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torch7: How to flatten a Tensor?

I want to flatten any general n-dimensional torch.Tensor but in a way which is computationally optimized. (By "flatten" here, I mean converting a given Tensor to a one-dimensional Tensor which has the same number of elements as the given vector.) I am using the following steps currently to do so:

local original_tensor = -- output of some intermediate layer of a conv-net residing in the GPU
local shaping_tensor = torch.Tensor(original_tensor:nElement())
original_tensor = original_tensor:resizeAs(shaping_tensor:cuda())

I believe it is slightly inefficient because of :cuda() which pushes this new Tensor from memory to the GPU. Can someone please suggest a more efficient way to do this?

Thanks in advance.

Solution

  • Typical approach is to create a view (thus not actually reshaping the tensor).

    x:view(x:nElement())

    which comes directly from official "torch for numpy users" https://github.com/torch/torch7/wiki/Torch-for-Numpy-users