Python - Tensorflow bitwise.bitwise_and() method
Last Updated :
04 Jun, 2020
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:
Python3
# 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))
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:
Python3
# 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))
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]
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