DiffModeler

Job ID : ded5b78208981b434c2c67a970fef227

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 11:44:09 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
single_chain_pdb
Q99J21.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 2.000000
revised contour 0.221125
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 0.534385 (0.534385) train_time 28.180323 (28.180323) 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 0.005892 (0.270138) train_time 27.076727 (27.628525) 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 0.015051 (0.185109) train_time 27.796996 (27.684682) 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 0.004985 (0.140078) train_time 27.621784 (27.668958) 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 0.007324 (0.113527) train_time 27.817948 (27.698756) 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 0.005558 (0.095532) train_time 28.361005 (27.809131) 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 0.002312 (0.082215) train_time 27.783702 (27.805498) 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 0.007417 (0.072865) train_time 27.926906 (27.820674) 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 0.002666 (0.065066) train_time 28.299444 (27.873871) 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 0.002721 (0.058831) train_time 28.452905 (27.931774) 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 0.008705 (0.054274) train_time 27.934048 (27.931981) 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 0.002634 (0.049971) train_time 28.407154 (27.971579) 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 0.001807 (0.046266) train_time 27.990147 (27.973007) 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 0.007737 (0.043514) train_time 27.969689 (27.972770) 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 0.002098 (0.040753) train_time 28.641911 (28.017379) 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 0.005894 (0.038574) train_time 28.409163 (28.041866) 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 0.003299 (0.036499) train_time 28.117596 (28.046321) 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 0.008566 (0.034947) train_time 28.303122 (28.060587) 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 0.002090 (0.033218) train_time 28.093818 (28.062336) 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 0.003643 (0.031739) train_time 28.183980 (28.068418) 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 0.004755 (0.030454) train_time 28.321116 (28.080452) 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 0.002476 (0.029182) train_time 28.397639 (28.094869) 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 0.002033 (0.028002) train_time 28.497946 (28.112394) 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 0.004056 (0.027004) train_time 28.147601 (28.113861) 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 0.003377 (0.026059) train_time 28.392753 (28.125017) 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 0.001915 (0.025131) train_time 28.265999 (28.130439) 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 0.002051 (0.024276) train_time 28.461047 (28.142684) 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 0.003716 (0.023542) train_time 28.206384 (28.144959) 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 0.002722 (0.022824) train_time 28.187328 (28.146420) 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 0.002585 (0.022149) train_time 28.124362 (28.145685) 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 0.002246 (0.021507) train_time 28.221603 (28.148134) 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 0.002619 (0.020917) train_time 28.077584 (28.145929) 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 0.002628 (0.020363) train_time 28.213941 (28.147990) 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 0.002158 (0.019827) train_time 28.173234 (28.148733) 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 0.002238 (0.019325) train_time 28.027333 (28.145264) 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 0.002264 (0.018851) train_time 28.188935 (28.146477) 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 0.011874 (0.018662) train_time 28.356606 (28.152156) 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 0.006250 (0.018335) train_time 28.158782 (28.152331) 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 0.002467 (0.017929) train_time 28.117104 (28.151427) 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 0.002405 (0.017541) train_time 28.242286 (28.153699) 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 0.011066 (0.017383) train_time 28.211511 (28.155109) 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 0.001776 (0.017011) train_time 28.169980 (28.155463) 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 0.001837 (0.016658) train_time 28.439965 (28.162079) 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 0.009716 (0.016500) train_time 28.342108 (28.166171) 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 0.004595 (0.016236) train_time 28.139471 (28.165577) 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 0.009122 (0.016081) train_time 28.246186 (28.167330) 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 0.002298 (0.015788) train_time 28.438082 (28.173090) 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 0.004840 (0.015560) train_time 28.081769 (28.171188) 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 0.013719 (0.015522) train_time 28.160903 (28.170978) 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 0.002169 (0.015255) train_time 28.224921 (28.172057) 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 0.004200 (0.015038) train_time 28.458317 (28.177670) 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 0.006449 (0.014873) train_time 28.113355 (28.176433) 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 0.003479 (0.014658) train_time 28.405006 (28.180746) 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 0.013059 (0.014629) train_time 28.200917 (28.181119) 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 11:44:09 '
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 : 5.299100875854492
dmean : 1.4311480522155762
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 : 0.7293558120727539
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:19 '
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 11:44:09 '
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 : 5.021738052368164
dmean : 0.10980329662561417
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 : 0.43385621905326843
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:20 '
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 11:44:09 '
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 : 5.265072345733643
dmean : 1.4003511667251587
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 : 0.7292097806930542
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:25 '
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 11:44:09 '
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 : 4.987875461578369
