PyTorch .positive()

The .positive() method in PyTorch returns a new tensor containing the same values as the input tensor. It implements the unary plus operation (+tensor), creating a copy of the tensor without modifying the values. This method is useful when an explicit copy or consistency with other unary operations in mathematical expressions is needed.

Syntax

torch.positive(input)

Parameters:

• input (Tensor): The input tensor.

Return value:

The .positive() method returns a new tensor with the same values and data type as the input tensor.

Example

This example demonstrates how to use the .positive() method to create a copy of a tensor:

import torch

# Define a tensor with positive and negative values
tensor = torch.tensor([[-3.5, 2.1], [0.0, -7.8]])

# Apply the positive operation
positive_tensor = torch.positive(tensor)

# Verify they contain the same values
print("Original Tensor:")
print(tensor)

print("\nPositive Tensor:")
print(positive_tensor)

# Check if they are the same object
print("\nAre they the same object?", tensor is positive_tensor)

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This example results in the following output:

Original Tensor:
tensor([[-3.5000,  2.1000],
        [ 0.0000, -7.8000]])

Positive Tensor:
tensor([[-3.5000,  2.1000],
        [ 0.0000, -7.8000]])

Are they the same object? False

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In this example:

• Value Preservation: All values remain unchanged, including negative numbers (-3.5 stays -3.5, -7.8 stays -7.8).
• New Tensor: The .positive() method creates a new tensor object, as confirmed by the is comparison returning False.
• Use Case: This operation is equivalent to the unary + operator and is primarily used for creating explicit copies or maintaining consistency in mathematical operations.