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77 lines
2.2 KiB
Python
77 lines
2.2 KiB
Python
# Copyright 2023 Ant Group CO., Ltd.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
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# in compliance with the License. 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 distributed under the License
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# is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
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# or implied.
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from abc import ABC, abstractmethod
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class NNExecutor(ABC):
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"""
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Entry point of model execution in a certain pod.
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"""
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@classmethod
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def from_config(cls, nn_config, **kwargs):
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pass
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def __init__(self, backend_model, backend_tokenizer, init_args, **kwargs):
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self.backend_model = backend_model
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self.backend_tokenizer = backend_tokenizer
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self.init_args = init_args
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self.kwargs = kwargs
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class LLMExecutor(NNExecutor):
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@classmethod
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def from_config(cls, nn_config: dict, **kwargs):
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"""
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Args:
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nn_config
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"""
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if "nn_name" in nn_config:
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from nn4k.executor.hugging_face import HfLLMExecutor
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return HfLLMExecutor.from_config(nn_config)
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else:
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o = cls.__new__(cls)
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o._nn_config = nn_config
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return o
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@abstractmethod
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def execute_sft(self, args=None, callbacks=None, **kwargs):
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"""
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The entry point of SFT execution in a certain pod.
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"""
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raise NotImplementedError(f"{self.__class__.__name__} does not support SFT.")
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@abstractmethod
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def execute_rl_tuning(self, args=None, callbacks=None, **kwargs):
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"""
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The entry point of SFT execution in a certain pod.
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"""
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raise NotImplementedError(
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f"{self.__class__.__name__} does not support RL-Tuning."
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)
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def execute_inference(self, args, **kwargs):
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dataset = args.parse_dataset()
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ret = []
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for d in dataset:
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ret.append(self.inference(d))
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return ret
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@abstractmethod
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def inference(self, data, **kwargs):
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"""
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The entry point of inference. Usually for local invokers or model services.
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"""
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raise NotImplementedError()
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