launch-computation-example / create_results.py
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sasha HF staff
Update 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]
#Uploading results
api.upload_folder(
folder_path=out_dir,
repo_id="EnergyStarAI/results_debug",
repo_type="dataset",
)
#Updating requests
requests = load_dataset("EnergyStarAI/requests_debug", split="test", token=TOKEN)
requests_dset = requests.to_pandas()
models_ran=[]
for f in os.scandir(out_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)
print("Models ran are: " + str(models_ran))
requests_dset.loc[requests_dset["model"].isin(models_ran), ['status']] = "COMPLETED"
updated_dset =Dataset.from_pandas(requests_dset)
updated_dset.push_to_hub("EnergyStarAI/requests_debug", split="test", token=TOKEN)
print("Updated model status")