| python |
| import os |
| import torch |
| from safetensors import safe_open |
| from safetensors.torch import save_file |
| import logging |
| import shutil |
| from datetime import datetime |
|
|
| |
| logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') |
|
|
| def backup_existing_file(file_path): |
| if os.path.exists(file_path): |
| timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") |
| backup_path = f"{file_path}.backup_{timestamp}" |
| shutil.copy2(file_path, backup_path) |
| logging.info(f"Created backup of existing file: {backup_path}") |
|
|
| def convert_safetensors_to_pytorch(input_file, output_file): |
| try: |
| |
| if not os.path.exists(input_file): |
| raise FileNotFoundError(f"Input file {input_file} not found.") |
|
|
| |
| backup_existing_file(output_file) |
|
|
| |
| logging.info(f"Loading safetensors file: {input_file}") |
| with safe_open(input_file, framework="pt", device="cpu") as f: |
| state_dict = {key: f.get_tensor(key) for key in f.keys()} |
|
|
| |
| logging.info(f"Saving as PyTorch bin file: {output_file}") |
| torch.save(state_dict, output_file) |
|
|
| logging.info("Conversion complete.") |
| logging.info(f"Created: {output_file}") |
|
|
| except Exception as e: |
| logging.error(f"An error occurred during conversion: {str(e)}") |
| raise |
|
|
| if __name__ == "__main__": |
| input_file = "maxcushion.safetensors" |
| output_file = "pytorch_model.bin" |
|
|
| try: |
| convert_safetensors_to_pytorch(input_file, output_file) |
| except Exception as e: |
| logging.error(f"Conversion failed: {str(e)}") |
| else: |
| logging.info("Script executed successfully.") |
