getLr.py

import torch
import os
import json
from transformers import AutoModelForCausalLM


def extract_and_merge_instruction_residual(
    instruction_model_dir, 
    base_model_dir, 
    output_dir,
):
    """
    Extract instruction residual in full precision (float32) without any loss.
    """

    # Load models
    base_model = AutoModelForCausalLM.from_pretrained(
        base_model_dir,
        torch_dtype=torch.float32,
        device_map="cpu",
        trust_remote_code=True
    )

    instruction_model = AutoModelForCausalLM.from_pretrained(
        instruction_model_dir,
        torch_dtype=torch.float32,
        device_map="cpu",
        trust_remote_code=True
    )

    base_state_dict = base_model.state_dict()
    instruction_state_dict = instruction_model.state_dict()

    # Compute high-precision residual
    residual_state_dict = {}
    for key in base_state_dict:
        if key in instruction_state_dict:
            residual_state_dict[key] = (instruction_state_dict[key] - base_state_dict[key]).to(torch.float32)
        else:
            print(f"Warning: Key {key} not found in instruction model state dict")

    os.makedirs(output_dir, exist_ok=True)

    adapter_path = os.path.join(output_dir, "instruction_residual_adapter")
    os.makedirs(adapter_path, exist_ok=True)
    torch.save(residual_state_dict, os.path.join(adapter_path, "adapter_model.bin"))

    # Adapter config
    adapter_config = {
        "adapter_type": "instruction_residual",
        "base_model_name_or_path": base_model_dir,
        "target_modules": ["all"],
        "lora_alpha": 1.0,
        "lora_dropout": 0.0,
        "task_type": "CAUSAL_LM"
    }

    with open(os.path.join(adapter_path, "adapter_config.json"), "w") as f:
        json.dump(adapter_config, f, indent=4)

    print(f"✅ Full-precision (float32) instruction residual adapter saved to {adapter_path}")


if __name__ == "__main__":
    instruction_model_file = "/workspace/meta-llama/Llama-3.2-3B-Instruct"
    base_model_file = "/workspace/meta-llama/Llama-3.2-3B"
    residual_output_file = "/workspace/Llama-3.2-3B-Lr"

    extract_and_merge_instruction_residual(
        instruction_model_file,
        base_model_file,
        residual_output_file,
    )