Torch View - Python

Torch View is a PyTorch function that returns a tensor with the same data as the input tensor but with a different size or shape. It is a powerful tool that allows us to manipulate tensors and create new tensors with different sizes and shapes, without changing the data stored in the original tensor.

Syntax

torch.view(input, shape)

The function takes two arguments:

• input: the input tensor that we want to reshape.
• shape: the new shape that we want to apply to the input tensor.

Example

import torch

# create a 2D tensor with shape (3, 4)
x = torch.randn(3, 4)
print(x)

# reshape the tensor to have shape (2, 6)
y = torch.view(x, (2, 6))
print(y)

Output:

tensor([[ 0.1254,  1.0163, -1.5829,  0.1746],
        [ 0.7520, -0.1972, -1.4101,  0.7017],
        [-0.4865, -1.0701,  0.3225, -0.1152]])
tensor([[ 0.1254,  1.0163, -1.5829,  0.1746,  0.7520, -0.1972],
        [-1.4101,  0.7017, -0.4865, -1.0701,  0.3225, -0.1152]])

In this example, we create a 2D tensor x with shape (3, 4). We then use torch.view to reshape the tensor to have shape (2, 6). The resulting tensor y has the same data as x, but with a different shape.

Conclusion

Torch View is a powerful PyTorch function that allows us to manipulate tensors and create new tensors with different sizes and shapes, without changing the data stored in the original tensor. It is a useful tool for deep learning engineers who work with tensors on a regular basis.