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import datetime |
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import subprocess |
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from pathlib import Path |
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import pandas as pd |
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import typer |
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from click.utils import echo |
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from datasets import get_dataset_config_names, load_dataset |
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CSV_SCHEMA = { |
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"banking_77": (5000, 2), |
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"overruling": (2350, 2), |
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"semiconductor_org_types": (449, 2), |
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"ade_corpus_v2": (5000, 2), |
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"twitter_complaints": (3399, 2), |
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"neurips_impact_statement_risks": (150, 2), |
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"systematic_review_inclusion": (2244, 2), |
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"terms_of_service": (5000, 2), |
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"tai_safety_research": (1639, 2), |
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"one_stop_english": (518, 2), |
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"tweet_eval_hate": (2966, 2), |
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} |
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app = typer.Typer() |
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@app.command() |
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def install(): |
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typer.echo("Installing dependencies ...") |
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try: |
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p = subprocess.run( |
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"pip install --upgrade pip".split(), |
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stderr=subprocess.PIPE, |
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stdout=subprocess.PIPE, |
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check=True, |
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encoding="utf-8", |
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) |
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except subprocess.CalledProcessError as exc: |
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raise EnvironmentError(exc.stderr) |
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try: |
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p = subprocess.run( |
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"pip install --upgrade -r requirements.txt".split(), |
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stderr=subprocess.PIPE, |
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stdout=subprocess.PIPE, |
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check=True, |
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encoding="utf-8", |
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) |
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except subprocess.CalledProcessError as exc: |
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raise EnvironmentError(exc.stderr) |
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typer.echo("Success!") |
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@app.command() |
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def validate(): |
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tasks = get_dataset_config_names("ought/raft") |
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prediction_files = list(Path("data").rglob("*.csv")) |
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mismatched_files = set(tasks).symmetric_difference(set([f.parent.name for f in prediction_files])) |
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if mismatched_files: |
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raise ValueError(f"Incorrect number of files! Expected {len(tasks)} files, but got {len(prediction_files)}.") |
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shape_errors = [] |
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column_errors = [] |
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for prediction_file in prediction_files: |
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df = pd.read_csv(prediction_file) |
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incorrect_shape = df.shape != CSV_SCHEMA[prediction_file.parent.name] |
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if incorrect_shape: |
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shape_errors.append(prediction_file) |
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incorrect_columns = sorted(df.columns) != ["ID", "Label"] |
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if incorrect_columns: |
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column_errors.append(prediction_file) |
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if shape_errors: |
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raise ValueError(f"Incorrect CSV shapes in files: {shape_errors}") |
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if column_errors: |
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raise ValueError(f"Incorrect CSV columns in files: {column_errors}") |
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load_errors = [] |
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for task in tasks: |
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try: |
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_ = load_dataset("../{{cookiecutter.repo_name}}", task) |
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except Exception as e: |
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load_errors.append(e) |
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if load_errors: |
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raise ValueError(f"Could not load predictions! Errors: {load_errors}") |
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typer.echo("All submission files validated! ✨ 🚀 ✨") |
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typer.echo("Now you can make a submission 🤗") |
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@app.command() |
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def submit(): |
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subprocess.call("git pull origin main".split()) |
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subprocess.call(["git", "add", "."]) |
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subprocess.call(["git", "commit", "-m", "Submission"]) |
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subprocess.call(["git", "push"]) |
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today = datetime.date.today() |
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idx = (today.weekday() + 1) % 7 |
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sun = today + datetime.timedelta(7 - idx) |
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typer.echo("Submission successful! 🎉 🥳 🎉") |
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typer.echo(f"Your submission will be evaulated on {sun:%A %d %B %Y} ⏳") |
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if __name__ == "__main__": |
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app() |
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