# tensorflow::ops::AvgPool3DGrad

`#include <nn_ops.h>`

Computes gradients of average pooling function.

## Summary

Arguments:

- scope: A [Scope](https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object
- orig_input_shape: The original input dimensions.
- grad: [Output](https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) backprop of shape `[batch, depth, rows, cols, channels]`.
- ksize: 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: 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: The type of padding algorithm to use.

<br />

Optional attributes (see `https://www.tensorflow.org/versions/r1.15/api_docs/cc/struct/tensorflow/ops/avg-pool3-d-grad/attrs#structtensorflow_1_1ops_1_1_avg_pool3_d_grad_1_1_attrs`):

- data_format: 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: \[batch, in_channels, in_depth, in_height, in_width\].

<br />

Returns:

- `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output`: The backprop for input.

<br />

| ### Constructors and Destructors ||
|---|---|
| `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1ac294eebcd4d868dfa68e6a5f7d4c5ea9(const ::https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input orig_input_shape, ::https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input grad, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding)` ||
| `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1a8362b0628d56d49ee76c24faaed842f9(const ::https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input orig_input_shape, ::https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input grad, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding, const https://www.tensorflow.org/versions/r1.15/api_docs/cc/struct/tensorflow/ops/avg-pool3-d-grad/attrs#structtensorflow_1_1ops_1_1_avg_pool3_d_grad_1_1_attrs & attrs)` ||

| ### Public attributes ||
|---|---|
| `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1ac7d2ea5c42f4949a936e71f6debf81be` | `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation` |
| `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1a9709fb2d31ca099ef81e317ecef40df8` | `::https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output` |

| ### Public functions ||
|---|---|
| `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1a30c25a58bfaad694e981cf0bbf407254() const ` | `::tensorflow::Node *` |
| `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1a4738d18b18c18a46d9f6d9c262df86a2() const ` | ` `` ` |
| `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1ac991ec111bedce628daadef30690cd18() const ` | ` `` ` |

| ### Public static functions ||
|---|---|
| `https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad_1aa9e0fbc35b1b72dd2e277ff5db79ca99(StringPiece x)` | `https://www.tensorflow.org/versions/r1.15/api_docs/cc/struct/tensorflow/ops/avg-pool3-d-grad/attrs#structtensorflow_1_1ops_1_1_avg_pool3_d_grad_1_1_attrs` |

| ### Structs ||
|---|---|
| [tensorflow::ops::AvgPool3DGrad::Attrs](https://www.tensorflow.org/versions/r1.15/api_docs/cc/struct/tensorflow/ops/avg-pool3-d-grad/attrs) | Optional attribute setters for [AvgPool3DGrad](https://www.tensorflow.org/versions/r1.15/api_docs/cc/class/tensorflow/ops/avg-pool3-d-grad#classtensorflow_1_1ops_1_1_avg_pool3_d_grad). |

## Public attributes

### operation

```
Operation operation
```

### output

```
::tensorflow::Output output
```

## Public functions

### AvgPool3DGrad

```
 AvgPool3DGrad(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input orig_input_shape,
  ::tensorflow::Input grad,
  const gtl::ArraySlice< int > & ksize,
  const gtl::ArraySlice< int > & strides,
  StringPiece padding
)
```

### AvgPool3DGrad

```
 AvgPool3DGrad(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input orig_input_shape,
  ::tensorflow::Input grad,
  const gtl::ArraySlice< int > & ksize,
  const gtl::ArraySlice< int > & strides,
  StringPiece padding,
  const AvgPool3DGrad::Attrs & attrs
)
```

### node

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

### operator::tensorflow::Input

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

### operator::tensorflow::Output

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

## Public static functions

### DataFormat

```
Attrs DataFormat(
  StringPiece x
)
```