Add fusions for SigLIP and Conformer-Encoder (#23528)
### Description
This PR adds fusions for [Google's SigLIP
model](https://huggingface.co/google/siglip-base-patch16-224/) and
Microsoft's internal conformer-encoder model.
Here is an example of how to run the ORT transformer optimizer for the
SigLIP model.
```
$ git clone https://github.com/microsoft/onnxruntime
$ cd onnxruntime/onnxruntime/python/tools/transformers
$ python3 optimizer.py --input /path/to/model.onnx --output /path/to/model_opt.onnx --model_type clip --num_heads 16 --hidden_size 1152 --use_external_data_format --opt_level 0 --disable_shape_inference
```
Here is an example of how to run the ORT transformer optimizer for the
conformer-encoder model.
```
$ git clone https://github.com/microsoft/onnxruntime
$ cd onnxruntime/onnxruntime/python/tools/transformers
$ python3 optimizer.py --input /path/to/model.onnx --output /path/to/model_opt.onnx --model_type conformer --num_heads 16 --hidden_size 1024 --use_external_data_format --opt_level 0 --disable_shape_inference --convert_attribute
```
### Motivation and Context
This PR helps optimize multi-modal models that use SigLIP for the vision
encoder and conformer-encoder for the speech encoder.
This PR uses changes from the following PRs:
- https://github.com/pytorch/pytorch/pull/144801
- https://github.com/microsoft/onnxscript/pull/2018
- https://github.com/microsoft/onnxscript/pull/2019
- https://github.com/microsoft/onnxscript/pull/2020
- https://github.com/microsoft/onnxscript/pull/2021
- https://github.com/microsoft/onnxscript/pull/2022
- https://github.com/microsoft/onnxscript/pull/2024
- https://github.com/microsoft/onnxscript/pull/2025
- https://github.com/microsoft/onnxscript/pull/2029
- https://github.com/microsoft/onnxscript/pull/2033
### Introduction of ONNX Script
This PR introduces [ONNX
Script](https://github.com/microsoft/onnxscript) into the ORT
transformer optimizer as an optional step via the
`fold_transpose_initializers()` method of the `DynamoOnnxHelper` class.
