60 lines
4.4 KiB
Python
60 lines
4.4 KiB
Python
#!/usr/bin/env python3
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"""Run the engine's own preset M reconstruction (post_m.comp) on a captured launch and compare its outputs.
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usage: test_post_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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cap, frame, work, kvk = sys.argv[1], int(sys.argv[2]), sys.argv[3], sys.argv[4]
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# the kernel name can be overridden; post_3_2 (reconstruction/render < 3) needs the larger shared tile
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K = os.environ.get('POST_KERNEL') or next((k for k in ('rrlite_post_3_1_mvlo_hdr_folded', 'rrlite_post_3_2_mvlo_hdr_folded')
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if glob.glob(f'{cap}/replay/replay-*-{k}')), 'rrlite_post_3_1_mvlo_hdr_folded')
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TILE = ['-DTILE_W=15', '-DTILE_H=15'] if '3_2' in K else []
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# preset L's unfolded kernels (no _folded suffix) run post_m.comp's PRESET_L variant, one tap wider per tier
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if '_ldr' in K:
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TILE = TILE + ['-DLDR=1']
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if not K.endswith('_folded'):
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TILE = [d for d in TILE if d == '-DLDR=1'] + ['-DPRESET_L=1'] + (['-DTILE_W=16', '-DTILE_H=16'] if '3_2' in K else ['-DTILE_W=11', '-DTILE_H=11'])
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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 = lambda o: float(np.fromfile(res[o], np.float16)[0])
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hw, hh = i2(140); rw, rh = i2(148)
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open(f'{work}/params.bin', 'wb').write(struct.pack('<2i2i2i2f2f2ffIff', *i2(8), hw, hh, rw, rh, *f2(124), *f2(132), *f2(160),
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struct.unpack_from('<f', P, 120)[0], P[168], expo(16), expo(24)))
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def tex(binding, off, ch, bits, mode, w=rw, h=rh): return f'tex {binding} {res[off]} {w} {h} {ch} {bits} {mode}'
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lines = [f'param {work}/params.bin', f'grid {(hw + 15) // 16} {(hh + 15) // 16}',
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tex(1, 0, 4, 16, 'nearest'), tex(2, 40, 4, 8, 'nearest'), tex(3, 32, 4, 8, 'nearest'), tex(4, 48, 4, 16, 'nearest'),
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tex(5, 56, 4, 16, 'linear', hw, hh), tex(6, 64, 2, 16, 'nearest'), tex(7, 72, 2, 16, 'nearest'), tex(8, 80, 2, 16, 'linear'),
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f'surf 9 {hw} {hh} 4 16 - {work}/hist.bin', f'surf 10 {(hw + 1) // 2} {(hh + 1) // 2} 4 32 - {work}/half.bin',
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f'outbuf {work}/packed.bin {hw * hh * 4}']
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open(f'{work}/manifest', 'w').write('\n'.join(lines) + '\n')
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spv = f'{work}/post_m.spv'
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subprocess.run(['glslangValidator', '-V', '--target-env', 'vulkan1.3', *TILE, f'{HERE}/post_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[-600:]); 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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print(f'frame {frame} (launch {seq}) {K} {rw}x{rh} -> {hw}x{hh}, reset {P[168]}, exposure {expo(16):.4g} / {expo(24):.4g}')
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a = np.fromfile(res[96], np.float16).astype(np.float64); b = np.fromfile(f'{work}/hist.bin', np.float16).astype(np.float64)
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d = np.abs(a - b)
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print(f' new history psnr {10 * np.log10(np.abs(a).max() ** 2 / max((d ** 2).mean(), 1e-30)):5.1f} dB identical {100 * (np.fromfile(res[96], np.uint16) == np.fromfile(f"{work}/hist.bin", np.uint16)).mean():5.1f}% max |diff| {d.max():.4g}')
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def unpack(f):
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w = np.fromfile(f, np.uint32)
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return np.stack([w & 2047, (w >> 11) & 2047, w >> 22], -1).astype(np.float64)
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a, b = unpack(res[104]), unpack(f'{work}/packed.bin')
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d = np.abs(a - b)
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print(f' packed output identical {100 * (d == 0).mean():5.1f}% within one step {100 * (d <= 1).mean():5.1f}% psnr {10 * np.log10(2047.0 ** 2 / max((d ** 2).mean(), 1e-30)):5.1f} dB max step {int(d.max())}')
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if 112 in res: # the half-resolution output; the launch dumps do not always carry it
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codes = np.fromfile(res[112], np.uint32)
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a = np.stack([codes & 1023, (codes >> 10) & 1023, (codes >> 20) & 1023], -1).astype(np.float32) / np.float32(1023)
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b = np.fromfile(f'{work}/half.bin', np.float32).reshape(-1, 4)[:, :3]
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d = np.abs(a.astype(np.float64) - b)
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exact = a.view(np.uint32) == b.view(np.uint32)
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print(f' half output psnr {10 * np.log10(1.0 / max((d ** 2).mean(), 1e-30)):5.1f} dB identical {100 * exact.mean():5.1f}% max |diff| {d.max():.4g}')
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