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83 lines
3.0 KiB
Python
83 lines
3.0 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import os
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from typing import Optional, Union
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from transformers import AutoConfig, PretrainedConfig
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from vllm.transformers_utils.configs.deepseek_vl2 import DeepseekV2Config
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class EAGLEConfig(PretrainedConfig):
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model_type = "eagle"
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def __init__(self,
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model: Union[PretrainedConfig, dict, None] = None,
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truncated_vocab_size: Optional[int] = None,
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method: Optional[str] = 'eagle',
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**kwargs):
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model_config: Union[PretrainedConfig, DeepseekV2Config, None]
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if isinstance(model, dict):
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archs = model.get("architectures", [])
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target_archs = ["DeepseekV2ForCausalLM", "DeepseekV3ForCausalLM"]
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if any(target_arch in archs for target_arch in target_archs):
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# AutoConfig does not support DeepSeek MoE models yet
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model_config = DeepseekV2Config(**model)
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else:
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model_config = AutoConfig.for_model(**model)
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else:
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model_config = model
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for k, v in kwargs.items():
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if k != "architectures" and k != "model_type" and hasattr(
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model_config, k):
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setattr(model_config, k, v)
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self.model = model_config
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if self.model is None:
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self.truncated_vocab_size = None
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else:
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self.truncated_vocab_size = self.model.vocab_size if \
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truncated_vocab_size is None else truncated_vocab_size
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# Eagle model name should follow naming convention of
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# LlamaForCausalLM -> EagleLlamaForCausalLM
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# LlamaForCausalLM -> Eagle3LlamaForCausalLM / LlamaForCausalLMEagle3
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if method == "eagle":
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assert self.model is not None, \
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"model should not be None when method is eagle"
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kwargs["architectures"] = [
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f"Eagle{arch}" if not arch.startswith("Eagle") \
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else arch for arch in self.model.architectures
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]
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elif method == "eagle3":
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assert self.model is not None, \
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"model should not be None when method is eagle3"
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kwargs["architectures"] = [
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arch if arch.startswith("Eagle3") or arch.endswith("Eagle3")
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else f"Eagle3{arch}" for arch in self.model.architectures
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]
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else:
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raise ValueError(f"Invalid method {method}. \
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Supported methods are eagle and eagle3.")
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super().__init__(**kwargs)
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if self.model is not None:
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for k, v in self.model.to_dict().items():
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if k not in kwargs:
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setattr(self, k, v)
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@classmethod
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def from_pretrained(
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cls,
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pretrained_model_name_or_path: Union[str, os.PathLike],
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**kwargs,
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) -> "EAGLEConfig":
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config_dict, kwargs = cls.get_config_dict(
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pretrained_model_name_or_path, **kwargs)
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return cls.from_dict(config_dict, **kwargs)
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