# Python | Tensorflow cos () method

The `tensorflow.math ` module provides support for many basic mathematical operations. The ` tf.cos () ` [alias ` tf.math.cos `] function provides support for the cosine 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 element-wise cosine is calculated.

Syntax : tf.cos (x, name = None) or tf.math.cos ( 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 sin function and # saving the result to & # 39; b & # 39; b = tf.cos (a, name = ’cos’ )   # Initiated Tensorflow session host 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_2: 0", shape = (6,), dtype = float32) Input: [1. -0.5 3.4000001 -2.0999999 0. -6.5] Return type: Tensor ("cos: 0", shape = (6,), dtype = float32) Output: [0.54030228 0.87758255 -0.96679819 -0.50484604 1. 0.97658765] `

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.cos (a, name ` ` = ` ` ’cos’ ` `) `   ` # Initiating a Tensorflow session ` ` with tf.Session () as sess: ` ` print ` ` (` ` ’Inpu t: ’` `, a) ` ` ` ` print ` ` (` ` ’Output:’ ` `, sess.run (b)) ` ` plt.plot (a, sess.run (b), color ` ` = ` ` ’red’ ` `, marker ` ` = ` ` "o" ` `) ` ` plt.title (` ` "tensorflow.cos" ` `) ` ` 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: [0.28366219 -0.41384591 -0.90903414 -0.9598162 -0.5413659 0.1417459 0.75556135 1. 0.75556135 0.1417459 -0.5413659 -0.9598162 -0.90903414 -0.41384591 0.28366219 ] `

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