ColossalAI/applications/Chat/coati/models/gpt/gpt_rm.py

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2023-03-28 12:25:36 +00:00
from typing import Optional
import torch.nn as nn
from transformers.models.gpt2.configuration_gpt2 import GPT2Config
from transformers.models.gpt2.modeling_gpt2 import GPT2Model
from ..base import RewardModel
class GPTRM(RewardModel):
"""
GPT Reward model.
Args:
pretrained (str): Pretrained model name or path.
config (GPT2Config): Model config.
lora_rank (int): Rank of the low-rank approximation.
lora_train_bias (str): LoRA bias training mode.
"""
def __init__(self,
pretrained: Optional[str] = None,
config: Optional[GPT2Config] = None,
lora_rank: int = 0,
lora_train_bias: str = 'none') -> None:
if pretrained is not None:
model = GPT2Model.from_pretrained(pretrained)
elif config is not None:
model = GPT2Model(config)
else:
model = GPT2Model(GPT2Config())
value_head = nn.Linear(model.config.n_embd, 1)
value_head.weight.data.normal_(mean=0.0, std=1 / (model.config.n_embd + 1))
super().__init__(model, value_head, lora_rank, lora_train_bias)