The tensorflow.math module provides support for many basic mathematical operations. The tf.sin () [alias tf.math.sin ] function provides support for the sine function in Tensorflow. It expects input in radians, and output is in the range [-1, 1]. Input type — tensor, and if the input contains more than one element, the elementwise sine is calculated.

Syntax : tf.sin (x, name = None) or tf.math.sin ( 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)   # Apply the sin function and # save the result to & # 39; b & # 39; b = tf.sin (a, name = `sin` )    # Initiation 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))

Exit:

 Input type: Tensor ("Const_1: 0", shape = (6,), dtype = float32) Input: [1. -0.5 3.4000001 -2 .0999999 0. -6.5] Return type: Tensor ("sin_0: 0", shape = (6,), dtype = float32) Output: [0.84147096 -0.47942555 -0.25554121 -0.86320943 0. -0.21511999] 

Code # 2: Rendering

# Import Tensorflow library import tensorflow as tf   # Importing the NumPy library import numpy as np   # Import matplotlib.pylot function import matplotlib.pyplot as plt   # Vector size 15 with values ​​from -5 to 5 a = np.linspace ( - 5 , 5 , 15 )   # Using the sigmoid function and # saving the result to & # 39; b & # 39; b = tf.sin (a, name = `sin` )   # Initiating a Tensorflow session with tf.Session () as sess: print ( `In put: ` , a)   print ( `Output:` , sess.run (b)) plt.plot (a, sess.run (b), color = `red` , marker = "o" )  plt.title ( "tensorflow.sin" )  plt.xlabel ( "X" )  plt.ylabel ( "Y" )       plt.show ()

Exit:

 Input: [-5. -4.28571429 -3.57142857 -2.85714286 -2.14285714 -1.42857143 -0.71428571 0. 0.71428571 1.42857143 2.14285714 2.85714286 3.57142857 4.28571429 5.] Output: [0.95892427 0.91034694 0.41672165 -0.2806294 -0.84078711 -0.98990308 -0.6550779 0. 0.6550779 0.98990308 0.84078711 0.2806294 -0.41672165 -0.91034694 -0.95892427]