[WIP] Add HPU support to vLLM v1 - cont.

[kzawora-intel]

Up-to-date variant of #487 after rebase and with functional TP. Diff will become more readable once #605 gets merged.

• Implemented v1 HPU attn backend, worker, model_runner and executor
• VLLM_USE_V1=1 properly selects V1 HPU components
• V1 HPU executor loads model properly
• V1 HPU executor allocates KV cache properly
• V1 HPU model runner is constructed properly and initializes bucketing
• V1 HPU attention backend gets selected automatically
• profile_run works on dummy data
• V1 HPU model_runner prepares input tensors based on SchedulerOutputs (rather than SequenceGroupMetadata)
• V1 HPU model_runner differentiates prefill and decode sequences
• V1 HPU model_runner execute_model runs for prefill
• V1 HPU model_runner execute_model runs for decode
• V1 HPU model_runner handles mixed-batch scenarios
• V1 HPU model_runner prefill returns correct results
• V1 HPU model_runner decode returns correct results (w/ flat PA)
• V1 HPU model_runner decode returns correct results (w/ contiguous PA)
• V1 HPU model_runner prefill runs at BS>1
• V1 standard greedy and random sampling work on HPU
• Capturing and replaying HPU Graphs work
• Llama3.1-8B runs on GSM-8k with SOTA accuracy
• V1 HPU model_runner warmup works properly
• V1 HPU automatic prefix caching works properly
• Tensor parallelism works
• torch.compile works