because of the overlap too big 0.0896551724137931
#10.pdb remove because of the overlap too big 0.0896551724137931
#7.pdb remove because of the overlap too big 0.0896551724137931
#8.pdb remove because of the overlap too big 0.0896551724137931
initial candidates still remained 17
still remains 3 chains
iterative fitting, still remains:
{'A': 1, 'B': 0, 'C': 0, 'D': 0}
iterative_B created
score 53.62: local refinment!
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.005698038265109062
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.20155172049999237
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 63
ny : 73
nz : 99
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 63
my : 73
mz : 99
cella : (63., 73., 99.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.014791193418204784
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (80., 44., 38.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3261460065841675
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:28:49 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
iterative_B existed
WARNING: Use StructureBlurrer.gaussian_blur_real_space_box()to blured a map with a user defined defined cubic box
#0.pdb score:53.28
before vesper local fitting score: 53.62
after vesper local fitting score: 53.28
#2.pdb
Score: 53.62
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.01689133420586586
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3513621687889099
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.01689133420586586
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3513621687889099
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:31:57 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563406944274902
dmean : 0.017897317185997963
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.22905376553535461
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563406944274902
dmean : 0.017897317185997963
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.22905376553535461
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:31:59 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
#2.pdb remove because of the overlap too big 1.0
#0.pdb remove because of the overlap too big 1.0
initial candidates still remained 15
still remains 2 chains
iterative fitting, still remains:
{'A': 1, 'B': 1, 'C': 0, 'D': 0}
iterative_C created
score 52.93: local refinment!
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.0016728183254599571
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.20537473261356354
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 64
ny : 69
nz : 99
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 64
my : 69
mz : 99
cella : (64., 69., 99.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.004347190726548433
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 74., 40.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3394361138343811
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:32:01 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
iterative_C existed
WARNING: Use StructureBlurrer.gaussian_blur_real_space_box()to blured a map with a user defined defined cubic box
#0.pdb score:52.59
before vesper local fitting score: 52.93
after vesper local fitting score: 52.59
#3.pdb
Score: 52.93
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.01839485950767994
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.31625208258628845
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.01839485950767994
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.31625208258628845
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:35:10 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563406944274902
dmean : 0.013454746454954147
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.19840289652347565
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563406944274902
dmean : 0.013454746454954147
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.19840289652347565
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:35:12 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
#3.pdb remove because of the overlap too big 1.0
#1.pdb remove because of the overlap too big 1.0
#0.pdb remove because of the overlap too big 1.0
#4.pdb remove because of the overlap too big 0.2
#5.pdb remove because of the overlap too big 0.2
#2.pdb remove because of the overlap too big 0.2103448275862069
#15.pdb remove because of the overlap too big 0.8568965517241379
#6.pdb remove because of the overlap too big 0.8568965517241379
#6.pdb remove because of the overlap too big 0.8568965517241379
initial candidates still remained 6
still remains 1 chains
iterative fitting, still remains:
{'A': 1, 'B': 1, 'C': 1, 'D': 0}
iterative_D created
score 52.59: local refinment!
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.006848947610706091
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.19853484630584717
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 69
ny : 64
nz : 99
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 69
my : 64
mz : 99
cella : (69., 64., 99.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.01842673309147358
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 40.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.32768166065216064
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:35:15 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
iterative_D existed
WARNING: Use StructureBlurrer.gaussian_blur_real_space_box()to blured a map with a user defined defined cubic box
#0.pdb score:53.62
before vesper local fitting score: 52.59
after vesper local fitting score: 53.62
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.016909440979361534
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2775791883468628
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.016909440979361534
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2775791883468628
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:38:24 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563406944274902
dmean : 0.009569349698722363
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.16721506416797638
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 103
ny : 102
nz : 114
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 103
my : 102
mz : 114
cella : (103., 102., 114.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563406944274902
dmean : 0.009569349698722363
ispg : 1
nsymbt : 0
extra1 : b'\x00\x00\x00\x00\x00\x00\x00\x00'
exttyp : b''
nversion : 20141
extra2 : b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
origin : (41., 42., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.16721506416797638
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 16:38:26 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
#4.pdb remove because of the overlap too big 0.593103448275862
#2.pdb remove because of the overlap too big 0.593103448275862
#1.pdb remove because of the overlap too big 0.6275862068965518
#0.pdb remove because of the overlap too big 0.593103448275862
#2.pdb remove because of the overlap too big 0.6448275862068965
#1.pdb remove because of the overlap too big 0.6448275862068965
initial candidates still remained 0
still remains 0 chains
INFO : DiffModeler Prediction Done















If the output looks wrong or the job has failed. You can submit it for review here.