46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
import torch
|
|
from vllm.config import CUDAGraphMode
|
|
from vllm.v1.spec_decode.suffix_decoding import \
|
|
SuffixDecodingProposer as VllmSuffixDecodingProposer
|
|
|
|
from vllm_ascend.spec_decode.interface import Proposer, SpecDcodeType
|
|
|
|
|
|
class SuffixDecodingProposer(VllmSuffixDecodingProposer, Proposer):
|
|
|
|
def __init__(self, vllm_config, device, runner):
|
|
super().__init__(vllm_config)
|
|
self.name = SpecDcodeType.SUFFIX
|
|
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,
|
|
in_graph_capturing=None,
|
|
num_reqs=None,
|
|
num_tokens_across_dp=None,
|
|
aclgraph_runtime_mode: CUDAGraphMode = CUDAGraphMode.NONE,
|
|
batch_descriptor=None,
|
|
dummy_compute_logits=lambda hidden_states: None,
|
|
is_profile=False):
|
|
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,
|
|
aux_hidden_states=None) -> list[list[int]]:
|
|
draft_token_ids = self.propose(self.runner.input_batch,
|
|
valid_sampled_token_ids)
|
|
return draft_token_ids
|