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]