8000 Failed when RNN run with cudnn with `requires_grad` set to `False` · Issue #776 · pytorch/pytorch · GitHub
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Failed when RNN run with cudnn with requires_grad set to False #776

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meijieru opened this issue Feb 18, 2017 · 0 comm 8000 ents
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Failed when RNN run with cudnn with requires_grad set to False #776

meijieru opened this issue Feb 18, 2017 · 0 comments
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meijieru commented Feb 18, 2017 •
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import torch
import torch.nn as nn
from torch.autograd import Variable

lstm = nn.LSTM(2, 3, 1, bidirectional=True)
lstm.cuda()
for param in lstm.parameters():
    param.requires_grad = False  # NOTE: Failed when 'False' but succeed when 'True'

input = torch.ones(4, 5, 2)  # [T, b, i]
input = input.cuda()
input = Variable(input, requires_grad=True)
output, _ = lstm(input)
output.backward(torch.ones(output.size()).cuda())

When run on cpu or requires_grad set to True, it does succeed.
Otherwise, it fails with error message:

Traceback (most recent call last):
  File "test_lstm.py", line 17, in <module>
    output.backward(torch.ones(output.size()).cuda())
  File "/home/jrmei/.local/lib/python2.7/site-packages/torch/autograd/variable.py", line 158, in backward
    self._execution_engine.run_backward((self,), (gradient,), retain_variables)
RuntimeError: CudnnRNN returned an invalid number of gradient tensors (expected 11, but got 4)

It seems like the check done by the framework has a bug.
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