PyTorch .reciprocal()

The .reciprocal() method performs an element-wise operation that returns the multiplicative inverse of every element in the tensor. For any element x, the result is 1/x. This method works with tensors that have floating-point or complex data types (such as torch.float32, torch.float64, or torch.complex64). If an element equals zero, the reciprocal for that position becomes infinity (inf).

Syntax

torch.reciprocal(input, *, out=None)

Parameters:

• input (Tensor): The input tensor whose elements will be inverted.
• out (Tensor, optional): The output tensor to store the result. Must have the same shape as input.

Return value:

Returns a tensor containing the element-wise reciprocals of input.

Example 1: Compute element-wise reciprocals

In this example, we create a tensor of floating-point numbers and calculate their reciprocals using torch.reciprocal():

import torch

# Create a tensor of floating-point values
x = torch.tensor([2.0, 4.0, 0.5, 0.0])

print("Original Tensor:")
print(x)

# Compute the reciprocal
result = torch.reciprocal(x)

print("\nReciprocal Tensor:")
print(result)
# Note: Division by zero results in 'inf'

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The output of this code is:

Original Tensor:
tensor([2.0000, 4.0000, 0.5000, 0.0000])

Reciprocal Tensor:
tensor([0.5000, 0.2500, 2.0000,    inf])

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Example 2: Using the out parameter

In this example, the result is stored in a pre-allocated output tensor using the out parameter:

import torch

# Input tensor
x = torch.tensor([1.0, 2.0, 0.25])

# Create an empty tensor with the same shape
out_tensor = torch.empty_like(x)

# Store the result in 'out_tensor'
torch.reciprocal(x, out=out_tensor)

print("Input Tensor:")
print(x)

print("\nReciprocal stored in 'out' tensor:")
print(out_tensor)

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The output of this code is:

Input Tensor:
tensor([1.0000, 2.0000, 0.2500])

Reciprocal stored in 'out' tensor:
tensor([1.0000, 0.5000, 4.0000])

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