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layer issu
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> /content/trans-vsumm/seq_sum.py(78)forward() | |
-> src = layer(src, src_mask) | |
(Pdb) src.shape | |
torch.Size([461, 1024, 256]) | |
(Pdb) src_mask.shape | |
torch.Size([461, 1, 1, 1024]) | |
> /content/trans-vsumm/seq_sum.py(78)forward() | |
-> src = layer(src, src_mask) | |
(Pdb) src.shape | |
torch.Size([461, 1024, 256]) | |
(Pdb) src_mask.shape | |
torch.Size([461, 1, 1, 1024]) | |
(Pdb) self.layers | |
ModuleList( | |
(0): EncoderLayer( | |
(self_attn_layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) | |
(ff_layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) | |
(self_attention): MultiHeadAttentionLayer( | |
(fc_q): Linear(in_features=1024, out_features=1024, bias=False) | |
(fc_k): Linear(in_features=1024, out_features=1024, bias=False) | |
(fc_v): Linear(in_features=1024, out_features=1024, bias=False) | |
(fc_o): Linear(in_features=1024, out_features=1024, bias=False) | |
(dropout): Dropout(p=0.1, inplace=False) | |
) | |
(dropout): Dropout(p=0.1, inplace=False) | |
) | |
) | |
(Pdb) n | |
(Pdb) n | |
RuntimeError: mat1 dim 1 must match mat2 dim 0 | |
> /content/trans-vsumm/seq_sum.py(78)forward() | |
-> src = layer(src, src_mask) |
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