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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) | |