# Python | PyTorch tan() method

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]
```

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