"""Correctness runner for KDA forward (chunk form). Runs solution.Model vs reference.Model across all shapes in shapes.py, 3 seeds each, with per-dtype atol/rtol (bf16 default 1e-2 plus a 5e-2 override for this problem). Also rejects forbidden ops by grep. """ import re import sys from pathlib import Path import torch import yaml # Make the repo's src/ importable REPO_ROOT = Path(__file__).resolve().parents[2] sys.path.insert(0, str(REPO_ROOT)) from src.eval.correctness import check_correctness # noqa: E402 def _apply_shape(reference, shape): """Override reference's module-level shape shims so get_inputs/get_init_inputs match.""" for k, v in shape.items(): setattr(reference, k, v) def main(): try: import reference import shapes import solution except Exception as e: print(f"FAIL: import error: {e}") sys.exit(1) problem_yaml = Path("problem.yaml") meta = yaml.safe_load(problem_yaml.read_text()) if problem_yaml.exists() else {} # --- Forbidden-op check ------------------------------------------------ sol_src = Path("solution.py").read_text() if Path("solution.py").exists() else "" for forbidden in meta.get("forbidden", []): pat = re.escape(forbidden) if re.search(pat, sol_src): print(f"FAIL: forbidden op used: {forbidden}") sys.exit(1) device = torch.device("cuda:0") tol_override = meta.get("tolerance") or None # --- Per-shape correctness -------------------------------------------- all_shapes = shapes.SHAPES for shape_idx, shape in enumerate(all_shapes): _apply_shape(reference, shape) init_args = reference.get_init_inputs() ref_model = reference.Model(*init_args).to(device).eval() sol_model = solution.Model(*init_args).to(device).eval() # Share weights/buffers. strict=True closes the "identity kernel" cheat. sd = ref_model.state_dict() try: sol_model.load_state_dict(sd, strict=True) except RuntimeError as e: print(f"FAIL: state_dict mismatch at shape {shape_idx} ({shape}): {e}") sys.exit(1) for seed in (42, 123, 456): torch.manual_seed(seed) torch.cuda.manual_seed_all(seed) inputs = [t.to(device) if hasattr(t, "to") else t for t in reference.get_inputs()] with torch.no_grad(): ref_out = ref_model(*inputs) sol_out = sol_model(*inputs) ok, msg = check_correctness( ref_out, sol_out, dtype=ref_out.dtype, override=tol_override, ) if not ok: print(f"FAIL: shape {shape_idx} {shape} seed {seed}: {msg}") sys.exit(1) # --- Framework label (for stats) -------------------------------------- _emit_framework_label() print("PASS") def _emit_framework_label(): """Write framework.txt with the detected kernel framework.""" patterns = [ ("ptx", r"asm\s+volatile|asm\s*\(|mma\.sync|tcgen05\."), ("cutlass3", r"\bcute::|cutlass/gemm/collective|cutlass::arch::Sm(9|10|12)"), ("cutlass2", r"cutlass/gemm/device/gemm|cutlass::gemm::device"), ("cuda_wmma", r"\bnvcuda::wmma\b|wmma::fragment"), ("triton", r"import\s+triton\b|@triton\.jit|\btl\.dot\b"), ("cuda_raw", r"torch\.utils\.cpp_extension\.load_inline|__global__\s+void"), ] sol = Path("solution.py") if not sol.exists(): return code = sol.read_text() label = "unknown" for name, pat in patterns: if re.search(pat, code): label = name break Path("framework.txt").write_text(label + "\n") if __name__ == "__main__": main()