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python
import os
import torch
from safetensors import safe_open
from safetensors.torch import save_file
import logging
import shutil
from datetime import datetime
# Set up logging
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:
# Check if input file exists
if not os.path.exists(input_file):
raise FileNotFoundError(f"Input file {input_file} not found.")
# Backup existing pytorch_model.bin if it exists
backup_existing_file(output_file)
# Load the safetensors 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()}
# Save as PyTorch bin file
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.") |