SkipLayerNormalization (CPU)
============================

* Domain: ``com.microsoft``
* Device: ``CPU``
* Kernel: ``onnx_light_cpu::SkipLayerNormalization``
* Supported types: ``FLOAT``, ``FLOAT16``, ``BFLOAT16``
* Opset bounds: since opset 1

Operator support
----------------

.. list-table::
   :header-rows: 1
   :widths: 30 70

   * - Capability
     - Implementation
   * - Shape inference
     - :cpp:func:`onnx_light_cpu::ComputeShapeSkipLayerNormalization`
   * - Peak memory
     - :cpp:func:`onnx_light_cpu::ComputePeakMemorySkipLayerNormalization`
   * - Fusion patterns
     - None
   * - Gradient
     - Not provided

LightOpSchema
~~~~~~~~~~~~~

**Version:** 1

Adds input, skip, and optional bias, then applies last-axis layer normalization, gamma scaling, and optional beta. Supports rank-2 and rank-3 inputs with matching FLOAT, FLOAT16, or BFLOAT16 types. For rank-3 input, skip may omit the batch dimension or have batch size one. Optional FLOAT statistics contain the mean and inverse standard deviation. Optional output slot 3 contains the residual sum in the input type.

**Inputs**

- **input** (``T``): Input tensor with shape (S, H) or (B, S, H), with 0 < H <= INT_MAX.
- **skip** (``T``): Residual tensor matching input, or (S, H)/(1, S, H) for rank-3 input.
- **gamma** (``T``): Rank-1 scale tensor with length H.
- **beta** (``T``): Optional rank-1 shift tensor with length H.
- **bias** (``T``): Optional rank-1 bias added to the residual, with length H.

**Outputs**

- **output** (``T``): Normalized result with the input shape and type.
- **mean** (``U``): Optional FLOAT mean with input shape and final dimension one.
- **inv_std_var** (``U``): Optional FLOAT inverse standard deviation with input shape and final dimension one.
- **input_skip_bias_sum** (``T``): Optional residual sum with the input shape and type.

**Attributes**

- **epsilon** (``FLOAT``): Finite nonnegative value added to the last-axis variance. (optional, default: ``1e-12``)

**Type constraints**

- **T**: Matching FLOAT, FLOAT16, or BFLOAT16 tensors. Allowed types: tensor(bfloat16), tensor(float), tensor(float16).
- **U**: FLOAT saved-statistics tensors. Allowed types: tensor(float).