mirror of https://github.com/hpcaitech/ColossalAI
34 lines
1016 B
Python
34 lines
1016 B
Python
from typing import Optional
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import torch.nn as nn
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from transformers.models.gpt2.configuration_gpt2 import GPT2Config
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from transformers.models.gpt2.modeling_gpt2 import GPT2Model
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from .critic import Critic
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class GPTCritic(Critic):
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"""
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GPT Critic model.
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Args:
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pretrained (str): Pretrained model name or path.
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config (GPT2Config): Model config.
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checkpoint (bool): Enable gradient checkpointing.
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"""
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def __init__(self,
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pretrained: Optional[str] = None,
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config: Optional[GPT2Config] = None,
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checkpoint: bool = False) -> None:
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if pretrained is not None:
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model = GPT2Model.from_pretrained(pretrained)
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elif config is not None:
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model = GPT2Model(config)
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else:
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model = GPT2Model(GPT2Config())
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if checkpoint:
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model.gradient_checkpointing_enable()
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value_head = nn.Linear(model.config.n_embd, 1)
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super().__init__(model, value_head)
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