Download research/problems/gemm_optimization/rectangles/evaluator.py from FrontierCS/Frontier-CS: direct link, hf CLI and curl.
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https://huggingface.co/datasets/FrontierCS/Frontier-CS/resolve/refs%2Fpr%2F3/research/problems/gemm_optimization/rectangles/evaluator.py
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hf download hf://datasets/FrontierCS/Frontier-CS@refs/pr/3/research/problems/gemm_optimization/rectangles/evaluator.py
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curl -L -o evaluator.py https://huggingface.co/datasets/FrontierCS/Frontier-CS/resolve/refs%2Fpr%2F3/research/problems/gemm_optimization/rectangles/evaluator.py
9.24 kB
| #!/usr/bin/env python3 | |
| import argparse | |
| import importlib.util | |
| import json | |
| import math | |
| import os | |
| import sys | |
| from pathlib import Path | |
| from types import ModuleType | |
| from typing import Any, Dict, List, Tuple | |
| # Add resources to path for imports | |
| HERE = Path(__file__).resolve().parent | |
| RESOURCES_DIR = HERE / "resources" | |
| sys.path.insert(0, str(RESOURCES_DIR)) | |
| from benchmark import run_benchmark | |
| from triton_matmul_baseline import matmul as baseline_matmul | |
| import torch | |
| import triton | |
| DEFAULT_SPEC = HERE / "resources" / "submission_spec.json" | |
| ARTIFACT_PATH = Path("./output_ans").resolve() | |
| def load_solution_module(solution_path: Path) -> ModuleType: | |
| """Load the solution module from the given path.""" | |
| if not solution_path.exists(): | |
| raise FileNotFoundError(f"solution.py not found at {solution_path}") | |
| spec = importlib.util.spec_from_file_location("submitted_solution", solution_path) | |
| if spec is None or spec.loader is None: | |
| raise ImportError(f"Failed to load spec for {solution_path}") | |
| module = importlib.util.module_from_spec(spec) | |
| spec.loader.exec_module(module) | |
| return module | |
| def materialize_artifact(result: Any, solution_path: Path) -> Path: | |
| """Materialize the solution result into an artifact file.""" | |
| ARTIFACT_PATH.parent.mkdir(parents=True, exist_ok=True) | |
| if isinstance(result, dict): | |
| with ARTIFACT_PATH.open("w", encoding="utf-8") as fout: | |
| json.dump(result, fout) | |
| return ARTIFACT_PATH | |
| if isinstance(result, str): | |
| # Check if the string could be a file path (reasonable length and no newlines) | |
| # before calling is_file() to avoid "File name too long" errors | |
| is_possible_path = len(result) < 4096 and '\n' not in result | |
| if is_possible_path: | |
| candidate = Path(result) | |
| try: | |
| if candidate.is_file(): | |
| with ARTIFACT_PATH.open("w", encoding="utf-8") as fout: | |
| json.dump({"program_path": str(candidate.resolve())}, fout) | |
| return ARTIFACT_PATH | |
| except OSError: | |
| # Path too long or other OS error - treat as code string | |
| pass | |
| # Treat as code string | |
| with ARTIFACT_PATH.open("w", encoding="utf-8") as fout: | |
| fout.write(result) | |
| return ARTIFACT_PATH | |
| raise TypeError( | |
| "Solution.solve() must return a dict/path-string/code-string; got " | |
| f"{type(result)!r}." | |
| ) | |
| def load_matmul_from_artifact(artifact_path: Path) -> Any: | |
| """Load the matmul function from the artifact.""" | |
| with artifact_path.open("r", encoding="utf-8") as fin: | |
| artifact = json.load(fin) | |
| if "code" in artifact: | |
| # Write code to temporary file and import as module to avoid Triton source inspection issues | |
| import tempfile | |
| import os | |
| try: | |
| # Create temporary file | |
| with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False) as f: | |
| f.write(artifact["code"]) | |
| temp_file = f.name | |
| # Import the module | |
| import importlib.util | |
| spec = importlib.util.spec_from_file_location("temp_matmul_module", temp_file) | |
| module = importlib.util.module_from_spec(spec) | |
| spec.loader.exec_module(module) | |
| if not hasattr(module, "matmul"): | |
| raise ValueError("Code must define a 'matmul' function") | |
| # Clean up temporary file | |
| os.unlink(temp_file) | |
| return module.matmul | |
| except Exception as e: | |
| # Clean up temporary file if it exists | |
| try: | |
| if 'temp_file' in locals(): | |
| os.unlink(temp_file) | |
| except: | |
| pass | |
| raise | |
| elif "program_path" in artifact: | |
| # Load from external file | |
| program_path = Path(artifact["program_path"]) | |
| if not program_path.exists(): | |
| raise FileNotFoundError(f"Program file not found: {program_path}") | |
| spec = importlib.util.spec_from_file_location("submitted_program", program_path) | |
