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import argparse
import json
import os
import shlex
import shutil
import subprocess
from huggingface_hub import HfApi, hf_hub_download, snapshot_download
from huggingface_hub.utils._errors import EntryNotFoundError
from loguru import logger
from competitions import utils
from competitions.compute_metrics import compute_metrics
from competitions.enums import SubmissionStatus
from competitions.params import EvalParams
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--config", type=str, required=True)
return parser.parse_args()
def upload_submission_file(params, file_path):
logger.info("Uploading submission file")
pass
def generate_submission_file(params):
logger.info("Downloading submission dataset")
submission_dir = snapshot_download(
repo_id=params.submission_repo,
local_dir=params.output_path,
token=os.environ.get("USER_TOKEN"),
repo_type="model",
)
# submission_dir has a script.py file
# start a subprocess to run the script.py
# the script.py will generate a submission.csv file in the submission_dir
# push the submission.csv file to the repo using upload_submission_file
logger.info("Generating submission file")
# Copy socket-kit.so to submission_dir
shutil.copyfile("socket-kit.so", f"{submission_dir}/socket-kit.so")
# Define your command
cmd = "python script.py"
socket_kit_path = os.path.abspath(f"{submission_dir}/socket-kit.so")
# Copy the current environment and modify it
env = os.environ.copy()
env["LD_PRELOAD"] = socket_kit_path
cmd = shlex.split(cmd)
# Start the subprocess
process = subprocess.Popen(cmd, cwd=submission_dir, env=env)
# Wait for the process to complete or timeout
try:
process.wait(timeout=params.time_limit)
except subprocess.TimeoutExpired:
logger.info(f"Process exceeded {params.time_limit} seconds time limit. Terminating...")
process.kill()
process.wait()
# Check if process terminated due to timeout
if process.returncode and process.returncode != 0:
logger.error("Subprocess didn't terminate successfully")
else:
logger.info("Subprocess terminated successfully")
logger.info("contents of submission_dir")
logger.info(os.listdir(submission_dir))
api = HfApi(token=params.token)
for sub_file in params.submission_filenames:
logger.info(f"Uploading {sub_file} to the repository")
sub_file_ext = sub_file.split(".")[-1]
api.upload_file(
path_or_fileobj=f"{submission_dir}/{sub_file}",
path_in_repo=f"submissions/{params.team_id}-{params.submission_id}.{sub_file_ext}",
repo_id=params.competition_id,
repo_type="dataset",
)
@utils.monitor
def run(params):
logger.info(params)
if isinstance(params, dict):
params = EvalParams(**params)
utils.update_submission_status(params, SubmissionStatus.PROCESSING.value)
if params.competition_type == "script":
try:
requirements_fname = hf_hub_download(
repo_id=params.competition_id,
filename="requirements.txt",
token=params.token,
repo_type="dataset",
)
except EntryNotFoundError:
requirements_fname = None
if requirements_fname:
logger.info("Installing requirements")
utils.uninstall_requirements(requirements_fname)
utils.install_requirements(requirements_fname)
if len(str(params.dataset).strip()) > 0:
# _ = Repository(local_dir="/tmp/data", clone_from=params.dataset, token=params.token)
_ = snapshot_download(
repo_id=params.dataset,
local_dir="/tmp/data",
token=params.token,
repo_type="dataset",
)
generate_submission_file(params)
evaluation = compute_metrics(params)
utils.update_submission_score(params, evaluation["public_score"], evaluation["private_score"])
utils.update_submission_status(params, SubmissionStatus.SUCCESS.value)
utils.delete_space(params)
if __name__ == "__main__":
args = parse_args()
_params = json.load(open(args.config, encoding="utf-8"))
_params = EvalParams(**_params)
run(_params)
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