ayo
7c5d3c9157
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.
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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