# tf.raw_ops.MaxPool3DGradGrad

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Computes second-order gradients of the maxpooling function.

#### View aliases


**Compat aliases for migration**

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

[`tf.compat.v1.raw_ops.MaxPool3DGradGrad`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/MaxPool3DGradGrad)

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    tf.raw_ops.MaxPool3DGradGrad(
        orig_input,
        orig_output,
        grad,
        ksize,
        strides,
        padding,
        data_format='NDHWC',
        name=None
    )

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| ## Args ||
|---|---|
| `orig_input` | A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `int64`, `bfloat16`, `uint16`, `half`, `uint32`, `uint64`. The original input tensor. |
| `orig_output` | A `Tensor`. Must have the same type as `orig_input`. The original output tensor. |
| `grad` | A `Tensor`. Must have the same type as `orig_input`. Output backprop of shape `[batch, depth, rows, cols, channels]`. |
| `ksize` | A list of `ints` that has length `>= 5`. 1-D tensor of length 5. The size of the window for each dimension of the input tensor. Must have `ksize[0] = ksize[4] = 1`. |
| `strides` | A list of `ints` that has length `>= 5`. 1-D tensor of length 5. The stride of the sliding window for each dimension of `input`. Must have `strides[0] = strides[4] = 1`. |
| `padding` | A `string` from: `"SAME", "VALID"`. The type of padding algorithm to use. |
| `data_format` | An optional `string` from: `"NDHWC", "NCDHW"`. Defaults to `"NDHWC"`. The data format of the input and output data. With the default format "NDHWC", the data is stored in the order of: \[batch, in_depth, in_height, in_width, in_channels\]. Alternatively, the format could be "NCDHW", the data storage order is: \[batch, in_channels, in_depth, in_height, in_width\]. |
| `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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