dmean : 0.10862910002470016
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 : 0.43015655875205994
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:26 '
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 11:44:09 '
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 : -0.9430050849914551
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 : 0.33263248205184937
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:30 '
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 11:44:09 '
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 : -0.027348682284355164
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 : 0.2633155286312103
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:31 '
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 11:44:09 '
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 : 4.902483940124512
dmean : 1.022610068321228
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 : 0.7085807919502258
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:37 '
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 11:44:09 '
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 : 4.838048458099365
dmean : 0.09164212644100189
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 : 0.380502849817276
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:38 '
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 11:44:09 '
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 : 4.774104118347168
dmean : 0.6000829935073853
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 : 0.6557639241218567
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:44 '
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 11:44:09 '
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 : 4.715838432312012
dmean : 0.07006503641605377
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 : 0.3256257474422455
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:44 '
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 11:44:09 '
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 : 4.381374359130859
dmean : 0.17495372891426086
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 : 0.5845696330070496
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:49 '
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 11:44:09 '
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 : 4.332206726074219
dmean : 0.047992512583732605
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 : 0.2867743968963623
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:50 '
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 11:44:09 '
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 : 3.782137632369995
dmean : -0.21398751437664032
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 : 0.5111744403839111
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:55 '
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 11:44:09 '
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 : 3.743919610977173
dmean : 0.02704951912164688
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 : 0.2709929645061493
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:56 '
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 11:44:09 '
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 : 3.0599236488342285
dmean : -0.5342527627944946
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 : 0.448925256729126
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:59 '
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 11:44:09 '
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 : 3.033214569091797
dmean : 0.00818975642323494
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 : 0.27177560329437256
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:59 '
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 11:44:09 '
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 : 2.3149254322052
dmean : -0.7630215287208557
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 : 0.4039915204048157
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:05 '
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 11:44:09 '
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 : 2.298924446105957
dmean : -0.007314635906368494
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 : 0.2769940495491028
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:05 '
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 11:44:09 '
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 : 1.6537206172943115
dmean : -0.8922748565673828
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 : 0.3732224106788635
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:09 '
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 11:44:09 '
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 : 1.6463606357574463
dmean : -0.018257642164826393
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 : 0.2768583595752716
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:09 '
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 11:44:09 '
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 : 1.1803616285324097
dmean : -0.9369597434997559
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 : 0.348560094833374
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:14 '
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 11:44:09 '
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 : 1.1785539388656616
dmean : -0.024442316964268684
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 : 0.2690922021865845
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:15 '
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 : -0.027348682284355164
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 : 0.2633155286312103
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:10:31 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.09030772745609283
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.47396320104599
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:16 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
structure_modeling created
diffusion.mrc
The recording mode in the mrc file:2
XYZ dim:115,113,120
section in unit cell:0,0,0
sampling along X,Y,Z axis of unit cell:115,113,120
cell dimensions in angstroms:115.000000,113.000000,120.000000
Cell angles in degree:90,90,90
axis mode:(1,2,3)
density statistics:min(-1.000000),max(1.000004),mean(-0.090308)
space group number:1
extended data:0
origin state:(35.000000,36.000000,29.000000)
density data shape:
(120, 113, 115)
min density:0.000000
max density:1.000004
number of voxels: 1559400
width of x,y,z:(1.000000,1.000000,1.000000)
order mode:1
useful points: 111320
in total chain useful percentage 0.071386
after normalizing pho dens min 0.0000 max 1.0000
Origin: [35.0, 36.0, 29.0]
detected mode mapc 1, mapr 2, maps 3
LDP_1 created
carry on mean shifting jobs
useful points 111320
set up filters
fmaxd=2.000000
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
finishing meanshifting with 111320 points
here we get the density range 0.957646
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
110000
merging finishing with 26681 left
Origin: (35., 36., 29.)
