The torch.tan () function provides support for the torch function in PyTorch. It expects input in radians, and output is in the range [-∞, ∞]. Input type — tensor, and if the input contains more than one element, the element-wise tangent is calculated.

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:

Exit :

 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: Rendering

# PyTorch library import import torch   # Constant tensor of size 6 a = torch.FloatTensor ([ 1.0 , - 0.5 , 3.4 , - 2.1 , 0.0 , - 6.5 ]) print (a)   # Apply the tanning function and # save the result to & # 39; b & # 39; b = torch.tan (a) print (b)

# Import PyTorch library import torch   # Import NumPy library import numpy as np   # Import matplotlib.pylot function import matplotlib.pyplot as plt   # Vector size 15 with values ​​from -1 to 1 a = np.linspace ( - 1  , 1 , 15 )    # Applying a tangent function and # save the result to & # 39; b & # 39; b = torch.tan (torch.FloatTensor (a))   print (b)   # Plot 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]