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``` #include <array_ops.h> ```

## Summary

This operation pads a ``` input ``` with zeros according to the ``` paddings ``` you specify. ``` paddings ``` is an integer tensor with shape ``` [Dn, 2] ``` , where n is the rank of ``` input ``` . For each dimension D of ``` input ``` , ``` paddings[D, 0] ``` indicates how many zeros to add before the contents of ``` input ``` in that dimension, and ``` paddings[D, 1] ``` indicates how many zeros to add after the contents of ``` input ``` in that dimension.

The padded size of each dimension D of the output is:

``` paddings(D, 0) + input.dim_size(D) + paddings(D, 1) ```

For example:

```# 't' is [[1, 1], [2, 2]]
# 'paddings' is [[1, 1], [2, 2]]
# rank of 't' is 2
[0, 0, 1, 1, 0, 0]
[0, 0, 2, 2, 0, 0]
[0, 0, 0, 0, 0, 0]]
```

Args:

Returns:

• ``` Output ``` : The output tensor.

### Constructors and Destructors

``` Pad (const :: tensorflow::Scope & scope, :: tensorflow::Input input, :: tensorflow::Input paddings) ```

### Public attributes

``` operation ```
``` Operation ```
``` output ```
``` :: tensorflow::Output ```

### Public functions

``` node () const ```
``` ::tensorflow::Node * ```
``` operator::tensorflow::Input () const ```
``` ```
``` operator::tensorflow::Output () const ```
``` ```

## Public attributes

### operation

`Operation operation`

### output

`::tensorflow::Output output`

## Public functions

``` Pad(
const ::tensorflow::Scope & scope,
::tensorflow::Input input,
)```

### node

`::tensorflow::Node * node() const `

### operator::tensorflow::Input

` operator::tensorflow::Input() const `

### operator::tensorflow::Output

` operator::tensorflow::Output() const `
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