d4370ebc42
### What this PR does / why we need it?
Refactor spec decode
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
CI passed with new added/existing test.
- vLLM version: v0.10.1.1
- vLLM main:
6997a25ac6
---------
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Signed-off-by: Icey <1790571317@qq.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
66 lines
2.4 KiB
Python
66 lines
2.4 KiB
Python
import torch
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from vllm.v1.spec_decode.ngram_proposer import \
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NgramProposer as VllmNgramProposer
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from vllm_ascend.spec_decode.interface import Proposer, SpecDcodeType
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class NgramProposer(VllmNgramProposer, Proposer):
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def __init__(self, vllm_config, device, runner):
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super().__init__(vllm_config)
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self.name = SpecDcodeType.NGRAM
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self.device = device
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self.runner = runner
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def load_model(self, *args, **kwargs):
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# No model to load.
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pass
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@torch.inference_mode()
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def dummy_run(self,
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num_tokens,
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with_prefill=None,
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skip_attn=None,
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num_reqs=None,
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num_tokens_across_dp=None):
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pass
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def generate_token_ids(self,
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valid_sampled_token_ids,
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sampling_metadata=None,
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scheduler_output=None,
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spec_decode_metadata=None,
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positions=None,
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num_scheduled_tokens=None,
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hidden_states=None,
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attn_metadata=None,
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aux_hidden_states=None) -> list[list[int]]:
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# TODO(woosuk): Optimize.
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draft_token_ids: list[list[int]] = []
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for i, sampled_ids in enumerate(valid_sampled_token_ids):
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num_sampled_ids = len(sampled_ids)
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if not num_sampled_ids:
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# Skip speculative decoding.
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draft_token_ids.append([])
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continue
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# Skip requests that require top-p, top-k, etc.
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req_id = self.runner.input_batch.req_ids[i]
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if req_id in self.runner.input_batch.spec_decode_unsupported_reqs:
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draft_token_ids.append([])
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continue
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# Add sampled_token_ids to token_ids_cpu.
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start_idx = self.runner.input_batch.num_tokens_no_spec[i]
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end_idx = start_idx + num_sampled_ids
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self.runner.input_batch.token_ids_cpu[
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i, start_idx:end_idx] = sampled_ids
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drafter_output = self.propose(
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self.runner.input_batch.token_ids_cpu[i, :end_idx])
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if drafter_output is None or len(drafter_output) == 0:
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draft_token_ids.append([])
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else:
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draft_token_ids.append(drafter_output.tolist())
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return draft_token_ids
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