Previous voxel size: (1., 1., 1.)
nx, ny, nz 115 113 120
nxs,nys,nzs 0 0 0
mx,my,mz 115 113 120
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.09030772745609283
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.47396320104599
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:16 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.0149502754211426
dmean : 0.014463278464972973
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.12006860971450806
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:30 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
in total 6 isolated grid points
diffusion.mrc
The recording mode in the mrc file:2
XYZ dim:115,113,120
section in unit cell:0,0,0
sampling along X,Y,Z axis of unit cell:115,113,120
cell dimensions in angstroms:115.000000,113.000000,120.000000
Cell angles in degree:90,90,90
axis mode:(1,2,3)
density statistics:min(-1.000000),max(1.000004),mean(-0.090308)
space group number:1
extended data:0
origin state:(35.000000,36.000000,29.000000)
density data shape:
(120, 113, 115)
min density:0.000000
max density:1.000004
number of voxels: 1559400
width of x,y,z:(1.000000,1.000000,1.000000)
order mode:1
useful points: 111320
in total chain useful percentage 0.071386
after normalizing pho dens min 0.0000 max 1.0000
Origin: [35.0, 36.0, 29.0]
detected mode mapc 1, mapr 2, maps 3
LDP_2 created
carry on mean shifting jobs
useful points 111320
set up filters
fmaxd=4.000000
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
111320
finishing meanshifting with 111320 points
here we get the density range 2.056336
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
110000
merging finishing with 14844 left
Origin: (35., 36., 29.)
Previous voxel size: (1., 1., 1.)
nx, ny, nz 115 113 120
nxs,nys,nzs 0 0 0
mx,my,mz 115 113 120
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.09030772745609283
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.47396320104599
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:16 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.02496131882071495
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2704986035823822
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:11:47 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
in total 6 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 58.62
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.0149502754211426
dmean : 0.0120342206209898
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.10965025424957275
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.0149502754211426
dmean : 0.0120342206209898
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.10965025424957275
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:14:33 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
B created
fit_experiment_0 created
vesper_simu_output_0.out
top global fitting score 57.07
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.0149502754211426
dmean : 0.01002494990825653
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.10017595440149307
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.0149502754211426
dmean : 0.01002494990825653
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.10017595440149307
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:16:58 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
C created
fit_experiment_0 created
vesper_simu_output_0.out
top global fitting score 56.55
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.0149502754211426
dmean : 0.007858585566282272
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.08878017961978912
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.0149502754211426
dmean : 0.007858585566282272
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.08878017961978912
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:19:22 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
D created
fit_experiment_0 created
vesper_simu_output_0.out
top global fitting score 54.14
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.005999104119837284
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.0776330977678299
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 1.014950156211853
dmean : 0.005999104119837284
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.0776330977678299
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:21:50 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
structure_assembling created
Initial Score Pool Constructed
current acceptable score is 51.90
400 remained to assemble structures
iterative fitting, still remains:
{'A': 0, 'B': 0, 'C': 0, 'D': 0}
iterative_A created
score 58.62: local refinment!
