SoftMax-8 specification (#7911)

* prepared the specification

* updated versioned name

* fixed op number in link
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Yegor Kruglov 2021-10-14 21:11:41 +03:00 committed by GitHub
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@ -262,6 +262,7 @@ limitations under the License.
<tab type="user" title="Sin-1" url="@ref openvino_docs_ops_arithmetic_Sin_1"/> <tab type="user" title="Sin-1" url="@ref openvino_docs_ops_arithmetic_Sin_1"/>
<tab type="user" title="Sinh-1" url="@ref openvino_docs_ops_arithmetic_Sinh_1"/> <tab type="user" title="Sinh-1" url="@ref openvino_docs_ops_arithmetic_Sinh_1"/>
<tab type="user" title="SoftMax-1" url="@ref openvino_docs_ops_activation_SoftMax_1"/> <tab type="user" title="SoftMax-1" url="@ref openvino_docs_ops_activation_SoftMax_1"/>
<tab type="user" title="SoftMax-8" url="@ref openvino_docs_ops_activation_SoftMax_8"/>
<tab type="user" title="SoftPlus-4" url="@ref openvino_docs_ops_activation_SoftPlus_4"/> <tab type="user" title="SoftPlus-4" url="@ref openvino_docs_ops_activation_SoftPlus_4"/>
<tab type="user" title="SpaceToBatch-2" url="@ref openvino_docs_ops_movement_SpaceToBatch_2"/> <tab type="user" title="SpaceToBatch-2" url="@ref openvino_docs_ops_movement_SpaceToBatch_2"/>
<tab type="user" title="SpaceToDepth-1" url="@ref openvino_docs_ops_movement_SpaceToDepth_1"/> <tab type="user" title="SpaceToDepth-1" url="@ref openvino_docs_ops_movement_SpaceToDepth_1"/>

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## SoftMax <a name="SoftMax"></a> {#openvino_docs_ops_activation_SoftMax_8}
**Versioned name**: *SoftMax-8*
**Category**: *Activation function*
**Short description**: [Reference](https://github.com/Kulbear/deep-learning-nano-foundation/wiki/ReLU-and-Softmax-Activation-Functions#softmax)
**Detailed description**: [Reference](http://cs231n.github.io/linear-classify/#softmax)
**Attributes**
* *axis*
* **Description**: *axis* represents the axis of which the *SoftMax* is calculated. Negative value means counting
dimensions from the back. *axis* equal 1 is a default value.
* **Range of values**: `[-rank, rank - 1]`
* **Type**: int
* **Default value**: 1
* **Required**: *no*
**Mathematical Formulation**
\f[
y_{c} = \frac{e^{Z_{c}}}{\sum_{d=1}^{C}e^{Z_{d}}}
\f]
where \f$C\f$ is a size of tensor along *axis* dimension.
**Inputs**:
* **1**: Input tensor with enough number of dimension to be compatible with *axis* attribute. **Required.**
**Outputs**:
* **1**: The resulting tensor of the same shape and type as input tensor.
**Example**
```xml
<layer ... type="SoftMax" ... >
<data axis="1" />
<input> ... </input>
<output> ... </output>
</layer>
```

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@ -152,7 +152,7 @@ declared in `namespace opset8`.
* [Sign](arithmetic/Sign_1.md) * [Sign](arithmetic/Sign_1.md)
* [Sin](arithmetic/Sin_1.md) * [Sin](arithmetic/Sin_1.md)
* [Sinh](arithmetic/Sinh_1.md) * [Sinh](arithmetic/Sinh_1.md)
* [SoftMax](activation/SoftMax_1.md) * [SoftMax](activation/SoftMax_8.md)
* [SoftPlus](activation/SoftPlus_4.md) * [SoftPlus](activation/SoftPlus_4.md)
* [SpaceToBatch](movement/SpaceToBatch_2.md) * [SpaceToBatch](movement/SpaceToBatch_2.md)
* [SpaceToDepth](movement/SpaceToDepth_1.md) * [SpaceToDepth](movement/SpaceToDepth_1.md)