In PyTorch I have a 5D tensor `X`

of dimensions `B x 9 x C x H x W`

. I want to convert it into a 4D tensor `Y`

with dimensions `B x 9C x H x W`

such that concatenation happens channel wise.

To illustrate let,

a = X[1,0,:,:,:] b = X[1,1,:,:,:] c = X[1,2,:,:,:] ... i = X[1,8,:,:,:]

Then in the tensor `Y`

, `a to i`

should be channel wise concatenated.

You can easily broadcast to a new shape with `torch.reshape`

:

b, n, c, h, w = X.shape X = X.reshape(b, n*c, h, w)

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