[Frontend] [Core] Add Tensorizer support for LoRA adapter serialization and deserialization

[sangstar]

Serializing and deserializing LoRA adapters using tensorizer

This PR allows LoRA adapters to be serialized and deserialized using tensorizer. A test is added to confirm this and serializing LoRA files can be done with the same script that can save vLLM models in examples/tensorize_vllm_model.py.

Summary of changes

• Adjusted the CLI args for .buildkite/test-pipeline.yaml's invocation of the tensorize_vllm_model.py example script to additionally save and load a LoRA adapter, testing a model generation after deserialization to confirm the LoRA adapter was loaded properly
• Added --lora-path to tensorize_vllm_model.py as a base argparser argument that allows a user to specify the HuggingFace reference ID for a LoRA adapter, which can be either serialized or deserialized depending on whether the serialize or deserialize subparser is indicated.
• Added test_serialize_and_deserialize_lora to test_tensorizer.py testing saving and loading LoRA adapters with tensorizer.
• Allows deserializing a LoRA adapter by allowing TensorizerConfig to be passed in as a kwarg to LoRARequest. When this is done, the LoRA tensors are assumed to be in tensorizer's .tensors format and deserialized according to the parameters given in the TensorizerConfig provided.

[github-actions]

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