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How to compute the inverse hyperbolic sine in PyTorch?

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  • Last Updated : 27 Jun, 2022

In this article, we are going to discuss how to compute the inverse hyperbolic sine in PyTorch. 

torch.asinh() method:

The torch.asinh() method is used to compute the inverse hyperbolic sine of each element present in a given input tensor. This method accepts both real and complex-valued as input. It supports input tensors of any dimension. This method returns a tensor after computing the inverse hyperbolic sine of each element in a given input tensor. before moving further let’s see the syntax of this method.

Syntax: torch.asinh(input, *, out=None)

Parameters:

  • input: This is our input tensor.
  • out (optional) – This is our output tensor. 

Return: This method returns a tensor after computing the inverse hyperbolic sine of each element in a given input tensor.

Example 1:

In this example, we are computing the inverse hyperbolic sine for the real-valued 1D tensor.

Python3




# Import required library
import torch
  
# creating a input tensor
tens = torch.tensor([3., 1.3, 2., 2.3, -2.3])
  
# print the input tensor
print(" Input Tensor - ", tens)
  
# compute the inverse hyperbolic sine 
# of input tensor
tens_inv_hsin = torch.asinh(tens)
  
# print the above computed tensor
print(" Computed Inverse Hyperbolic Sine Tensor - "
      tens_inv_hsin)


Output:

 

Example 2:

In this example, we are computing the inverse hyperbolic sine for the complex-valued 1D tensor.

Python3




# Import required library
import torch
  
# creating a input tensor
tens = torch.tensor([2.1+3j, 2.+2.j, 4.+2.j, 2.4+2.j])
  
# print the input tensor
print(" Input Tensor - ", tens)
  
# compute the inverse hyperbolic sine 
# of input tensor
tens_inv_hsin = torch.asinh(tens)
  
# print the above computed tensor
print(" Computed Inverse Hyperbolic Sine - ",
      tens_inv_hsin)


Output:

 

Example 3:

In this example, we are computing the inverse hyperbolic sine for the real-valued 2D tensor.

Python3




# Import required library
import torch
  
# define a 2D input tensor
tens = torch.tensor([[1., 2.3, 1.3],
                     [2.1, 3., -2.3],
                     [3.2, 5.2, 2.3]])
  
# print the input tensor
print("\n Input Tensor: \n", tens)
  
# compute the inverse hyperbolic sine of 
# input tensor
tens_inv_hsin = torch.asinh(tens)
  
# print the above computed tensor
print("\n Computed Inverse Hyperbolic Sine: \n "
      tens_inv_hsin)


Output:

 

Example 4:

In this example, we are computing the inverse hyperbolic sine for the complex-valued 2D tensor.

Python3




# Import required library
import torch
  
# define a 2D input tensor
tens = torch.tensor([[2.1+3j, 2.+3.j, 3.1-3.5j],
                     [1.3+2j, 2.3-2.3j, 4.+3.j],
                     [3.2+5j, 6.+3.j, 4.2-3.2j]])
  
# print the input tensor
print("\n Input Tensor: \n", tens)
  
# compute the inverse hyperbolic sine
# of input tensor
tens_inv_hsin = torch.asinh(tens)
  
# print the above computed tensor
print("\n Computed Inverse Hyperbolic Sine: \n "
      tens_inv_hsin)


Output:

 


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