  # Python | PyTorch tan () method

NumPy | Python Methods and Functions

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] `