Tensorflow Python3 Python3
bitwise.bitwise_or() method performs the bitwise_or operation and return those bits set, that are either set(1) in a or in b or in both. The operation is done on the representation of a and b.
This method belongs to bitwise module.
Syntax:Let's see this concept with the help of few examples: Example 1:tf.bitwise.bitwise_or( a, b, name=None)ArgumentsReturn: It returns a Tensor having the same type as a and b.
- 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.
# Importing the Tensorflow library
import tensorflow as tf
# A constant a and b
a = tf.constant(43, dtype = tf.int32)
b = tf.constant(5, dtype = tf.int32)
# Applying the bitwise_or function
# storing the result in 'c'
c = tf.bitwise.bitwise_or(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_22:0", shape=(), dtype=int32)
43
Input 2 Tensor("Const_23:0", shape=(), dtype=int32)
5
Output: Tensor("BitwiseOr_1:0", shape=(), dtype=int32)
47
Example 2:
# Importing the Tensorflow library
import tensorflow as tf
# A constant vector of size 2
a = tf.constant([1, 6], dtype = tf.int32)
b = tf.constant([2, 5], dtype = tf.int32)
# Applying the bitwise_or function
# storing the result in 'c'
c = tf.bitwise.bitwise_or(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_20:0", shape=(2, ), dtype=int32)
[1 6]
Input 2 Tensor("Const_21:0", shape=(2, ), dtype=int32)
[2 5]
Output: Tensor("BitwiseOr:0", shape=(2, ), dtype=int32)
[3 7]