woutermans
e0d1549a21
A standalone Vulkan inference engine (engine/) for DLSS presets K and M that runs from weights extracted from the user's own nvngx_dlss.dll, with d4r's own input, network and reconstruction shaders or the native HIP network layers, recorded into the game's command list by the shim. Opt-in ([Engine] Enabled / D4R_ENGINE=1); anything uncovered falls back to the CUDA/ZLUDA path with the reason logged. Byte-identical to NGX's CUDA backend under the phase-capable reference (1706x960 -> 2560x1440, native HIP network, eleven frames, RX 9070 XT): - K render- and display-resolution motion vectors, HDR and LDR - K game-supplied exposure and automatic exposure with any pre-exposure and exposure scale (one residual: effective exposure exactly 2 or 4) - K and M with the DLSS indicator's inverted-axis parameters - M with any exposure settings (NGX ignores them for M) K packages need the current compile_k.py (marker D4RO0003). Also: HIP shared buffers are pooled across feature recreation (ROCm leaks destroyed imports), hipnet.bin must match the preset, M-only games do not load the K model, install_d4r_runtime.sh stages k, k-ldr, m, m-ldr with hip/, the activation table has a generator (gen_activation_m.py), and package_release.sh can bundle the engine's shaders (never its weights). Signed-off-by: woutermans <[email protected]>
35 lines
2.3 KiB
Python
35 lines
2.3 KiB
Python
#!/usr/bin/env python3
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"""Run the engine's own preset M downsample stage (down_m.comp) on a captured launch and compare the output.
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usage: test_down_m.py CAPTURE_DIR FRAME WORK_DIR KVK [repeats]
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"""
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import glob, os, re, struct, subprocess, sys
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import numpy as np
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K = 'rrlite_downsample_kernel_static_hdr'
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cap, frame, work, kvk = sys.argv[1], int(sys.argv[2]), sys.argv[3], sys.argv[4]
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reps = sys.argv[5] if len(sys.argv) > 5 else '1'
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HERE = os.path.dirname(os.path.abspath(__file__))
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os.makedirs(work, exist_ok=True)
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seq = sorted({int(re.match(r'launch-(\d+)-', os.path.basename(f)).group(1)) for f in glob.glob(f'{cap}/dump/launch-*-{K}-arg*')})[frame]
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res = {int(re.search(r'-arg(\d+)-', f).group(1)): f for f in glob.glob(f'{cap}/dump/launch-{seq:03d}-{K}-arg*')}
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P = open(f'{cap}/replay/replay-{seq:06d}-{K}/args.bin', 'rb').read()
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i2 = lambda o: struct.unpack_from('<2i', P, o); f2 = lambda o: struct.unpack_from('<2f', P, o)
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expo = float(np.fromfile(res[48], np.float16)[0])
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open(f'{work}/params.bin', 'wb').write(struct.pack('<8i4ff', *i2(0), *i2(40), *i2(64), *i2(72), *f2(80), *f2(88), expo))
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dims = lambda f: [int(x) for x in re.search(r'-(\d+x\d+x\d+)-fmt', f).group(1).split('x')]
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cw, ch, cc = dims(res[56]); ow, oh, oc = dims(res[32])
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open(f'{work}/manifest', 'w').write('\n'.join([
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f'param {work}/params.bin', f'grid {(ow + 7) // 8} {(oh + 63) // 64}', f'tex 1 {res[56]} {cw} {ch} {cc} 16 nearest',
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f'surf 2 {ow} {oh} 4 16 - {work}/out.bin', f'lut {res[24]}']) + '\n')
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spv = f'{work}/down_m.spv'
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subprocess.run(['glslangValidator', '-V', '--target-env', 'vulkan1.3', f'{HERE}/down_m.comp', '-o', spv], check=True, stdout=subprocess.DEVNULL)
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r = subprocess.run([kvk, spv, f'{work}/manifest', reps, '64'], capture_output=True, text=True)
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if r.returncode:
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print('FAILED', r.stderr[-400:]); sys.exit(1)
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for l in r.stdout.split('\n'):
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if 'us per' in l: print(l)
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a = np.fromfile(res[32], np.float16).astype(np.float64); b = np.fromfile(f'{work}/out.bin', np.float16).astype(np.float64)
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d = np.abs(a - b)
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print(f'frame {frame} (launch {seq}) {ow}x{oh}: psnr {10 * np.log10(np.abs(a).max() ** 2 / max((d ** 2).mean(), 1e-30)):.1f} dB, '
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f'identical {100 * (np.fromfile(res[32], np.uint16) == np.fromfile(f"{work}/out.bin", np.uint16)).mean():.1f}%, max |diff| {d.max():.4g}')
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