onnxruntime

LLaMA Model Optimization (#18021)

### Description
This PR contains fusion-level and kernel-level optimizations for [Meta's
LLaMA-2](https://blogs.microsoft.com/blog/2023/07/18/microsoft-and-meta-expand-their-ai-partnership-with-llama-2-on-azure-and-windows/).

Some of the added optimizations include:

- SimplifiedLayerNorm changes
  - Fusions for multiple variants
- SkipSimplifiedLayerNorm changes
  - Kernel support for CPU
- Rotary embeddings (previously did not exist)
  - Fusions for multiple variants
  - CPU and CUDA kernels
  - Supports interleaving and non-interleaving in the same kernels
  - Optimized cache that requires half of its originally exported sizes
- Reduced from `(max_sequence_length, head_size)` to
`(max_sequence_length, head_size / 2)`
- Multi-head attention
  - Support for 2D and 3D attention masks
- Group query attention (for FP16 CUDA and INT4 CUDA)
  - Integration with flash attention v2 and past-present buffer sharing
- Removes need for `attention_mask` input as it is supported in the
kernel
- 4 bit quantization
  - `block_size` parameter is available for customizing
- Support the new changes for [Microsoft
version](https://github.com/microsoft/Llama-2-Onnx)
- Support combinations of the below variants (ex: export ORT version and
run with Optimum)

Supported variants of LLaMA-2 include:
- [ORT
version](https://github.com/microsoft/onnxruntime/tree/main/onnxruntime/python/tools/transformers/models/llama)
- Produces one ONNX file that is already optimized (and quantized if
requested)
  - Integrates with Optimum
- [Another Microsoft version](https://github.com/microsoft/Llama-2-Onnx)
  - Already exported and available off-the-shelf
  - Faster versions of those models will be uploaded there soon
- [Hugging Face version](https://huggingface.co/meta-llama)
  - Models that end with `-hf`
- Some older and current versions of
[`transformers`](https://github.com/huggingface/transformers) and
[`optimum`](https://github.com/huggingface/optimum) that export the
model to ONNX differently
- Note that while some older versions are supported, it is recommended
to use the latest package versions.

### Usage

To use the optimizations, please see `README.md` for details. Please
note the various `requirements.txt` files for the package versions
recommended in order to use these changes.

To run the ORT transformer optimizer separately, run the script as
follows:
```
$ cd onnxruntime/onnxruntime/python/tools/transformers/
$ python3 optimizer.py --input <filename>.onnx --output <filename>.onnx --model_type gpt2 --num_heads <number of attention heads> --hidden_size <attention hidden size> --use_external_data_format --opt_level 0
```

### Motivation and Context
This PR helps the following issues:
- https://github.com/microsoft/onnxruntime/issues/14997
- https://github.com/microsoft/onnxruntime/issues/16254
- https://github.com/microsoft/onnxruntime/issues/17681
- https://github.com/microsoft/onnxruntime/issues/17925
- https://github.com/microsoft/onnxruntime-inference-examples/issues/320

This PR uses changes from the following PRs:
- https://github.com/pytorch/pytorch/pull/104468
- https://github.com/pytorch/pytorch/pull/109759
- https://github.com/microsoft/onnxruntime/pull/17020
- https://github.com/microsoft/onnxruntime/pull/17674
- https://github.com/microsoft/onnxruntime/pull/17890
- https://github.com/microsoft/onnxruntime/pull/17920
- https://github.com/huggingface/transformers/pull/26162
- https://github.com/huggingface/optimum/pull/1257
- https://github.com/huggingface/optimum/pull/1289
- https://github.com/huggingface/optimum/pull/1462

### New TorchDynamo Exporter (experimental stage)

This PR uses changes from the following issues and PRs to begin
supporting the [new TorchDynamo
exporter](https://pytorch.org/docs/stable/onnx.html#torchdynamo-based-onnx-exporter):
- https://github.com/huggingface/transformers/pull/26307
- https://github.com/pytorch/pytorch/issues/104903
- https://github.com/pytorch/pytorch/pull/105040
- https://github.com/microsoft/onnxscript/pull/847
- https://github.com/microsoft/onnxscript/pull/862
- https://github.com/microsoft/onnxscript/issues/493