How to Compute the Inverse Cosine and Inverse Hyperbolic Cosine in PyTorch
Last Updated :
02 Jun, 2022
In this article, we will see how to compute the inverse Cosine and Inverse Hyperbolic Cosine in Pytorch.
torch.acos() is used to find the inverse cosine of elements in a given tensor. We can apply this function on real as well as complex tensors.
Syntax: torch.acos(input_tensor)
Parameter:
It will take a tensor which can be real or complex.
Return:
inverse cosine values in a tensor
Example 1:
In this example, we will create a 3D tensor with three rows and three columns and return the inverse cosine values.
Python3
import torch
t1 = torch.tensor([[ 1 , 2 , 3 ],
[ 5 , 6 , 7 ],
[ 9 , 10 , 11 ]])
print (t1)
print (torch.acos(t1))
|
Output:
tensor([[ 1, 2, 3],
[ 5, 6, 7],
[ 9, 10, 11]])
tensor([[0., nan, nan],
[nan, nan, nan],
[nan, nan, nan]])
Example 2:
In this example, we will create a 1D complex tensor with real and imaginary parts with float type and return the inverse cosine values.
Python3
import torch
real = torch.tensor([ 78.2 , 23.2 ], dtype = torch.float32)
img = torch.tensor([ 32 , 41 ], dtype = torch.float32)
t1 = torch. complex (real, img)
print (t1)
print (torch.acos(t1))
|
Output:
tensor([78.2000+32.j, 23.2000+41.j])
tensor([0.3884-5.1298j, 1.0560-4.5457j])
torch.acosh() is used to find the inverse hyperbolic cosine of elements in a given tensor. We can apply this function on real as well as a complex tensor.
Syntax: torch.acosh(input_tensor)
Parameter:
It will take a tensor which can be real or complex.
Return:
inverse hyperbolic cosine values in a tensor
In this example, we will create a 3D tensor with three rows and three columns and return the inverse hyperbolic cosine values.
Python3
import torch
t1 = torch.tensor([[ 1 , 2 , 3 ],
[ 5 , 6 , 7 ],
[ 9 , 10 , 11 ]])
print (t1)
print (torch.acosh(t1))
|
Output:
tensor([[ 1, 2, 3],
[ 5, 6, 7],
[ 9, 10, 11]])
tensor([[0.0000, 1.3170, 1.7627],
[2.2924, 2.4779, 2.6339],
[2.8873, 2.9932, 3.0890]])
Example 2:
In this example, we will create a 1D complex tensor with real and imaginary parts with float type and return the inverse hyperbolic cosine values.
Python3
import torch
real = torch.tensor([ 78.2 , 23.2 ], dtype = torch.float32)
img = torch.tensor([ 32 , 41 ], dtype = torch.float32)
t1 = torch. complex (real, img)
print (t1)
print (torch.acosh(t1))
|
Output:
tensor([78.2000+32.j, 23.2000+41.j])
tensor([5.1298+0.3884j, 4.5457+1.0560j])
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