# Python | PyTorch tan() method

• Last Updated : 05 Jan, 2022

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.tan()` provides support for the tangent function in PyTorch. It expects the input in radian form and the output is in the range [-∞, ∞]. The input type is tensor and if the input contains more than one element, element-wise tangent is computed.

Syntax: torch.tan(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:

## Python3

 `# Importing the PyTorch library``import` `torch`` ` `# A constant tensor of size 6``a ``=` `torch.FloatTensor([``1.0``, ``-``0.5``, ``3.4``, ``-``2.1``, ``0.0``, ``-``6.5``])``print``(a)`` ` `# Applying the tan function and``# storing the result in 'b'``b ``=` `torch.tan(a)``print``(b)`

Output:

``` 1.0000
-0.5000
3.4000
-2.1000
0.0000
-6.5000
[torch.FloatTensor of size 6]

1.5574
-0.5463
0.2643
1.7098
0.0000
-0.2203
[torch.FloatTensor of size 6]
```

Code #2: Visualization

## Python3

 `# Importing the PyTorch library``import` `torch`` ` `# Importing the NumPy library``import` `numpy as np`` ` `# Importing the matplotlib.pyplot 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 tangent function and``# storing the result in 'b'``b ``=` `torch.tan(torch.FloatTensor(a))`` ` `print``(b)`` ` `# Plotting``plt.plot(a, b.numpy(), color ``=` `'red'``, marker ``=` `"o"``) ``plt.title(``"torch.tan"``) ``plt.xlabel(``"X"``) ``plt.ylabel(``"Y"``) `` ` `plt.show()`

Output:

```-1.5574
-1.1549
-0.8670
-0.6430
-0.4569
-0.2938
-0.1438
0.0000
0.1438
0.2938
0.4569
0.6430
0.8670
1.1549
1.5574
[torch.FloatTensor of size 15]
``` My Personal Notes arrow_drop_up