launch-computation-example / create_results.py
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import os
import sys
from datasets import load_dataset, Dataset
from huggingface_hub import HfApi
import pandas as pd
TOKEN = os.environ.get("DEBUG")
api = HfApi(token=TOKEN)
out_dir = sys.argv[1]
all_attempts_read = open("/app/attempts.txt", "r+").readlines()
failed_attempts_read = open("/app/failed_attempts.txt", "r+").readlines()
# Uploading output to the results dataset.
api.upload_folder(
folder_path=out_dir,
repo_id="AIEnergyScore/results_debug",
repo_type="dataset",
)
# Updating requests
requests = load_dataset("AIEnergyScore/requests_debug", split="test",
token=TOKEN)
requests_dset = requests.to_pandas()
for line in all_attempts_read:
experiment_name, model = line.strip().split(',')
if line not in failed_attempts_read:
requests_dset.loc[
requests_dset["model"] == model, ['status']] = "COMPLETED"
else:
requests_dset.loc[
requests_dset["model"] == model, ['status']] = "FAILED"
updated_dset = Dataset.from_pandas(requests_dset)
updated_dset.push_to_hub("AIEnergyScore/requests_debug", split="test",
token=TOKEN)
print("Updated model status")