mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 11:56:44 +08:00
98 lines
4.3 KiB
Python
98 lines
4.3 KiB
Python
"""
|
||
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
|
||
#
|
||
# Licensed under the Apache License, Version 2.0 (the "License"
|
||
# you may not use this file except in compliance with the License.
|
||
# You may obtain a copy of the License at
|
||
#
|
||
# http://www.apache.org/licenses/LICENSE-2.0
|
||
#
|
||
# Unless required by applicable law or agreed to in writing, software
|
||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||
# See the License for the specific language governing permissions and
|
||
# limitations under the License.
|
||
"""
|
||
from typing import Any, Dict, Optional
|
||
|
||
from fastdeploy.engine.config import ModelConfig
|
||
from fastdeploy.reasoning import ReasoningParserManager
|
||
|
||
|
||
class InputPreprocessor:
|
||
"""
|
||
Args:
|
||
model_name_or_path (str):
|
||
Model name or path to the pretrained model. If a model name is provided, it should be a
|
||
key in the Hugging Face Transformers' model registry (https://huggingface.co/models).
|
||
The model will be downloaded from the Hugging Face model hub if necessary.
|
||
If a path is provided, the model will be loaded from that path.
|
||
reasoning_parser (str, optional):
|
||
Reasoning parser type. Defaults to None.
|
||
Flag specifies the reasoning parser to use for extracting reasoning content from the model output
|
||
enable_mm (bool, optional):
|
||
Whether to use the multi-modal model processor. Defaults to False.
|
||
|
||
Raises:
|
||
ValueError:
|
||
If the model name is not found in the Hugging Face Transformers' model registry and the path does not
|
||
exist.
|
||
"""
|
||
|
||
def __init__(
|
||
self,
|
||
model_name_or_path: str,
|
||
reasoning_parser: str = None,
|
||
limit_mm_per_prompt: Optional[Dict[str, Any]] = None,
|
||
mm_processor_kwargs: Optional[Dict[str, Any]] = None,
|
||
enable_mm: bool = False,
|
||
) -> None:
|
||
|
||
self.model_name_or_path = model_name_or_path
|
||
self.reasoning_parser = reasoning_parser
|
||
self.enable_mm = enable_mm
|
||
self.limit_mm_per_prompt = limit_mm_per_prompt
|
||
self.mm_processor_kwargs = mm_processor_kwargs
|
||
|
||
def create_processor(self):
|
||
"""
|
||
创建数据处理器。如果启用了多模态注册表，则使用该表中的模型；否则，使用传递给构造函数的模型名称或路径。
|
||
返回值：DataProcessor（如果不启用多模态注册表）或MultiModalRegistry.Processor（如果启用多模态注册表）。
|
||
|
||
Args:
|
||
无参数。
|
||
|
||
Returns:
|
||
DataProcessor or MultiModalRegistry.Processor (Union[DataProcessor, MultiModalRegistry.Processor]): 数据处理器。
|
||
"""
|
||
reasoning_parser_obj = None
|
||
if self.reasoning_parser:
|
||
reasoning_parser_obj = ReasoningParserManager.get_reasoning_parser(
|
||
self.reasoning_parser)
|
||
architectures = ModelConfig(self.model_name_or_path).architectures
|
||
if not self.enable_mm:
|
||
if "Ernie4_5_MoeForCausalLM" not in architectures \
|
||
and "Ernie4_5_ForCausalLM" not in architectures:
|
||
from fastdeploy.input.text_processor import DataProcessor
|
||
self.processor = DataProcessor(
|
||
model_name_or_path=self.model_name_or_path, reasoning_parser_obj=reasoning_parser_obj)
|
||
else:
|
||
from fastdeploy.input.ernie_processor import ErnieProcessor
|
||
self.processor = ErnieProcessor(
|
||
model_name_or_path=self.model_name_or_path, reasoning_parser_obj=reasoning_parser_obj)
|
||
else:
|
||
if not architectures.startswith(
|
||
"Ernie4_5_VLMoeForConditionalGeneration"):
|
||
raise ValueError(
|
||
f"Model {self.model_name_or_path} is not a valid Ernie4_5_VLMoe model."
|
||
)
|
||
else:
|
||
from fastdeploy.input.ernie_vl_processor import \
|
||
ErnieMoEVLProcessor
|
||
self.processor = ErnieMoEVLProcessor(
|
||
model_name_or_path=self.model_name_or_path,
|
||
limit_mm_per_prompt=self.limit_mm_per_prompt,
|
||
mm_processor_kwargs=self.mm_processor_kwargs,
|
||
reasoning_parser_obj=reasoning_parser_obj)
|
||
return self.processor
|