# tf.raw_ops.MirrorPadGrad

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Gradient op for `MirrorPad` op. This op folds a mirror-padded tensor.

#### View aliases


**Compat aliases for migration**

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

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

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    tf.raw_ops.MirrorPadGrad(
        input, paddings, mode, name=None
    )

This operation folds the padded areas of `input` by `MirrorPad` according to the
`paddings` you specify. `paddings` must be the same as `paddings` argument
given to the corresponding `MirrorPad` op.

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

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

#### For example:

    # 't' is [[1, 2, 3], [4, 5, 6], [7, 8, 9]].
    # 'paddings' is [[0, 1]], [0, 1]].
    # 'mode' is SYMMETRIC.
    # rank of 't' is 2.
    pad(t, paddings) ==> [[ 1,  5]
                          [11, 28]]

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| ## Args ||
|---|---|
| `input` | A `Tensor`. The input tensor to be folded. |
| `paddings` | A `Tensor`. Must be one of the following types: `int32`, `int64`. A two-column matrix specifying the padding sizes. The number of rows must be the same as the rank of `input`. |
| `mode` | A `string` from: `"REFLECT", "SYMMETRIC"`. The mode used in the `MirrorPad` op. |
| `name` | A name for the operation (optional). |

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

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