 # 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 ] `