Python | Tensorflow atan () method

NumPy | Python Methods and Functions

The tensorflow.math module provides support for many basic mathematical operations. The tf.atan () [alias tf.math.atan ] function provides support for the inverse tangent function in Tensorflow. This gives the output in radians. Input type — tensor, and if the input contains more than one element, the inverse tangent is calculated for each element.

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

Parameters :
x : A tensor of any of the following types: bfloat16, half , float32, float64, int32, int64, 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 , 0.2 , 0.0 , - 2 ],

dtype = tf.float32)

 
# Using the atan function and
# save the result to & # 39; b & # 39;

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

< code class = "undefined spaces">  
# 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: Tensor ("Const_8: 0", shape = (6,), dtype = float32) Input: [1. -0.5 3.4 0.2 0. -2. ] Return type: Tensor ("atan: 0", shape = (6,), dtype = float32) Output: [0.7853982 -0.4636476 1.2847449 0.19739556 0. -1.1071488] 

Code # 2: Rendering

# Import Tensorflow library

import tensorflow as tf

 
# Import 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 )

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

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

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

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

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

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

plt.title ( " tensorflow.atan "

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: [-1.37340077 -1.34156439 -1.29778762 -1.23412151 -1.13416917 -0.96007036 -0.62024949 0. 0.62024949 0.96007036 1.13416917 1.23412151 1.29778762 1.34156439 1.37340077] 





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