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fix pad_packed_sequence method input requires_grad==True #8574

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merged 6 commits into from
Jul 6, 2022
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Merged

fix pad_packed_sequence method input requires_grad==True #8574

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ab59a60
fix pad_packed_sequence method input requires_grad==True
Ldpe2G Jul 5, 2022
0f2453e
Merge branch 'master' into dev_fix_pad_packed_sequence_input_needs_grad
Ldpe2G Jul 5, 2022
00d20cf
fix append error when batch_first=True
Ldpe2G Jul 6, 2022
0a7a83b
Merge branch 'dev_fix_pad_packed_sequence_input_needs_grad' of https:…
Ldpe2G Jul 6, 2022
5ea980d
Merge branch 'master' into dev_fix_pad_packed_sequence_input_needs_grad
Ldpe2G Jul 6, 2022
935c6de
Merge branch 'master' into dev_fix_pad_packed_sequence_input_needs_grad
mergify[bot] Jul 6, 2022
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3 changes: 2 additions & 1 deletion python/oneflow/nn/utils/rnn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -362,6 +362,7 @@ def pad_packed_sequence(
device=sequence.data.device,
requires_grad=sequence.data.requires_grad,
)
padded_output = padded_output.clone()
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对了，我昨天突然想到这里不应该这么写，应该先判断一下 requires_grad 再 clone，否则的话在 requires_grad 为 False 时，会有一次多余的 memcpy 操作，有计算的浪费

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好的，我再改下


# This will be modified at every iteration, but we reserve memory for it now.
tmp_view_size = output_size # == [-1, -1, *sequence.data.size()[1:]]
Expand Down Expand Up @@ -390,7 +391,7 @@ def pad_packed_sequence(
prev_batch_size = batch_size

if batch_first:
permute_dims = (1, 0)
permute_dims = [1, 0]
for i in range(2, padded_output.ndim):
permute_dims.append(i)
padded_output = padded_output.permute(permute_dims)
Expand Down
8 changes: 8 additions & 0 deletions python/oneflow/test/expensive/test_rnn_utils.py
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Expand Up @@ -42,9 +42,11 @@ def _test_rnn_utils_pack_padded_sequence(test_case, device):
padded_inputs[0 : lengths[i], i : i + 1, :] = i + 1

inputs = flow.from_numpy(padded_inputs).to(device)
inputs.requires_grad = True
flow_res = flow_rnn_utils.pack_padded_sequence(inputs, lengths)

torch_inputs = torch.from_numpy(padded_inputs).to(device)
torch_inputs.requires_grad = True
torch_res = torch_rnn_utils.pack_padded_sequence(torch_inputs, lengths)

test_case.assertTrue(
Expand All @@ -70,6 +72,9 @@ def _test_rnn_utils_pack_padded_sequence(test_case, device):
flow_res, batch_first=False
)

torch_seq_unpacked.sum().backward()
flow_seq_unpacked.sum().backward()

test_case.assertTrue(
np.allclose(
torch_seq_unpacked.cpu().detach().numpy(),
Expand All @@ -85,6 +90,9 @@ def _test_rnn_utils_pack_padded_sequence(test_case, device):
atol=1e-8,
)
)
test_case.assertTrue(
np.allclose(inputs.grad.cpu().numpy(), torch_inputs.grad.cpu().numpy())
)


def _test_rnn_utils_pad_sequence(test_case, device):
Expand Down