.where()

In PyTorch, the .where function returns a new tensor with elements chosen based on a condition, selecting values from one source when the condition is met and from another when it is not.

Syntax

torch.where(condition, input, other) → Tensor

• condition: The boolean tensor that controls selection.
• input: The tensor to select elements from when the condition is True.
• other: The tensor to select elements from when the condition is False.

It returns a tensor of elements selected from either input or other, based on the condition.

Example

The following example demonstrates the usage of the .where() function:

import torch

# Define tensors
condition = torch.tensor([[True, False], [False, True]])
x = torch.tensor([[1, 2], [3, 4]])
y = torch.tensor([[9, 8], [7, 6]])

# Select elements based on the condition
res = torch.where(condition, x, y)

# Print the result
print(res)

The above code produces the following output:

tensor([[1, 8],
        [7, 4]])

In this example, the .where() function selects elements from the x tensor where the condition tensor is True and from the y tensor where the condition tensor is False. The resulting tensor is created by selecting elements from x or y based on the condition tensor.

The .where() function is particularly useful in conditional operations where element-wise selection between tensors is required.