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#!/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
# 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()
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