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import pathlib |
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from pathlib import Path |
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import tempfile |
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from typing import BinaryIO, Literal |
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import json |
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import pandas as pd |
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import gradio as gr |
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from datasets import load_dataset, Dataset |
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from huggingface_hub import upload_file, hf_hub_download |
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from gradio_leaderboard import ColumnFilter, Leaderboard, SelectColumns |
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from evaluation import evaluate_problem |
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from datetime import datetime |
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import os |
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from about import PROBLEM_TYPES, TOKEN, CACHE_PATH, API, submissions_repo, results_repo |
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def read_boundary(filename): |
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local_path = hf_hub_download( |
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repo_id=submissions_repo, |
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repo_type="dataset", |
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filename=filename, |
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) |
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return local_path |
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def write_results(record, result): |
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record.update(result) |
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record['result_filename'] = record['submission_filename'].rstrip('.json') + '_results.json' |
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print(record['result_filename']) |
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record['evaluated'] = True |
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record["objectives"] = json.dumps(record.get("objectives", [])) |
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record["feasibilities"] = json.dumps(record.get("feasibility", [])) |
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if 'objective' not in record.keys(): |
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record['objective'] = 0.0 |
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record['minimize_objective'] = True |
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record['feasibility'] = 0.0 |
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with tempfile.NamedTemporaryFile(mode="w", suffix=".json", delete=False) as tmp: |
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json.dump(record, tmp, indent=2) |
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tmp.flush() |
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tmp_name = tmp.name |
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API.upload_file( |
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path_or_fileobj=tmp_name, |
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path_in_repo=record['result_filename'], |
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repo_id=results_repo, |
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repo_type="dataset", |
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commit_message=f"Add result data for {record['result_filename']}" |
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) |
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pathlib.Path(tmp_name).unlink() |
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return |
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def get_user(profile: gr.OAuthProfile | None) -> str: |
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if profile is None: |
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return "Please login to submit a boundary for evaluation." |
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return profile.username |
