diff --git a/docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/normalization/rms-norm-15.rst b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/normalization/rms-norm-15.rst new file mode 100644 index 00000000000000..a2ad1621d2262b --- /dev/null +++ b/docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/normalization/rms-norm-15.rst @@ -0,0 +1,95 @@ +.. {#openvino_docs_ops_normalization_RMS_15} + +RMS +=== + + +.. meta:: + :description: Learn about RMS-15 - a normalization operation. + +**Versioned name**: *RMS-15* + +**Category**: *Normalization* + +**Short description**: Calculates Root Mean Square (RMS) normalization of the input tensor. + +**Detailed description** + +*RMSNorm* operation performs Root Mean Square (RMS) normalization on a given input ``data`` along dimensions specified by ``axes`` input. +`Reference `__. + +.. code-block:: py + + (x / Sqrt(ReduceMean(x^2, axes) + eps)) + + + - If the optional ``scale`` input is provided: + +.. code-block:: py + + (x / Sqrt(ReduceMean(x^2, axes) + eps)) * scale + + +**Attributes** + +* *epsilon* + + * **Description**: A very small value added to the variance for numerical stability. Ensures that division by zero does not occur for any normalized element. + * **Range of values**: a positive floating-point number + * **Type**: ``float`` + * **Required**: *yes* + +* *compute_type* + + * **Description**: The precision for internal computation, before scaling. + * **Range of values**: Supported floating point type: "f32", "f16", ... + * **Type**: ``string`` + * **Default value**: "undefined" (the same as the input type) + * **Required**: *no* + + +**Inputs** + +* **1**: ``data`` - Input data to be normalized. A tensor of type *T* and arbitrary shape. **Required.** + +* **2**: ``axes`` - 1D or scalar tensor which specifies indices of dimensions in ``data`` that define normalization slices. Allowed range of axes is ``[-r; r-1]`` where ``r = rank(data)``, the order can be not sorted. Negative value means counting dimensions from the back. Type *T_AXES*. **Required.** + +* **3**: ``scale`` - A tensor of type *T* containing the scale values for . The shape should be broadcastable to the shape of ``data`` tensor. **Optional.** + + +**Outputs** + +* **1**: Output tensor of the same shape and type as the ``data`` input tensor. + +**Types** + +* *T*: any floating point type. +* *T_AXES*: ``int64`` or ``int32``. + +**Example** + +.. code-block:: xml + :force: + + + + + + 6 + 12 + 10 + 24 + + + 1 + + + + + 6 + 12 + 10 + 24 + + +