Python – Tensorflow bitwise.left_shift() method
Last Updated :
04 Jun, 2020
Tensorflow bitwise.left_shift()
method performs the left_shift operation on input a defined by input b and return the new constant. The operation is done on the representation of a and b.
This method belongs to bitwise module.
Syntax: tf.bitwise.left_shift( 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:
import tensorflow as tf
a = tf.constant( 8 , dtype = tf.int32)
b = tf.constant( 2 , dtype = tf.int32)
c = tf.bitwise.left_shift(a, b)
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_49:0", shape=(), dtype=int32)
8
Input 2 Tensor("Const_50:0", shape=(), dtype=int32)
2
Output: Tensor("LeftShift_1:0", shape=(), dtype=int32)
32
Example 2:
import tensorflow as tf
a = tf.constant([ 8 , 16 , 32 ], dtype = tf.int32)
b = tf.constant([ 2 , 2 , 3 ], dtype = tf.int32)
c = tf.bitwise.left_shift(a, b)
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_51:0", shape=(3, ), dtype=int32)
[ 8 16 32]
Input 2 Tensor("Const_52:0", shape=(3, ), dtype=int32)
[2 2 3]
Output: Tensor("LeftShift_2:0", shape=(3, ), dtype=int32)
[ 32 64 256]
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