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Python – Tensorflow bitwise.left_shift() method

Last Updated : 04 Jun, 2020
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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 constant a and b
a = tf.constant(8, dtype = tf.int32)
b = tf.constant(2, dtype = tf.int32)  
  
# Applying the left_shift() function 
# storing the result in 'c' 
c = tf.bitwise.left_shift(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_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 constant a and b 


a = tf.constant([8, 16, 32], dtype = tf.int32) 


b = tf.constant([2, 2, 3], dtype = tf.int32)   


  


# Applying the left_shift() function  


# storing the result in 'c'  


c = tf.bitwise.left_shift(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_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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                                                    PranchalKatiyar                                                

                                                

                                                

            
                                            

                                            
                                        

                                        

                                            
                                            

                                                
                                                
                                            

                                            
                                                                            

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