Related Articles
Python | PyTorch asin() method
• Last Updated : 06 Jan, 2019

PyTorch is an open-source machine learning library developed by Facebook. It is used for deep neural network and natural language processing purposes.

The function `torch.asin()` provides support for the inverse sine function in PyTorch. It expects the input to be in the range [-1, 1] and gives the output in radian form. It returns nan if the input does not lie in the range [-1, 1]. The input type is tensor and if the input contains more than one element, element-wise inverse sine is computed.

Syntax: torch.asin(x, out=None)

Parameters:
x: Input tensor
name (optional): Output tensor

Return type: A tensor with the same type as that of x.

Code #1:

 `# Importing the PyTorch library``import` `torch`` ` `# A constant tensor of size 6``a ``=` `torch.FloatTensor([``1.0``, ``-``0.5``, ``3.4``, ``0.2``, ``0.0``, ``-``2``])``print``(a)`` ` `# Applying the inverse sin function and``# storing the result in 'b'``b ``=` `torch.asin(a)``print``(b)`

Output:

```tensor([ 1.0000, -0.5000,  3.4000,  0.2000,  0.0000, -2.0000])
tensor([ 1.5708, -0.5236,     nan,  0.2014,  0.0000,     nan])
```

Code #2: Visualization

 `# Importing the PyTorch library``import` `torch`` ` `# Importing the NumPy library``import` `numpy as np`` ` `# Importing the matplotlib.pylot function``import` `matplotlib.pyplot as plt`` ` `# A vector of size 15 with values from -1 to 1``a ``=` `np.linspace(``-``1``, ``1``, ``15``)`` ` `# Applying the inverse sine function and``# storing the result in 'b'``b ``=` `torch.asin(torch.FloatTensor(a))`` ` `print``(b)`` ` `# Plotting``plt.plot(a, b.numpy(), color ``=` `'red'``, marker ``=` `"o"``) ``plt.title(``"torch.asin"``) ``plt.xlabel(``"X"``) ``plt.ylabel(``"Y"``) `` ` `plt.show()`

Output:

```tensor([-1.5708, -1.0297, -0.7956, -0.6082, -0.4429, -0.2898, -0.1433,  0.0000,
0.1433,  0.2898,  0.4429,  0.6082,  0.7956,  1.0297,  1.5708])
``` Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

My Personal Notes arrow_drop_up