Pytorch reshape tensor dimension

Question

For example, I have 1D vector with dimension (5). I would like to reshape it into 2D matrix (1,5).

Here is how I do it with numpy

>>> import num         


        

Answer 1

This question has been thoroughly answered already, but I want to add for the less experienced python developers that you might find the * operator helpful in conjunction with view().

For example if you have a particular tensor size that you want a different tensor of data to conform to, you might try:

img = Variable(tensor.randn(20,30,3)) # tensor with goal shape
flat_size = 20*30*3
X = Variable(tensor.randn(50, flat_size)) # data tensor

X = X.view(-1, *img.size()) # sweet maneuver
print(X.size()) # size is (50, 20, 30, 3)

This works with numpy shape too:

img = np.random.randn(20,30,3)
flat_size = 20*30*3
X = Variable(tensor.randn(50, flat_size))
X = X.view(-1, *img.shape)
print(X.size()) # size is (50, 20, 30, 3)