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from typing import Any, Dict, List, Tuple
import torch
from copy import deepcopy
from transformers import AutoModelForCausalLM, AutoTokenizer
from .GRACE import GRACE
from .grace_hparams import GraceHyperParams
from .utils import tokenize
from ...util import nethook
import gradio as gr
def apply_grace_to_model(
model: AutoModelForCausalLM,
tok: AutoTokenizer,
requests: List[Dict],
hparams: GraceHyperParams,
num_steps: int,
edit_lr: float,
copy=False,
return_orig_weights=False,
keep_original_weight=False,
**kwargs: Any,
) -> Tuple[AutoModelForCausalLM, Dict[str, Any]]:
request = requests
if copy:
model = deepcopy(model)
weights_copy = {}
device = torch.device('cpu')
hparams.edit_lr = edit_lr
editor = GRACE(model=model, config=hparams, device=device)
tokens = tokenize(request, tokenizer=tok, device=device)
editor.edit(config=hparams, tokens=tokens)
# editor.to('cpu')
gr.Info("Completed editing via GRACE!")
return editor
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