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inference.log
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# The inference output might be:
torch.Size([1, 100, 13])
torch.Size([1, 25, 112, 112])
tensor([[-0.0887, -0.0948, -0.0021, ..., 0.7376, -0.1593, -0.1588],
[-0.1069, -0.0945, -0.0028, ..., 0.7364, -0.1590, -0.1591],
[-0.1116, -0.0940, -0.0036, ..., 0.7350, -0.1588, -0.1595],
...,
[-0.0184, -0.0815, -0.0253, ..., 0.3925, -0.1646, -0.1462],
[-0.0152, -0.0798, -0.0333, ..., 0.3358, -0.1695, -0.1300],
[-0.0136, -0.0779, -0.0470, ..., 0.1228, 0.1252, -0.1512]])
torch.Size([25, 128])
==========================
torch.Size([1, 200, 13])
torch.Size([1, 50, 112, 112])
tensor([[-0.10590755 -0.0885424 0.00964742 ... 0.78541106 -0.16136746 -0.15291189]
[-0.11187012 -0.08820734 0.00944356 ... 0.78670716 -0.15966198 -0.15319586]
[-0.11497926 -0.08787549 0.00908665 ... 0.78717077 -0.15922906 -0.15342724]
...
[-0.02891648 -0.05359361 -0.0116765 ... 0.44861248 -0.1651328 -0.14146683]
[-0.02247998 -0.05153918 -0.01845645 ... 0.37009075 -0.1694393 -0.12486269]
[-0.02042701 -0.04920176 -0.02980761 ... 0.14132908 0.0638896 -0.14834262]])
torch.Size([50, 128])
======================================
torch.Size([1, 84, 13])
torch.Size([1, 21, 112, 112])
tensor([[ 0.02173683 0.7959661 -0.02629013 ... 0.09069754 0.22159217 -0.01207334]
[ 0.02201553 0.810594 -0.02790174 ... 0.08995613 0.19760351 -0.01551662]
[ 0.0218851 0.82863694 -0.03179551 ... 0.08902452 0.18390514 -0.01514692]
...
[ 0.01304861 0.11315729 0.01856261 ... 0.08940861 0.00458653 0.00400829]
[ 0.0118171 0.06813843 0.02143023 ... 0.08527904 -0.02095525 -0.00280911]
[ 0.01047295 -0.00415571 0.02270312 ... 0.07493475 -0.05328951 -0.01202559]])
torch.Size([21, 128])
=======================================
torch.Size([1, 400, 13])
torch.Size([1, 100, 112, 112])
tensor([[-0.00352758 0.83813536 0.09201904 ... 0.40371484 0.27853543 -0.00917351]
[-0.00370954 0.8379351 0.08970974 ... 0.4165748 0.13884643 -0.01080725]
[-0.00398439 0.83760494 0.0865115 ... 0.42264128 0.0773297 -0.01209168]
...
[-0.01376476 -0.05013295 0.06964908 ... 0.38606793 -0.16800241 0.01603755]
[-0.0115702 -0.04844839 0.0665013 ... 0.31757268 -0.16577664 0.02324991]
[-0.01053312 -0.04700252 0.06004376 ... 0.13100827 0.07428606 -0.03262951]])
torch.Size([100, 128])
# The start scores for the test data are:
[-3.214273 -3.6669817 -3.8399193 -3.9743302 -4.159114 -4.3499117
-4.3989267 -4.404181 -4.4411807 -4.43583 -4.377288 -4.2411027
-4.247399 -4.2412534 -4.0229306 -3.8560483 -3.8146665 -3.9160302
-3.9888375 -4.0244155 -3.939712 -3.678749 -3.2006643 -2.9725544
-2.19283 ]
[-2.0738566 -2.5114522 -2.8330786 -2.941253 -2.491425 -2.6769667
-2.8156152 -3.1470816 -3.2858593 -3.4103734 -3.6339047 -3.7652538
-3.9284477 -4.0566387 -4.1676793 -4.247504 -4.2168856 -4.227703
-4.1786346 -4.0691996 -3.9831212 -3.8217425 -3.3898883 -2.926102
-2.1954176]
[0.17597255 0.20986646 0.25299045 0.7798105 1.071713 1.1942053
1.2717576 1.4455926 1.5154485 1.699275 1.8517779 1.7052683
1.6057909 1.4765203 1.4153332 1.3371235 1.2516025 1.1912241
1.0783631 0.9818315 0.85924524 0.75021565 0.6695677 0.4915204
0.38098097]
[ 1.0879407 1.15037 1.2204249 1.2118441 1.2185776 1.1750311
1.1902214 1.1662662 1.1200147 1.1270055 1.0646596 0.9427329
0.8822885 0.7603179 0.5396047 0.2516482 -0.17553289 -0.84684455
-1.532304 -1.9274075 -2.2282622 -2.631992 -2.7213569 -2.7395864
-2.1192882 ]