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# 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:

 `# 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]
```

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