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			74 lines
		
	
	
		
			2.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			74 lines
		
	
	
		
			2.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| """
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| # Copyright (c) 2025  PaddlePaddle Authors. All Rights Reserved.
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| #
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| # Licensed under the Apache License, Version 2.0 (the "License"
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| # you may not use this file except in compliance with the License.
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| # You may obtain a copy of the License at
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| #
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| #     http://www.apache.org/licenses/LICENSE-2.0
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| #
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| # Unless required by applicable law or agreed to in writing, software
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| # distributed under the License is distributed on an "AS IS" BASIS,
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| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| # See the License for the specific language governing permissions and
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| # limitations under the License.
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| """
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| 
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| from abc import ABC, abstractmethod
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| from copy import deepcopy
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| from typing import Any
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| 
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| from fastdeploy.config import FDConfig
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| from fastdeploy.utils import spec_logger
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| 
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| 
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| class Proposer(ABC):
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|     """
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|     Proposer Base Class.
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| 
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|     Used to provide an extensible interface for draft tokens within
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|     the speculative decoding framework
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|     """
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| 
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|     def __init__(self, cfg: FDConfig):
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|         """
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|         Init Speculative proposer
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|         """
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|         self.cfg = deepcopy(cfg)
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|         self.parallel_config = self.cfg.parallel_config
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|         self.model_config = self.cfg.model_config
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|         self.speculative_config = self.cfg.speculative_config
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|         self.kv_cache_config = self.cfg.kv_cache_config
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|         self.quant_config = self.cfg.quant_config
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| 
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|         self.max_num_seqs = self.parallel_config.max_num_seqs
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|         self.max_model_len = self.parallel_config.max_model_len
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|         self.speculative_method = self.speculative_config.method
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|         self.max_draft_token_num = self.speculative_config.num_speculative_tokens
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| 
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|         spec_logger.info(f"Speculate config: {self.speculative_config}")
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| 
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|     def run(self, *args, **kwargs) -> Any:
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|         """
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|         Unified entry point for all proposer types.
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|         Dispatches to subclass-specific logic via `_run_impl`.
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|         """
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|         return self._run_impl(*args, **kwargs)
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| 
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|     @abstractmethod
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|     def _run_impl(self, *args, **kwargs) -> Any:
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|         """
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|         Implemention for different method
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|         """
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|         raise NotImplementedError
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| 
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|     def is_chunk_prefill_enabled(self) -> bool:
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|         """
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|         Check whether chunk-based prefill is enabled.
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|         Default is False.
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| 
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|         Returns:
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|             bool: True if chunk prefill is enabled; False otherwise.
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|         """
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|         return False
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