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# torch.reshape

torch.reshape(input, shape) → Tensor

  Returns a tensor with the same data and number of elements as `input`, but with the specified shape. When possible, the returned tensor will be a view of `input`. Otherwise, it will be a copy. Contiguous inputs and inputs with compatible strides can be reshaped without copying, but you should not depend on the copying vs. viewing behavior.

  See `torch.Tensor.view()` on when it is possible to return a view.

  A single dimension may be -1, in which case it’s inferred from the remaining dimensions and the number of elements in `input`.

  Parameters:

    - input (Tensor) – the tensor to be reshaped

    - shape (tuple of python:int) – the new shape

  Example:

      >>> a = torch.arange(4.)
      >>> torch.reshape(a, (2, 2))
      tensor([[ 0.,  1.],
              [ 2.,  3.]])
      >>> b = torch.tensor([[0, 1], [2, 3]])
      >>> torch.reshape(b, (-1,))
      tensor([ 0,  1,  2,  3])

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