Python | Tensorflow tan () method

The tensorflow.math module provides support for many basic mathematical operations. The tf.tan () [alias tf.math.tan ] function provides support for the tangent function in Tensorflow. Input in radians is expected. Input type — tensor, and if the input contains more than one element, the element-wise tangent is calculated.

Syntax : tf.tan (x, name = None) or tf.math.tan ( x, name = None)

Parameters :
x : A tensor of any of the following types: float16, float32, float64, complex64, or complex128.
name (optional): The name for the operation.

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

Code # 1:

# Tensorflow library import

import tensorflow as tf

  
# Constant vector of size 6

a = tf.constant ([ 1.0 , - 0.5 , 3.4 , - 2.1 , 0.0 , - 6.5 ],

dtype = tf.float32)

  
# Applying the tan function and
# save the result to & # 39; b & # 39;

b = tf.tan (a, name = ` tan` )

  
# Initiating a Tensorflow session
with tf.Session () as sess:

print ( `Input type:` , a)

print ( `Input:` , sess.run (a))

print ( `Return type:` , b)

print ( `Output : ` , sess.run (b))

Output :

 Input type: T ensor ("Const: 0", shape = (6,), dtype = float32) Input: [1. -0.5 3.4 -2.1 0. -6.5] Return type: Tensor ("tan: 0", shape = (6, ), dtype = float32) Output: [1.5574077 -0.5463025 0.264317 1.7098469 0. -0.2202772] 

Code # 2: Rendering

# Tensorflow library import

import tensorflow as tf

 
# Import NumPy library

import numpy as np

 
# Import matplotlib.pylot function

import matplotlib. pyplot as plt

 
# Vector p size 15 with values ​​from -1 to 1

a = np.linspace ( - 1 , 1 , 15 )

 
# Applying the tangent function and
# save the result to & # 39; b & # 39;

b = tf.tan (a, name = `tan` )

 
# Initiate a session Tensorflow
with tf.Session () as sess:

print < code class = "plain"> ( `Input:` , a)

print ( `Output: ` , sess.run (b))

  plt.plot (a, sess.run (b), color = ` red` , marker = "o"

plt.title ( "tensorflow .tan "

  plt. xlabel ( "X"

plt.ylabel ( "Y"

 

  plt.show ()

Output :

 Input: [-1. -0.85714286 -0.71428571 -0.57142857 -0.42857143 -0.28571429 -0.14285714 0. 0.14285714 0.28571429 0.42857143 0.57142857 0.71428571 0.85714286 1.] Output: [-1.55740772 -1.15486601 -0.86700822 -0.64298589 -0.45689311 -0.29375136 -0.14383696 0. 0.14383696 0.29375136 0.45689311 0.64298589 0.86700822 1.15486601 1.55740772]