TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning  neural networks.

Method Used:

• tf.pad: This method accepts input tensor and padding tensor with other optional arguments and returns a Tensor with added padding and same type as input Tensor. Padding tensor is a Tensor with shape(n, 2).

Example 1: This example uses constant padding mode i.e. value at all the padded indices will be constant.

## Python3

 `# importing the library ` `import` `tensorflow as tf ` ` `  `# Initializing the Input ` `input` `=` `tf.constant([[``1``, ``2``], [``3``, ``4``]]) ` `padding ``=` `tf.constant([[``2``, ``2``], [``2``, ``2``]]) ` ` `  `# Printing the Input ` `print``(``"Input: "``, ``input``) ` `print``(``"Padding: "``, padding) ` ` `  `# Generating padded Tensor ` `res ``=` `tf.pad(``input``, padding, mode ``=``'CONSTANT'``) ` ` `  `# Printing the resulting Tensors ` `print``(``"Res: "``, res )`

Output:

```Input:  tf.Tensor(
[[1 2]
[3 4]], shape=(2, 2), dtype=int32)
[[2 2]
[2 2]], shape=(2, 2), dtype=int32)
Res:  tf.Tensor(
[[0 0 0 0 0 0]
[0 0 0 0 0 0]
[0 0 1 2 0 0]
[0 0 3 4 0 0]
[0 0 0 0 0 0]
[0 0 0 0 0 0]], shape=(6, 6), dtype=int32)

```

Example 2: This example uses REFLECT padding mode. For this mode to work paddings[D, 0] and paddings[D, 1] must be less than or equal to tensor.dim_size(D) – 1.

## Python3

 `# importing the library ` `import` `tensorflow as tf ` ` `  `# Initializing the Input ` `input` `=` `tf.constant([[``1``, ``2``, ``5``], [``3``, ``4``, ``6``]]) ` `padding ``=` `tf.constant([[``1``, ``1``], [``2``, ``2``]]) ` ` `  `# Printing the Input ` `print``(``"Input: "``, ``input``) ` `print``(``"Padding: "``, padding) ` ` `  `# Generating padded Tensor ` `res ``=` `tf.pad(``input``, padding, mode ``=``'REFLECT'``) ` ` `  `# Printing the resulting Tensors ` `print``(``"Res: "``, res )`

Output:

```Input:  tf.Tensor(
[[1 2 5]
[3 4 6]], shape=(2, 3), dtype=int32)
[[1 1]
[2 2]], shape=(2, 2), dtype=int32)
Res:  tf.Tensor(
[[6 4 3 4 6 4 3]
[5 2 1 2 5 2 1]
[6 4 3 4 6 4 3]
[5 2 1 2 5 2 1]], shape=(4, 7), dtype=int32)

```

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.

My Personal Notes arrow_drop_up Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.

Article Tags :

Be the First to upvote.

Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.