Python | Tensorflow abs() method
Tensorflow is an open-source machine learning library developed by Google. One of its applications is to develop deep neural networks.
The module
tensorflow.math
provides support for many basic mathematical operations. Function
tf.abs()
[alias
tf.math.abs
] provides support for the
absolute function in Tensorflow. It expects the input in form of complex numbers as
or floating point numbers. The input type is tensor and if the input contains more than one element, an element-wise absolute value is computed.
For a complex number
, the absolute value is computed as
.
For floating point numbers
, the absolute value is computed as
Syntax: tf.abs(x, name=None) or tf.math.abs(x, name=None)
Parameters:
x: A Tensor or SparseTensor of type float16, float32, float64, int32, int64, complex64 or complex128.
name (optional): The name for the operation.
Return type: A Tensor or SparseTensor with the same size and type as that of x with absolute values. For complex64 or complex128 input, the returned Tensor will be of type float32 or float64, respectively.
Code #1: For Floating point numbers
Python3
import tensorflow as tf
a = tf.constant([ - 0.5 , - 0.1 , 0 , 0.1 , 0.5 ], dtype = tf.float32)
b = tf. abs (a, name = 'abs' )
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:0", shape=(5, ), dtype=float32)
Input : [-0.5 -0.1 0. 0.1 0.5]
Return Type : Tensor("abs:0", shape=(5, ), dtype=float32)
Output : [0.5 0.1 0. 0.1 0.5]
Code #2: Visualization
Python3
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
a = np.linspace( - 5 , 5 , 11 )
b = tf. abs (a, name = 'abs' )
with tf.Session() as sess:
print ( 'Input:' , a)
print ( 'Output:' , sess.run(b))
plt.plot(a, sess.run(b), color = 'red' , marker = "o" )
plt.title( "tensorflow.abs" )
plt.xlabel( "X" )
plt.ylabel( "Y" )
plt.show()
|
Output:
Input: [-5. -4. -3. -2. -1. 0. 1. 2. 3. 4. 5.]
Output: [5. 4. 3. 2. 1. 0. 1. 2. 3. 4. 5.]
Code #3: For Complex Numbers
Python3
import tensorflow as tf
a = tf.constant([[ - 2.25 + 4.75j ], [ - 3.25 + 5.75j ]],
dtype = tf.complex64)
b = tf. abs (a, name = 'abs' )
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_1:0", shape=(2, 1), dtype=complex64)
Input : [[-2.25+4.75j] [-3.25+5.75j]]
Return Type : Tensor("abs_1:0", shape=(2, 1), dtype=float32)
Output : [[5.255949 ] [6.6049223]]
Last Updated :
07 Jan, 2022
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