PyTorch .tan()

The torch.tan() function returns the tangent of each element in the input tensor. It is part of PyTorch’s math operations used in deep learning and scientific computing.

Syntax

torch.tan(input, *, out=None) → Tensor

Parameters:

• input (Tensor): Input tensor with one or more elements in radians.
• out (Tensor, optional): Optional tensor to store the output.

Return value:

A tensor containing the tangent of each input element, with the same shape as the input tensor.

Example 1: Using torch.tan() with a 1D tensor

In this example, torch.tan() computes the tangent of a 1D tensor containing angles in radians:

import torch

# Create a tensor with values in radians
input_tensor = torch.tensor([0, torch.pi / 4, torch.pi / 6])

# Compute the tangent
output_tensor = torch.tan(input_tensor)

print(output_tensor)

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The output of this code is:

tensor([0.0000, 1.0000, 0.5774])

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Example 2: Applying torch.tan() with a 2D tensor

In this example, torch.tan() is applied to a 2D tensor of angles in radians:

import torch

# Create a 2x2 tensor with elements with values in radians
matrix = torch.tensor([[0, torch.pi / 4], [torch.pi, torch.pi / 6]])

# Compute the tangent
result = torch.tan(matrix)

print(result)

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The output of this code is:

tensor([[0.0000e+00, 1.0000e+00],
        [8.7423e-08, 5.7735e-01]])

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