2021-12-21 20:26:37 +03:00
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# SoftMax {#openvino_docs_ops_activation_SoftMax_8}
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2021-10-14 21:11:41 +03:00
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**Versioned name**: *SoftMax-8*
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**Category**: *Activation function*
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**Short description**: [Reference](https://github.com/Kulbear/deep-learning-nano-foundation/wiki/ReLU-and-Softmax-Activation-Functions#softmax)
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**Detailed description**: [Reference](http://cs231n.github.io/linear-classify/#softmax)
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**Attributes**
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* *axis*
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* **Description**: *axis* represents the axis of which the *SoftMax* is calculated. Negative value means counting
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dimensions from the back. *axis* equal 1 is a default value.
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* **Range of values**: `[-rank, rank - 1]`
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* **Type**: int
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* **Default value**: 1
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* **Required**: *no*
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**Mathematical Formulation**
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\f[
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y_{c} = \frac{e^{Z_{c}}}{\sum_{d=1}^{C}e^{Z_{d}}}
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\f]
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where \f$C\f$ is a size of tensor along *axis* dimension.
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**Inputs**:
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* **1**: Input tensor with enough number of dimension to be compatible with *axis* attribute. **Required.**
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**Outputs**:
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* **1**: The resulting tensor of the same shape and type as input tensor.
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**Example**
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```xml
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<layer ... type="SoftMax" ... >
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<data axis="1" />
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<input> ... </input>
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<output> ... </output>
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</layer>
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```
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