meg-huggingface
Cleaning up
f5a3abd
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("AIEnergyScore/requests_debug", split="test",
token=TOKEN).to_pandas()
# 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("AIEnergyScore/requests_debug", split="test",
token=TOKEN)