feat: add d4r inference engines and Windows parity tooling
Add native K/M/RR inference engines, HIP kernels, replay and validation harnesses, and Windows DLSS setup and runtime support. Include GPU profiling tools, build and packaging scripts, platform integration patches, and implementation documentation.
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#!/usr/bin/env python3
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"""Compare native K enc1/enc2 launches with the existing numpy reference."""
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import argparse
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import math
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import pathlib
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import sys
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import numpy as np
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SCRIPT = pathlib.Path(__file__).resolve()
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REFERENCE = SCRIPT.parent / "reference"
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if not (REFERENCE / "pwin_model.py").exists():
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REFERENCE = SCRIPT.parents[2] / "kernels" / "tools"
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sys.path.insert(0, str(REFERENCE))
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from pwin_model import pwin_encoder # noqa: E402
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class SyntheticParams:
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def __init__(self, folder):
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self.input = np.fromfile(folder / "input.bin", dtype=np.uint8)
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self.weights = np.fromfile(folder / "weights.bin", dtype=np.uint8)
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def i32x2(self, offset):
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return (8, 8) if offset == 0 else (0, 0)
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def ptr(self, offset):
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if offset == 8:
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return self.input, 0
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if offset == 64:
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return self.weights, 0
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raise ValueError(f"unsupported synthetic pointer offset {offset}")
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def f16(self, offset, byte, count):
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if offset != 64:
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raise ValueError(f"unsupported synthetic half pointer offset {offset}")
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return self.weights[byte:byte + 2 * count].view(np.float16).copy()
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def compare(name, actual, expected):
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if actual.shape != expected.shape:
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raise RuntimeError(f"{name} shape mismatch: {actual.shape} != {expected.shape}")
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if not np.isfinite(actual).all() or not np.isfinite(expected).all():
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raise RuntimeError(f"{name} contains NaN or Inf")
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diff = np.abs(actual.astype(np.float32) - expected.astype(np.float32))
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maximum = float(diff.max())
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relative = float((diff / np.maximum(np.abs(expected.astype(np.float32)), 1e-3)).max())
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rms = float(np.sqrt(np.mean(np.square(diff.astype(np.float64)))))
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peak = max(1.0, float(np.abs(expected.astype(np.float32)).max()))
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psnr = math.inf if rms == 0 else 20.0 * math.log10(peak / rms)
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mismatch = np.unravel_index(int(diff.argmax()), diff.shape)
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print(f"K_REFERENCE {name} max_abs={maximum:.9g} max_rel={relative:.9g} "
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f"rms={rms:.9g} psnr_db={psnr:.5g} worst={mismatch} "
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f"expected={float(expected[mismatch]):.9g} actual={float(actual[mismatch]):.9g}")
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return maximum, psnr
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--fixture-dir", required=True, type=pathlib.Path)
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parser.add_argument("--kernel-name", choices=("enc1", "enc2"), default="enc1")
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args = parser.parse_args()
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folder = args.fixture_dir
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params = SyntheticParams(folder)
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output_channels = 96 if args.kernel_name == "enc2" else 64
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reference_full, reference_merged = pwin_encoder(
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params, 0, 0, H=2, C=64, COUT=output_channels,
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posattn=args.kernel_name == "enc1")
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actual_full = np.fromfile(folder / "full.bin", np.float16).reshape(64, 64)
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actual_merged = np.fromfile(folder / "merged.bin", np.float16).reshape(16, output_channels)
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full_abs, full_psnr = compare("full", actual_full, reference_full)
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merged_abs, merged_psnr = compare("merged", actual_merged, reference_merged)
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# Initial acceptance for the synthetic nonzero FP16 fixture. Tighten this
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# after each K stage has been compared on captured DLSS weights/activations.
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if full_abs > 0.001 or full_psnr < 60.0 or merged_abs > 0.001 or merged_psnr < 60.0:
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raise RuntimeError(f"K {args.kernel_name} numerical mismatch against pwin_model.py")
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print(f"PASS K_REFERENCE reference=logical kernel={args.kernel_name} "
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"nonzero_weights=1 transformer_executed=1 nan_inf=0")
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if __name__ == "__main__":
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try:
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main()
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except Exception as error:
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print(f"FAIL K_REFERENCE {error}", file=sys.stderr)
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raise SystemExit(5)
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