# tf.raw_ops.FractionalMaxPoolGrad

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Computes gradient of the FractionalMaxPool function.

#### View aliases


**Compat aliases for migration**

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

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

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    tf.raw_ops.FractionalMaxPoolGrad(
        orig_input,
        orig_output,
        out_backprop,
        row_pooling_sequence,
        col_pooling_sequence,
        overlapping=False,
        name=None
    )

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| ## Args ||
|---|---|
| `orig_input` | A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `int64`. Original input for `fractional_max_pool` |
| `orig_output` | A `Tensor`. Must have the same type as `orig_input`. Original output for `fractional_max_pool` |
| `out_backprop` | A `Tensor`. Must have the same type as `orig_input`. 4-D with shape `[batch, height, width, channels]`. Gradients w.r.t. the output of `fractional_max_pool`. |
| `row_pooling_sequence` | A `Tensor` of type `int64`. row pooling sequence, form pooling region with col_pooling_sequence. |
| `col_pooling_sequence` | A `Tensor` of type `int64`. column pooling sequence, form pooling region with row_pooling sequence. |
| `overlapping` | An optional `bool`. Defaults to `False`. When set to True, it means when pooling, the values at the boundary of adjacent pooling cells are used by both cells. For example: <br /> `index 0 1 2 3 4` `value 20 5 16 3 7` If the pooling sequence is \[0, 2, 4\], then 16, at index 2 will be used twice. The result would be \[20, 16\] for fractional max pooling. |
| `name` | A name for the operation (optional). |

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

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