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Runtime error
| import argparse | |
| import os | |
| from datasets import load_dataset, Dataset | |
| from huggingface_hub import HfApi | |
| TOKEN = os.environ.get("DEBUG") | |
| api = HfApi(token=TOKEN) | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument( | |
| "--run_dir", | |
| default=None, | |
| type=str, | |
| required=True, | |
| help="Path to the run directory.", | |
| ) | |
| parser.add_argument( | |
| "--model_name", | |
| default=None, | |
| type=str, | |
| required=True, | |
| help="Model to benchmark.", | |
| ) | |
| args = parser.parse_args() | |
| # Updating request | |
| dataset = load_dataset("EnergyStarAI/requests_debug", split="test", token=TOKEN).to_pandas() | |
| def upload_results(output_dir): | |
| models_ran=[] | |
| for f in os.scandir(output_dir): | |
| if f.is_dir(): | |
| for s in os.scandir(f): | |
| if s.is_dir() and s.name not in ['hooks','info','objects','refs','logs']: | |
| for m in os.scandir(s): | |
| models_ran.append(s.name+'/' + m.name) | |
| return models_ran | |
| # Set benchmark to failed | |
| # TODO: This doesn't have to be try-except, we could actually check if the file is there. | |
| try: | |
| # Read error message | |
| with open(f"{args.run_dir}/error.log", 'r') as file: | |
| for f in file.readlines(): | |
| if 'Traceback (most recent call last):' in f: | |
| error_message = f | |
| dataset.loc[dataset["model"].isin([args.model_name]), ['status']] = "FAILED" | |
| print("Status set to FAILED") | |
| else: | |
| dataset.loc[dataset["model"].isin([args.model_name]), ['status']] = "COMPLETED" | |
| # Add a new column for the error message if necessary | |
| except FileNotFoundError as e: | |
| print(f"Could not find {args.run_dir}/error.log") | |
| updated_dataset = Dataset.from_pandas(dataset) | |
| updated_dataset.push_to_hub("EnergyStarAI/requests_debug", split="test", token=TOKEN) | |