pytorch-crf
pytorch-crf copied to clipboard
kmkurn
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
self.all_crf_list：[CRF(num_tags=3), CRF(num_tags=13)] all_logits_list： [tensor([[[-3.9874e+36, 1.4790e+13, -3.9874e+36], [-3.9874e+36, -7.3833e+12, -3.9874e+36], [-3.9874e+36, -2.0520e+12, -3.9874e+36], ..., [-3.9874e+36, -2.2289e+12, -3.9874e+36], [-3.9874e+36, 3.4035e+12, -3.9874e+36], [-3.9874e+36, -4.3337e+12, -3.9874e+36]],
[[-3.9874e+36, -2.3061e+12, -3.9874e+36],
[-3.9874e+36, -5.0479e+12, -3.9874e+36],
[-3.9874e+36, -6.4114e+12, -3.9874e+36],
...,
[-3.9874e+36, -4.6448e+12, -3.9874e+36],
[-3.9874e+36, -4.5191e+11, -3.9874e+36],
[-3.9874e+36, -3.6027e+12, -3.9874e+36]],
[[-3.9874e+36, -1.0979e+13, -3.9874e+36],
[-3.9874e+36, 1.6786e+12, -3.9874e+36],
[-3.9874e+36, -1.4357e+13, -3.9874e+36],
...,
[-3.9874e+36, -1.4507e+12, -3.9874e+36],
[-3.9874e+36, -1.1688e+12, -3.9874e+36],
[-3.9874e+36, -3.1413e+12, -3.9874e+36]],
...,
[[-3.9874e+36, -9.3924e+12, -3.9874e+36],
[-3.9874e+36, -7.9630e+12, -3.9874e+36],
[-3.9874e+36, -1.8307e+13, -3.9874e+36],
...,
[-3.9874e+36, 2.5791e+12, -3.9874e+36],
[-3.9874e+36, -5.5233e+12, -3.9874e+36],
[-3.9874e+36, -4.3978e+12, -3.9874e+36]],
[[-3.9874e+36, -5.4722e+12, -3.9874e+36],
[-3.9874e+36, -7.1854e+12, -3.9874e+36],
[-3.9874e+36, 8.8407e+12, -3.9874e+36],
...,
[-3.9874e+36, -8.6247e+12, -3.9874e+36],
[-3.9874e+36, -8.2108e+12, -3.9874e+36],
[-3.9874e+36, -8.4145e+12, -3.9874e+36]],
[[-3.9874e+36, 8.5906e+12, -3.9874e+36],
[-3.9874e+36, 7.3230e+12, -3.9874e+36],
[-3.9874e+36, 9.9933e+12, -3.9874e+36],
...,
[-3.9874e+36, -8.2361e+12, -3.9874e+36],
[-3.9874e+36, 4.3975e+12, -3.9874e+36],
[-3.9874e+36, 2.7981e+12, -3.9874e+36]]], device='cuda:0',
grad_fn=<ViewBackward0>), tensor([[[ 1.9106e+35, 2.6347e+13, 2.6358e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 8.9022e+36, 1.2304e+13, 1.2308e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 1.7277e+36, 2.7635e+13, 2.7643e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
...,
[ 1.1412e+35, 1.4332e+13, 1.4339e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 5.5772e+36, 1.0666e+13, 1.0674e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 5.5625e+36, 1.0355e+13, 1.0363e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00]],
[[ 3.7168e+36, 1.8778e+12, 1.8797e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 4.9625e+36, -2.1684e+12, -2.1664e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 3.0125e+36, 2.0084e+13, 2.0092e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
...,
[ 5.3837e+36, 5.4529e+12, 5.4594e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 4.9884e+36, 1.1655e+13, 1.1666e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 4.5793e+36, 4.0014e+12, 4.0107e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00]],
[[ 2.6895e+36, -6.3378e+12, -6.3468e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 3.2308e+36, 1.3881e+13, 1.3889e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 5.6345e+36, -1.6707e+13, -1.6720e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
...,
[-1.3854e+36, 5.2608e+12, 5.2626e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[-2.0923e+36, 4.7293e+12, 4.7297e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[-2.6322e+36, 1.3399e+12, 1.3388e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00]],
...,
[[ 3.2878e+36, -3.0469e+12, -3.0491e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 7.7211e+36, 1.0207e+13, 1.0212e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[-7.8782e+35, -7.6391e+11, -7.6446e+11, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
...,
[-2.3411e+36, 4.7278e+12, 4.7314e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 5.0340e+34, 5.7587e+12, 5.7638e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 4.7138e+36, -2.1504e+12, -2.1481e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00]],
[[-1.4105e+36, -2.8080e+12, -2.8100e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 2.1937e+36, 9.3866e+12, 9.3888e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[-2.4729e+36, 6.7364e+12, 6.7393e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
...,
[-2.9569e+36, 4.7332e+12, 4.7349e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[-4.6596e+36, 5.5627e+12, 5.5597e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[-5.2336e+36, 1.0084e+13, 1.0084e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00]],
[[-4.4111e+36, 1.4338e+13, 1.4346e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 4.9879e+36, 1.0435e+13, 1.0440e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[-1.9851e+36, 1.9111e+13, 1.9120e+13, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
...,
[ 3.9176e+36, 9.3128e+11, 9.3609e+11, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 4.3824e+36, 7.6145e+12, 7.6245e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00],
[ 4.4330e+36, 7.0763e+12, 7.0844e+12, ..., 0.0000e+00,
0.0000e+00, 0.0000e+00]]], device='cuda:0',
grad_fn=<ViewBackward0>)]
self.labels_split= [tensor([[-100, 1, 2, ..., -100, -100, -100], [-100, 1, 2, ..., -100, -100, -100], [-100, 1, 2, ..., -100, -100, -100], ..., [-100, 1, 2, ..., -100, -100, -100], [-100, 0, 0, ..., -100, -100, -100], [-100, 1, 2, ..., -100, -100, -100]], device='cuda:0'), tensor([[-100, 6, 12, ..., -100, -100, -100], [-100, 6, 12, ..., -100, -100, -100], [-100, 0, 0, ..., -100, -100, -100], ..., [-100, 0, 0, ..., -100, -100, -100], [-100, 0, 0, ..., -100, -100, -100], [-100, 6, 12, ..., -100, -100, -100]], device='cuda:0')]
[-crf(lo, la, reduction='mean') for crf, lo, la in zip(self.all_crf_list, all_logits_list, labels_split)]
跑不通 Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
