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Use foo.new instead of torch.FloatTensor for GPU. #211

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Merged
chsasank merged 1 commit into from
Mar 29, 2018
Merged

Use foo.new instead of torch.FloatTensor for GPU. #211

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10 changes: 5 additions & 5 deletions advanced_source/numpy_extensions_tutorial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,12 +38,12 @@ class BadFFTFunction(Function):
def forward(self, input):
numpy_input = input.numpy()
result = abs(rfft2(numpy_input))
return torch.FloatTensor(result)
return input.new(result)

def backward(self, grad_output):
numpy_go = grad_output.numpy()
result = irfft2(numpy_go)
return torch.FloatTensor(result)
return grad_output.new(result)

# since this layer does not have any parameters, we can
# simply declare this as a function, rather than as an nn.Module class
Expand Down Expand Up @@ -90,7 +90,7 @@ class ScipyConv2dFunction(Function):
def forward(ctx, input, filter):
result = correlate2d(input.numpy(), filter.numpy(), mode='valid')
ctx.save_for_backward(input, filter)
return torch.FloatTensor(result)
return input.new(result)

@staticmethod
def backward(ctx, grad_output):
Expand All @@ -99,8 +99,8 @@ def backward(ctx, grad_output):
grad_input = convolve2d(grad_output.numpy(), filter.t().numpy(), mode='full')
grad_filter = convolve2d(input.numpy(), grad_output.numpy(), mode='valid')

return Variable(torch.FloatTensor(grad_input)), \
Variable(torch.FloatTensor(grad_filter))
return Variable(grad_output.new(grad_input)), \
Variable(grad_output.new(grad_filter))


class ScipyConv2d(Module):
Expand Down