Python | Tensorflow logical_not() 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 logical operations. Function tf.logical_not() [alias tf.math.logical_not or tf.Tensor.__invert__] provides support for the logical NOT function in Tensorflow. It expects the input of bool type. The input type is tensor and if the input contains more than one element, an element-wise logical NOT is computed, $ NOT x $ .

Syntax: tf.logical_not(x, name=None) or tf.math.logical_not(x, name=None) or tf.Tensor.__invert__(x, name=None) Parameters: x: A Tensor of type bool. name (optional): The name for the operation. Return type: A Tensor of bool type with the same size as that of x.

Code: Python3

# Importing the Tensorflow library
import tensorflow as tf

# A constant vector of size 4
a = tf.constant([True, False, False, True], dtype = tf.bool)

# Applying the NOT function and
# storing the result in 'b'
b = tf.logical_not(a, name ='logical_not')

# Initiating a Tensorflow session
with tf.Session() as sess:
    print('Input type:', a)
    print('Input a:', sess.run(a))
    print('Return type:', b)
    print('Output:', sess.run(b))

Output:

Input type: Tensor("Const:0", shape=(4, ), dtype=bool)
Input: [ True False False True]
Return type: Tensor("logical_and:0", shape=(4, ), dtype=bool)
Output: [ False True True False]