| if spec is None or spec.loader is None: | |
| raise ImportError(f"Failed to load spec for {program_path}") | |
| module = importlib.util.module_from_spec(spec) | |
| spec.loader.exec_module(module) | |
| if not hasattr(module, "matmul"): | |
| raise ValueError("Program must define a 'matmul' function") | |
| return module.matmul | |
| else: | |
| raise ValueError("Artifact must contain either 'code' or 'program_path'") | |
| def evaluate_kernel_performance(matmul_func: Any) -> Dict[str, Any]: | |
| """Evaluate the performance of a Triton kernel implementation.""" | |
| try: | |
| # Run benchmark comparing against baseline | |
| result = run_benchmark(matmul_func, baseline_matmul, print_output=False) | |
| # Extract key metrics | |
| geometric_mean_speedup = result["geometric_mean_speedup"] | |
| arithmetic_mean_speedup = result["arithmetic_mean_speedup"] | |
| median_speedup = result["median_speedup"] | |
| pass_all = result["pass_all"] | |
| # Enforce strict correctness: if any test fails, score 0 | |
| if not pass_all: | |
| return { | |
| "error": "Correctness not 100% across all tests", | |
| "geometric_mean_speedup": geometric_mean_speedup, | |
| "arithmetic_mean_speedup": arithmetic_mean_speedup, | |
| "median_speedup": median_speedup, | |
| "score": 0, | |
| "pass_all": False, | |
| "total_tests": len(result["rows"]), | |
| "passed_tests": sum(1 for r in result["rows"] if r["close_passed"]), | |
| } | |
| # Calculate score (0-100 scale) | |
| # Map 1x-3x speedup to 0-100 points | |
| raw_score = min(geometric_mean_speedup, 3.0) | |
| score = max(0, (raw_score - 1.0) / 2.0 * 100) | |
| return { | |
| "geometric_mean_speedup": geometric_mean_speedup, | |
| "arithmetic_mean_speedup": arithmetic_mean_speedup, | |
| "median_speedup": median_speedup, | |
| "score": score, | |
| "pass_all": pass_all, | |
| "total_tests": len(result["rows"]), | |
| "passed_tests": sum(1 for r in result["rows"] if r["close_passed"]), | |
| } | |
| except Exception as e: | |
| return { | |
| "error": str(e), | |
| "score": 0, | |
| "pass_all": False, | |
| } | |
| def evaluate(solution_path: Path, spec_path: Path) -> dict: | |
| """Main evaluation function.""" | |
| try: | |
| # Load solution module | |
| module = load_solution_module(solution_path) | |
| if not hasattr(module, "Solution"): | |
| raise ValueError("Solution module must define a 'Solution' class") | |
| solution_class = module.Solution | |
| solution_instance = solution_class() | |
| if not hasattr(solution_instance, "solve"): | |
| raise ValueError("Solution class must have a 'solve' method") | |
| # Get solution result | |
| result = solution_instance.solve(spec_path) | |
| # Materialize artifact | |
| artifact_path = materialize_artifact(result, solution_path) | |
| # Load matmul function from artifact | |
| matmul_func = load_matmul_from_artifact(artifact_path) | |
| # Evaluate performance | |
| evaluation_result = evaluate_kernel_performance(matmul_func) | |
| return { | |
| "status": "success", | |
| "artifact_path": str(artifact_path), | |
| **evaluation_result, | |
| } | |
| except Exception as e: | |
| return { | |
| "status": "error", | |
| "error": str(e), | |
| "score": 0, | |
| } | |
| def main(): | |
| parser = argparse.ArgumentParser(description="Evaluate GEMM optimization solutions") | |
| parser.add_argument( | |
| "--solution-path", | |
| type=Path, | |
| default=Path("./solution.py"), | |
| help="Path to solution.py file", | |
| ) | |
| parser.add_argument( | |
| "--spec-path", | |
| type=Path, | |
| default=DEFAULT_SPEC, | |
| help="Path to specification file", | |
| ) | |
| parser.add_argument( | |
| "--output-path", | |
| type=Path, | |
| default=Path("./result.json"), | |
| help="Path to output result file", | |
| ) | |
| args = parser.parse_args() | |
| # Run evaluation | |
| result = evaluate(args.solution_path, args.spec_path) | |
| # Write result | |
| with args.output_path.open("w", encoding="utf-8") as fout: | |
| json.dump(result, fout, indent=2) | |
| # Print summary | |
| if result["status"] == "success": | |
| print(f"Evaluation completed successfully!") | |
| print(f"Score: {result['score']:.2f}/100") | |
| print(f"Geometric mean speedup: {result['geometric_mean_speedup']:.3f}x") | |
| print(f"Tests passed: {result['passed_tests']}/{result['total_tests']}") | |
| # Print score as last line for main_loop.sh to extract | |
| print(result['score']) | |
| else: | |
| print(f"Evaluation failed: {result['error']}") | |
| # Print error score as last line | |
| print("0") | |
| sys.exit(1) | |
| if __name__ == "__main__": | |
| main() | |