.. _l-onnx-doccom.microsoft-QLinearSoftmax:

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com.microsoft - QLinearSoftmax
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.. contents::
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.. _l-onnx-opcom-microsoft-qlinearsoftmax-1:

QLinearSoftmax - 1 (com.microsoft)
==================================

**Version**

* **name**: `QLinearSoftmax (GitHub) <https://github.com/onnx/onnx/blob/main/docs/Operators.md#com.microsoft.QLinearSoftmax>`_
* **domain**: **com.microsoft**
* **since_version**: **1**
* **function**:
* **support_level**:
* **shape inference**:

This version of the operator has been available
**since version 1 of domain com.microsoft**.

**Summary**

QLinearSoftmax computes the normalized exponential values for the given input:
Softmax(input, axis) = Exp(input) / ReduceSum(Exp(input), axis=axis, keepdims=1)
The input does not need to explicitly be a 2D vector. The "axis" attribute
indicates the dimension along which QLinearSoftmax will be performed for onnx v.13+.
or the dimension coerced to NxD Matrix for onnx v.12-.
The output tensor has the same shape.

**Attributes**

* **axis**:
  apply softmax to elements for dimensions axis,or all dims along with
  axis according to op-version Default value is ``?``.
* **opset** (required):
  opset version of corresponding SoftMax. Default value is ``?``.

**Inputs**

* **X** (heterogeneous) - **T**:
  The input tensor
* **X_scale** (heterogeneous) - **tensor(float)**:
  Scale of quantized input 'X'. It must be a scalar.
* **x_zero_point** (optional, heterogeneous) - **T**:
  Zero point tensor for input 'X'.It must be a scalar.
* **y_scale** (heterogeneous) - **tensor(float)**:
  Scale of quantized output 'Y'. It must be a scalar.
* **y_zero_point** (heterogeneous) - **T**:
  Zero point tensor for output 'Y'. It must be a scalar.

**Outputs**

* **Y** (heterogeneous) - **T**:
  Output data tensor from pooling across the input tensor. The output
  tensor has the same rank as the input.

**Examples**