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.019153442233800888
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2456192821264267
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 77
ny : 66
nz : 105
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 77
my : 66
mz : 105
cella : (77., 66., 105.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.05569775030016899
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 : (66., 79., 38.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.4170439839363098
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:21:51 '
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:58.10
before vesper local fitting score: 58.62
after vesper local fitting score: 58.10
#0.pdb
Score: 58.62
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.08508581668138504
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.44346731901168823
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.08508581668138504
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.44346731901168823
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:25:14 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.0206147450953722
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.24571149051189423
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.0206147450953722
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.24571149051189423
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:25:16 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
#0.pdb remove because of the overlap too big 1.0
#3.pdb remove because of the overlap too big 0.8568965517241379
#4.pdb remove because of the overlap too big 0.8931034482758621
#5.pdb remove because of the overlap too big 0.7017241379310345
#8.pdb remove because of the overlap too big 0.1
#9.pdb remove because of the overlap too big 0.1
#10.pdb remove because of the overlap too big 0.11896551724137931
#11.pdb remove because of the overlap too big 0.10689655172413794
#12.pdb remove because of the overlap too big 0.10689655172413794
#4.pdb remove because of the overlap too big 0.1
#5.pdb remove because of the overlap too big 0.1
#13.pdb remove because of the overlap too big 0.44655172413793104
#14.pdb remove because of the overlap too big 0.07586206896551724
#15.pdb remove because of the overlap too big 0.09827586206896552
#16.pdb remove because of the overlap too big 0.07586206896551724
#17.pdb remove because of the overlap too big 0.20862068965517241
#6.pdb remove because of the overlap too big 0.07586206896551724
#4.pdb remove because of the overlap too big 0.07586206896551724
#18.pdb remove because of the overlap too big 0.06206896551724138
#7.pdb remove because of the overlap too big 0.06206896551724138
#5.pdb remove because of the overlap too big 0.06206896551724138
#19.pdb remove because of the overlap too big 0.10862068965517241
#6.pdb remove because of the overlap too big 0.22758620689655173
#20.pdb remove because of the overlap too big 0.22586206896551725
#21.pdb remove because of the overlap too big 0.05172413793103448
#22.pdb remove because of the overlap too big 0.16034482758620688
#23.pdb remove because of the overlap too big 0.3086206896551724
#8.pdb remove because of the overlap too big 0.05172413793103448
#24.pdb remove because of the overlap too big 0.11379310344827587
#25.pdb remove because of the overlap too big 0.10689655172413794
#26.pdb remove because of the overlap too big 0.11551724137931034
#27.pdb remove because of the overlap too big 0.06896551724137931
#28.pdb remove because of the overlap too big 0.08275862068965517
#9.pdb remove because of the overlap too big 0.07586206896551724
#7.pdb remove because of the overlap too big 0.09655172413793103
#8.pdb remove because of the overlap too big 0.09655172413793103
#9.pdb remove because of the overlap too big 0.07586206896551724
#29.pdb remove because of the overlap too big 0.15
#30.pdb remove because of the overlap too big 0.5706896551724138
#31.pdb remove because of the overlap too big 0.07241379310344828
#32.pdb remove because of the overlap too big 0.09655172413793103
#33.pdb remove because of the overlap too big 0.08620689655172414
#34.pdb remove because of the overlap too big 0.09655172413793103
#35.pdb remove because of the overlap too big 0.12758620689655173
#10.pdb remove because of the overlap too big 0.09655172413793103
#12.pdb remove because of the overlap too big 0.08620689655172414
#13.pdb remove because of the overlap too big 0.09655172413793103
#14.pdb remove because of the overlap too big 0.06379310344827586
#11.pdb remove because of the overlap too big 0.06379310344827586
#36.pdb remove because of the overlap too big 0.09137931034482759
#37.pdb remove because of the overlap too big 0.17413793103448275
#38.pdb remove because of the overlap too big 0.07413793103448275
#15.pdb remove because of the overlap too big 0.08103448275862069
#17.pdb remove because of the overlap too big 0.07413793103448275
#13.pdb remove because of the overlap too big 0.17413793103448275
#2.pdb remove because of the overlap too big 0.0706896551724138
#39.pdb remove because of the overlap too big 0.1810344827586207
#40.pdb remove because of the overlap too big 0.11206896551724138
#19.pdb remove because of the overlap too big 0.11206896551724138
#20.pdb remove because of the overlap too big 0.06724137931034482
#21.pdb remove because of the overlap too big 0.08275862068965517
#15.pdb remove because of the overlap too big 0.08275862068965517
initial candidates still remained 20
still remains 3 chains
iterative fitting, still remains:
{'A': 1, 'B': 0, 'C': 0, 'D': 0}
iterative_B created
score 57.07: local refinment!
