[SpecDecode] Add spec decode support

[MengqingCao]

What this PR does / why we need it?

Backport: #252
This support speculative decoding in Ascend, including speculating with a draft model、by matching n-grams in the prompt、using MLP speculators and using EAGLE based draft models.

Backport: #423
spec decode MultiStepWorker support TP1DraftModelRunner fully, support run the draft_model_runner with multi-step prepare on the NPU directly and support draft_model_runner use MLA.

1. before this pr, MultiStepWorker would not step into the branch using NPU prepare, but only into the branch using CPU prepare (line 52 of vllm_ascend/patch/patch_multi_step_worker.py). Although this has no effect on the correct operation of speculative decoding and the performance of the two branches is basically the same as of the current version, I support entering this branch in this PR. In general, there are two main changes in patch_multi_step_worker.py: first, the is_cuda_like() check is removed and the TP1DraftModelRunner rewritten in vllm_ascend is used; second, the supports_gpu_multi_step() function is made to return true on NPU devices when outer Multi_step_worker could work correct.

2. before this pr, TP1DraftModelRunner only supports Attention on NPU, but not MLA. The relevant adaptation is in vllm_ascend/worker/draft_model_runner.py. Although I don’t know why the input_positions of model_input.attn_metadata in vllm-ascend needs to be added in execute_model, it is done in model_runner.py, so I also made corresponding changes. Otherwise, when atten_backend is MLA, it will prompt that input_positions cannot be found.

3. I commented out two lines in draft_model_runner.py in line118 to support the scenario of K>1.

# lora_mapping=model_input.lora_mapping,
# lora_requests=model_input.lora_requests,

I added comments. In the future, when vllm-ascend supports lora feature, the changes here can be restored.

TODO：

• revert the patch when the related issues are addressed in vllm

How was this patch tested?

CI passed with new added test.

• e2e test for medusa proposer: tests/singlecard/spec_decode/e2e/test_medusa_correctness.py
• e2e test for mlp proposer: tests/singlecard/spec_decode/e2e/test_mlp_correctness.py
• e2e test for n-gram proposer: tests/singlecard/spec_decode/e2e/test_ngram_correctness.py

Tests for patched files:

• tests/singlecard/spec_decode/test_dynamic_spec_decode.py
• tests/singlecard/spec_decode/test_multi_step_worker.py
• tests/singlecard/spec_decode/test_ngram_worker.py
• tests/singlecard/spec_decode/test_spec_decode_worker.py

[MengqingCao]

There are 3 workflow cancled since a higher priority waiting request for limit-npu-4 exists. I think CI passed on (linux-arm64-npu-1, v0.8.4) is enough. WDYT? @wangxiyuan

[wangxiyuan]

# What's Patched and how it works:
# File: patch_xxx.py
#   1. vllm.spec_decode.multi_step_worker.MultiStepWorker.sampler_output
#    why:
#    how：
#    related pr(if no, explain why): 1. refused by vllm. 2. vllm doesn't support 3. prepare to submit....
#    future plane:
#   2. xxxx
# File: patch_yyy.py


# 0.8.4 patch doc:
# platform-0.8.4 + platform-common + worker-0.8.4 + worker-common
# ...

[MengqingCao]

Done.

CI in linux-arm64-npu-4, v0.8.4 failed due to the following reason:

Error: Error: failed to run script step: command terminated with non-zero exit code: Error executing in Docker Container: 137
Error: Process completed with exit code 1.
Error: Executing the custom container implementation failed. Please contact your self hosted runner administrator.

It seems no related to this pr, and the other 3 workflow is green

[wangxiyuan]

merged. Only fixed the merge conflict for the newest commit. No need to wait CI again.