How to reshape a torch tensor

This recipe helps you reshape a torch tensor

Recipe Objective

How to reshape a torch tensor?

This is possible by using the torch.reshape(input data, shape) function, which will returns a tensor having the same data and the number of elements as the input, but with a specified shape that we have defined. When possible the tensor which is returned will be the view of input, else it will be a copy. The neighboring inputs and the inputs with compatible strides which can be reshaped without copying but we should not be dependent on the copying vs the viewing behaviour. Let's understand it practically how to reshape a torch tensor.

Build Your First Text Classification Model using PyTorch

Step 1 - Import library

import torch

Step 2 - Take Sample data

data = torch.tensor([[1,2,3,4],[5,6,7,8]])
print("This is the Sample data:","\n",data, data.shape)

This is the Sample data: 
 tensor([[1, 2, 3, 4],
        [5, 6, 7, 8]]) torch.Size([2, 4])

Step 3 - Reshape the data

reshape = torch.reshape(data, (4,2))
print("This is the reshaped tensor:", "\n",reshape, reshape.shape)

This is the reshaped tensor: 
 tensor([[1, 2],
        [3, 4],
        [5, 6],
        [7, 8]]) torch.Size([4, 2])

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