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.02445029467344284
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.23538653552532196
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 64
ny : 77
nz : 104
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 64
my : 77
mz : 104
cella : (64., 77., 104.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.07424956560134888
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., 42., 38.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.40580230951309204
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:25:18 '
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:56.38
before vesper local fitting score: 57.07
after vesper local fitting score: 56.38
#1.pdb
Score: 57.07
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.07612711936235428
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.4124530553817749
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.07612711936235428
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.4124530553817749
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:28:50 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.017052363604307175
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.22350051999092102
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.017052363604307175
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.22350051999092102
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:28:51 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
#1.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 18
still remains 2 chains
iterative fitting, still remains:
{'A': 1, 'B': 1, 'C': 0, 'D': 0}
iterative_C created
score 56.55: local refinment!
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.021231746301054955
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.23917734622955322
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 66
ny : 76
nz : 105
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 66
my : 76
mz : 105
cella : (66., 76., 105.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.06258799135684967
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 : (40., 67., 38.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.40804731845855713
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:28:53 '
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:56.72
before vesper local fitting score: 56.55
after vesper local fitting score: 56.72
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.06902829557657242
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.37794312834739685
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.06902829557657242
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.37794312834739685
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:32:26 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.013035973533987999
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.19517557322978973
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.013035973533987999
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.19517557322978973
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:32:28 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
#2.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
#7.pdb remove because of the overlap too big 0.7724137931034483
#3.pdb remove because of the overlap too big 0.7724137931034483
#3.pdb remove because of the overlap too big 0.7724137931034483
#11.pdb remove because of the overlap too big 0.45
#10.pdb remove because of the overlap too big 0.45
#16.pdb remove because of the overlap too big 0.2413793103448276
#18.pdb remove because of the overlap too big 0.2413793103448276
#12.pdb remove because of the overlap too big 0.2413793103448276
#14.pdb remove because of the overlap too big 0.2413793103448276
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 54.14: local refinment!
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.02482740581035614
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.2256019115447998
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 72
ny : 64
nz : 104
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 72
my : 64
mz : 104
cella : (72., 64., 104.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.0796687975525856
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 : (43., 41., 38.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.4001252055168152
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:32:30 '
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:53.97
before vesper local fitting score: 54.14
after vesper local fitting score: 53.97
#6.pdb
Score: 54.14
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.0591483935713768
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3410889506340027
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : -1.0
dmax : 1.0000038146972656
dmean : -0.0591483935713768
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.3410889506340027
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:36:04 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.009714116342365742
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.1682998090982437
nlabl : 1
label : [b'Created by TEMPy on: 2023-11-09' b'' b'' b'' b'' b'' b'' b'' b'' b'']
nx : 115
ny : 113
nz : 120
mode : 2
nxstart : 0
nystart : 0
nzstart : 0
mx : 115
my : 113
mz : 120
cella : (115., 113., 120.)
cellb : (90., 90., 90.)
mapc : 1
mapr : 2
maps : 3
dmin : 0.0
dmax : 3.0563409328460693
dmean : 0.009714116342365742
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 : (35., 36., 29.)
map : b'MAP '
machst : [68 68 0 0]
rms : 0.1682998090982437
nlabl : 1
label : [b'Created by mrcfile.py 2023-11-09 12:36:05 '
b'' b'' b'' b'' b'' b'' b'' b'' b'']
#6.pdb remove because of the overlap too big 1.0
#2.pdb remove because of the overlap too big 1.0
#1.pdb remove because of the overlap too big 1.0
#2.pdb remove because of the overlap too big 1.0
#0.pdb remove because of the overlap too big 1.0
#1.pdb remove because of the overlap too big 1.0
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.