46e62efd44
### What this PR does / why we need it? Currently, MTP Model in deepseek can not be capture in ACLGraph. This PR is use to allow MTP to be captured in ACLGraph mode. ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.11.0rc3 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0 Signed-off-by: anon189Ty <Stari_Falcon@outlook.com>
69 lines
2.6 KiB
Python
69 lines
2.6 KiB
Python
import torch
|
|
from vllm.config import CUDAGraphMode
|
|
from vllm.v1.spec_decode.ngram_proposer import \
|
|
NgramProposer as VllmNgramProposer
|
|
|
|
from vllm_ascend.spec_decode.interface import Proposer, SpecDcodeType
|
|
|
|
|
|
class NgramProposer(VllmNgramProposer, Proposer):
|
|
|
|
def __init__(self, vllm_config, device, runner):
|
|
super().__init__(vllm_config)
|
|
self.name = SpecDcodeType.NGRAM
|
|
self.device = device
|
|
self.runner = runner
|
|
|
|
def load_model(self, *args, **kwargs):
|
|
# No model to load.
|
|
pass
|
|
|
|
@torch.inference_mode()
|
|
def dummy_run(self,
|
|
num_tokens,
|
|
with_prefill=None,
|
|
skip_attn=None,
|
|
num_reqs=None,
|
|
num_tokens_across_dp=None,
|
|
aclgraph_runtime_mode: CUDAGraphMode = CUDAGraphMode.NONE,
|
|
batch_descriptor=None):
|
|
pass
|
|
|
|
def generate_token_ids(self,
|
|
valid_sampled_token_ids,
|
|
sampling_metadata=None,
|
|
scheduler_output=None,
|
|
spec_decode_metadata=None,
|
|
positions=None,
|
|
num_scheduled_tokens=None,
|
|
hidden_states=None,
|
|
attn_metadata=None,
|
|
aux_hidden_states=None) -> list[list[int]]:
|
|
# TODO(woosuk): Optimize.
|
|
draft_token_ids: list[list[int]] = []
|
|
for i, sampled_ids in enumerate(valid_sampled_token_ids):
|
|
num_sampled_ids = len(sampled_ids)
|
|
if not num_sampled_ids:
|
|
# Skip speculative decoding.
|
|
draft_token_ids.append([])
|
|
continue
|
|
|
|
# Skip requests that require top-p, top-k, etc.
|
|
req_id = self.runner.input_batch.req_ids[i]
|
|
if req_id in self.runner.input_batch.spec_decode_unsupported_reqs:
|
|
draft_token_ids.append([])
|
|
continue
|
|
|
|
# Add sampled_token_ids to token_ids_cpu.
|
|
start_idx = self.runner.input_batch.num_tokens_no_spec[i]
|
|
end_idx = start_idx + num_sampled_ids
|
|
self.runner.input_batch.token_ids_cpu[
|
|
i, start_idx:end_idx] = sampled_ids
|
|
drafter_output = self.propose(
|
|
self.runner.input_batch.token_ids_cpu[i, :end_idx])
|
|
if drafter_output is None or len(drafter_output) == 0:
|
|
draft_token_ids.append([])
|
|
else:
|
|
draft_token_ids.append(drafter_output.tolist())
|
|
return draft_token_ids
|