c3ad7dc2a4
* Specify AdaptiveAvgPool-8 and AdaptiveMaxPool-8 * Apply review feedback * Describe indices output * Apply review feedback * Apply review feedback * Update AdaptiveMaxPool_8.md * Apply suggestions from code review Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com> * Apply review feedback Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com>
71 lines
2.0 KiB
Markdown
71 lines
2.0 KiB
Markdown
## AdaptiveAvgPool<a name="AdaptiveAvgPool"></a> {#openvino_docs_ops_pooling_AdaptiveAvgPool_8}
|
|
|
|
**Versioned name**: *AdaptiveAvgPool-8*
|
|
|
|
**Category**: *Pooling*
|
|
|
|
**Short description**: Applies average pooling with adaptive kernel size over the input.
|
|
|
|
**Detailed description**: This operation calculates the output based on the first input and `output_size` determined by the second input.
|
|
The kernel dimensions are calculated using the following formulae for the `NCDHW` input case:
|
|
|
|
\f[
|
|
\begin{array}{lcl}
|
|
d_{start} &=& floor(i*D_{in}/D_{out})\\
|
|
d_{end} &=& ceil((i+1)*D_{in}/D_{out})\\
|
|
h_{start} &=& floor(j*H_{in}/H_{out})\\
|
|
h_{end} &=& ceil((j+1)*H_{in}/H_{out})\\
|
|
w_{start} &=& floor(k*W_{in}/W_{out})\\
|
|
w_{end} &=& ceil((k+1)*W_{in}/W_{out})
|
|
\end{array}
|
|
\f]
|
|
|
|
The output is calculated with the following formula:
|
|
|
|
\f[
|
|
Output(i,j,k) = \frac{Input[d_{start}:d_{end}, h_{start}:h_{end}, w_{start}:w_{end}]}{(d_{end}-d_{start})*(h_{end}-h_{start})*(w_{end}-w_{start})}
|
|
\f]
|
|
|
|
**Inputs**:
|
|
|
|
* **1**: 3D, 4D, or 5D input tensor of shape `[N, C, H]`, `[N, C, H, W]` or `[N, C, D, H, W]` and type *T*. Required.
|
|
* **2**: 1D tensor describing output shape for spatial dimensions. Can be `[H_out]` for 3D input, `[H_out, W_out]` for 4D input, `[D_out, H_out, W_out]` for 5D input and of type *T_SHAPE*. Required.
|
|
|
|
**Outputs**:
|
|
|
|
* **1**: Output of type *T* and shape `[N, C, H_out]`, `[N, C, H_out, W_out]` or `[N, C, D_out, H_out, W_out]`.
|
|
|
|
**Types**
|
|
|
|
* *T*: floating-point type.
|
|
* *T_SHAPE*: `int32` or `int64`.
|
|
|
|
**Examples**
|
|
|
|
```xml
|
|
<layer ... type="AdaptiveAvgPool" ... >
|
|
<data output_type="i64"/>
|
|
<input>
|
|
<port id="0">
|
|
<dim>1</dim>
|
|
<dim>3</dim>
|
|
<dim>32</dim>
|
|
<dim>32</dim>
|
|
</port>
|
|
</input>
|
|
<input>
|
|
<port id="1">
|
|
<dim>2</dim>
|
|
</port>
|
|
</input>
|
|
<output>
|
|
<port id="2">
|
|
<dim>1</dim>
|
|
<dim>3</dim>
|
|
<dim>16</dim>
|
|
<dim>16</dim>
|
|
</port>
|
|
</output>
|
|
</layer>
|
|
```
|