onnxruntime

[QNN EP] Support Conv + Clip/Relu fusion (#21537)

### Description
- Supports quantized Conv + Activation on the HTP backend:
- Translates `DQs -> Conv -> Relu/Clip -> Q` into a single QNN Conv
operator if the Relu (or Clip) are redundant.



### Motivation and Context
Expands support for QDQ models created with tools that do not wrap Relu
or Clip with QDQ nodes.

This PR introduces the `IQnnNodeGroup` class. In the same way that a
`NodeUnit` represents a collection of `Nodes`, a `IQnnNodeGroup` can
represent one or more `NodeUnits` that are translated into a QNN
operator. QNN EP parses the ONNX graph to create a list of
`IQnnNodeGroup` objects, each representing a single `NodeUnit` or a
fusion of multiple `NodeUnits`.