ayo
34e6b0fe71
Add an experimental FSR Ray Regeneration backend for D3D12 RR requests: - Convert depth, motion, normals and albedos into AMD denoiser inputs. - Split and recompose diffuse/specular signals, then run Super Sampling. - Add stability/detail controls, demodulation guards and halo limiting. - Handle AMD provider discovery under NVIDIA GPU spoofing. - Add runtime probes, synthetic reference scenes and per-dispatch profiling. Add exact gfx11 DLSS-RR inference using f16 cooperative matrices: - Reproduce FP8 conversions, accumulation and camera reprojection arithmetic. - Widen model weights and avoid requiring VK_EXT_shader_float8. - Extend model building, replay tools and descriptor metadata. Expand motion preprocessing and experimental AW2 native-motion support: - Add tiled LDS dilation, padded allocation handling and thin-only sky fill. - Order dilation with input waits and NGX on the selected stream. - Add jitter-aligned native composition, hybrid routing and wire history repair. - Add prepared masks, sparse repair and independent motion/repair controls. Add optional fused R11G11B10 input/output conversion, sampled stage timings and profile summarization. Extend configuration, packaging, documentation, FidelityFX headers and CPU/GPU regression coverage.
73 lines
3.0 KiB
Python
73 lines
3.0 KiB
Python
#!/usr/bin/env python3
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"""Summarize warm D4R_PROFILE samples without merging feature instances or sizes.
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GPU pass fields and delayed vk_* fields are summarized independently. Their
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per-line difference is deliberately not calculated; they describe different frames.
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"""
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import argparse
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from collections import defaultdict
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import json
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import math
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from pathlib import Path
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import re
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import statistics
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GROUP_FIELDS = ('render', 'output', 'preset', 'quality', 'flags', 'input_wait',
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'feature', 'native_field', 'native_substitute', 'wire_requested', 'gpu_completion', 'vk_output_mode', 'vk_input_mode')
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FIELDS = ('vk_total', 'dlss_gpu', 'vk_input', 'vk_dlss_wait', 'vk_output',
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'native_motion_gpu', 'wire_repair_gpu', 'marker_wait', 'pipeline',
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'throughput_interval')
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def summarize(text, min_frame=300, since_clock=None, until_clock=None):
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groups = defaultdict(list)
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instance = 0
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for line in text.splitlines():
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if 'NVSDK_NGX_D3D12_CreateFeature(feature=' in line:
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instance += 1
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if 'D4R_PROFILE frame=' not in line:
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continue
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if since_clock is not None or until_clock is not None:
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clock = re.search(r'^\[\s*([0-9.]+)\]', line)
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if clock is None:
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continue
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seconds = float(clock[1])
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if since_clock is not None and seconds < since_clock:
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continue
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if until_clock is not None and seconds > until_clock:
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continue
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values = dict(re.findall(r'(\w+)=([^\s]+)', line))
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if int(values['frame']) < min_frame or values.get('reset') != '0':
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continue
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key = (instance, *(values.get(k, 'unknown') for k in
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GROUP_FIELDS))
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groups[key].append(values)
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result = []
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for key, samples in groups.items():
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row = dict(zip(('feature_instance', *GROUP_FIELDS), key))
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row.update(samples=len(samples), first_frame=int(samples[0]['frame']), last_frame=int(samples[-1]['frame']))
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row['timings_ms'] = {}
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for field in FIELDS:
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values = [float(s.get(field, '-1')) for s in samples]
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valid = [v for v in values if math.isfinite(v) and v >= 0]
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row['timings_ms'][field] = (dict(n=len(valid), median=statistics.median(valid),
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min=min(valid), max=max(valid)) if valid else None)
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result.append(row)
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return result
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def main():
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument('log', type=Path)
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parser.add_argument('--min-frame', type=int, default=300)
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parser.add_argument('--since-clock', type=float, help='minimum bracketed log-clock seconds')
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parser.add_argument('--until-clock', type=float, help='maximum bracketed log-clock seconds')
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args = parser.parse_args()
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print(json.dumps(summarize(args.log.read_text(errors='replace'), args.min_frame,
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args.since_clock, args.until_clock), indent=2))
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if __name__ == '__main__':
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main()
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