How to compute the inverse hyperbolic sine in PyTorch?
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:
