# tf.raw_ops.PadV2

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Pads a tensor.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.PadV2`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/PadV2)

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    tf.raw_ops.PadV2(
        input, paddings, constant_values, name=None
    )

This operation pads `input` according to the `paddings` and `constant_values`
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 padding values to add before the contents of `input` in that dimension,
and `paddings[D, 1]` indicates how many padding values to add after the contents
of `input` in that dimension. `constant_values` is a scalar tensor of the same
type as `input` that indicates the value to use for padding `input`.

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]]
    # 'constant_values' is 0
    # rank of 't' is 2
    pad(t, paddings) ==> [[0, 0, 0, 0, 0, 0]
                          [0, 0, 1, 1, 0, 0]
                          [0, 0, 2, 2, 0, 0]
                          [0, 0, 0, 0, 0, 0]]

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| ## Args ||
|---|---|
| `input` | A `Tensor`. |
| `paddings` | A `Tensor`. Must be one of the following types: `int32`, `int64`. |
| `constant_values` | A `Tensor`. Must have the same type as `input`. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
|---|---|
| A `Tensor`. Has the same type as `input`. ||

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