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, 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:
# 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))
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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]
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