onnxruntime

LayerNormalization broadcast (limited support for axis=2) (#23297)

### Description

Spec of LayerNormalization supports broadcasting (tensors Scale and B
should be unidirectional broadcastable to tensor X).
https://onnx.ai/onnx/operators/onnx__LayerNormalization.html
However, current implementation only allow scale and bias size to be
X.shape()[axis:].

Example of input tensors that normalized with axis=2:

| X shape |  Scale shape | B shape | Before | After |
| - | - | - | - | - |
| (B, S, D) | (D) | (D) | Supported | Supported |
| (B, S, D) | (1, 1, D) | (1, 1, D) | Supported | Supported |
| (B, S, D) | (B, 1, D) | (B, 1, D) | Not Supported | Supported |
| (B, S, D) | (1, S, D) | (1, S, D) | Not Supported | Supported |
| (B, S, D) | (B, S, D) | (B, S, D) | Not Supported | Supported |


Here we add limited support: axis=2; scale/bias has same shape;
scale/bias/X have same number of dimensions. It could support common use
case in LLM and vision models.

### Motivation and Context

Support Stable Diffusion 3.x and Flux model.