import argparse import os import sys import textwrap import pandas as pd def get_field(csv, model_name: str, field: str): try: return csv.loc[csv["name"] == model_name][field].item() except Exception as e: return None def check_graph_breaks(actual_csv, expected_csv, expected_filename): failed = [] improved = [] for model in actual_csv["name"]: graph_breaks = get_field(actual_csv, model, "graph_breaks") expected_graph_breaks = get_field(expected_csv, model, "graph_breaks") if graph_breaks == expected_graph_breaks: status = "PASS" print(f"{model:34} {status}") continue elif graph_breaks > expected_graph_breaks: status = "FAIL:" failed.append(model) elif graph_breaks < expected_graph_breaks: status = "IMPROVED:" improved.append(model) print( f"{model:34} {status:9} graph_breaks={graph_breaks}, expected={expected_graph_breaks}" ) msg = "" if failed or improved: if failed: msg += textwrap.dedent( f""" Error: {len(failed)} models have new dynamo graph breaks: {' '.join(failed)} """ ) if improved: msg += textwrap.dedent( f""" Improvement: {len(improved)} models have fixed dynamo graph breaks: {' '.join(improved)} """ ) sha = os.getenv("SHA1", "{your CI commit sha}") msg += textwrap.dedent( f""" If this change is expected, you can update `{expected_filename}` to reflect the new baseline. from pytorch/pytorch root, run `python benchmarks/dynamo/ci_expected_accuracy/update_expected.py {sha}` and then `git add` the resulting local changes to expected CSVs to your commit. """ ) return failed or improved, msg def main(): parser = argparse.ArgumentParser() parser.add_argument("--actual", type=str, required=True) parser.add_argument("--expected", type=str, required=True) args = parser.parse_args() actual = pd.read_csv(args.actual) expected = pd.read_csv(args.expected) failed, msg = check_graph_breaks(actual, expected, args.expected) if failed: print(msg) sys.exit(1) if __name__ == "__main__": main()