Error on transpose and view

import torch
import torch.nn.functional as F
def softmax(input, axis=1):
    Apply softmax on input at certain axis.
    input: Tensor (N*L or rank>2)
    axis: the axis to apply softmax
    Returns: Tensor with softmax applied on that dimension.
    input_size = input.size()
    trans_input = input.transpose(axis, len(input_size)-1)
    trans_size = trans_input.size()

    input_2d = trans_input.view(-1, trans_size[-1])
    soft_max_2d = F.softmax(input_2d)
    soft_max_nd = soft_max_2d.view(*trans_size)
    return soft_max_nd.transpose(axis, len(input_size)-1)

aa= torch.randn(3,4,4)
print aa

soft_1 = softmax(aa, axis = 1)
print soft_1

gives the following error:

File "/local/anaconda2/lib/python2.7/site-packages/torch/", line 214, in view
    raise ValueError("input should be contiguous")
ValueError: input should be contiguous

You can try this:

input_2d = trans_input.contiguous().view(-1, trans_size[-1])

Transpose followed by view will fail, because view requires the tensor to be contiguous. @longcw’s code should do it.