mirror of https://github.com/hpcaitech/ColossalAI
35 lines
1.0 KiB
Python
35 lines
1.0 KiB
Python
from typing import Optional
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import torch
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from .configuration_chatglm import ChatGLMConfig
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from .modeling_chatglm import ChatGLMForConditionalGeneration
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from ..base import Actor
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class ChatGLMActor(Actor):
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"""
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ChatGLM Actor model.
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Args:
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pretrained (str): Pretrained model name or path.
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config (ChatGLMConfig): Model config.
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checkpoint (bool): Enable gradient checkpointing.
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do not support lora for now.
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"""
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def __init__(self,
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pretrained: str = None,
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config: Optional[ChatGLMConfig] = None,
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checkpoint: bool = False) -> None:
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if pretrained is not None:
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model = ChatGLMForConditionalGeneration.from_pretrained(pretrained)
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elif config is not None:
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model = ChatGLMForConditionalGeneration(config)
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else:
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model = ChatGLMForConditionalGeneration(ChatGLMConfig())
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if checkpoint:
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model.gradient_checkpointing_enable()
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super().__init__(model, lora_rank=0, lora_train_bias='none')
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