Python – Tensorflow bitwise.bitwise_and() method
Tensorflow bitwise.bitwise_and()
method performs the bitwise_and operation and return those bits set, that are set(1) in both a and b. The operation is done on the representation of a and b.
This method belongs to bitwise module.
Syntax:
tf.bitwise.bitwise_and( a, b, name=None)
Arguments
- a: This must be a Tensor.It should be from the one of the following types: int8, int16, int32, int64, uint8, uint16, uint32, uint64.
- b: This should also be a Tensor, Type same as a.
- name: This is optional parameter and this is the name of the operation.
Return: It returns a Tensor having the same type as a and b.
Let’s see this concept with the help of few examples:
Example 1:
Example 1:
# Importing the Tensorflow library import tensorflow as tf # A constant a and b a = tf.constant( 4 , dtype = tf.int32) b = tf.constant( 6 , dtype = tf.int32) # Applying the bitwise_and() function # storing the result in 'c' c = tf.bitwise.bitwise_and(a, b) # Initiating a Tensorflow session with tf.Session() as sess: print ( "Input 1" , a) print (sess.run(a)) print ( "Input 2" , b) print (sess.run(b)) print ( "Output: " , c) print (sess.run(c)) |
Output:
Input 1 Tensor("Const_41:0", shape=(), dtype=int32) 4 Input 2 Tensor("Const_42:0", shape=(), dtype=int32) 6 Output: Tensor("BitwiseAnd_5:0", shape=(), dtype=int32) 4
Example 2:
# Importing the Tensorflow library import tensorflow as tf # A constant a and b a = tf.constant([ 1 , 2 , 7 ], dtype = tf.int32) b = tf.constant([ 1 , 5 , 8 ], dtype = tf.int32) # Applying the bitwise_and() function # storing the result in 'c' c = tf.bitwise.bitwise_and(a, b) # Initiating a Tensorflow session with tf.Session() as sess: print ( "Input 1" , a) print (sess.run(a)) print ( "Input 2" , b) print (sess.run(b)) print ( "Output: " , c) print (sess.run(c)) |
Output:
Input 1 Tensor("Const_43:0", shape=(3, ), dtype=int32) [1 2 7] Input 2 Tensor("Const_44:0", shape=(3, ), dtype=int32) [1 5 8] Output: Tensor("BitwiseAnd_6:0", shape=(3, ), dtype=int32) [1 0 0]