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27.7 kB
| { | |
| "code_state_sha256": "e06dd72f96b63b2c8724fd27e49c364bc908d88dcc9f7fa488107bdba6b77267", | |
| "completed_at": "2026-08-13T06:20:19.561952+00:00", | |
| "config": { | |
| "dataset_root": "/home/kadir/kadir_projects/github/VyvoUp/datasets/vctk-pcm-10h", | |
| "example_count": 4, | |
| "fft_sizes": [ | |
| 256, | |
| 512, | |
| 1024 | |
| ], | |
| "flashsr_checkpoint": "/home/kadir/kadir_projects/github/VyvoUp/.model-sources/flashsr/FastAudioSR/SR48k.pth", | |
| "flashsr_command": [ | |
| ".model-envs/flashsr/bin/python", | |
| "-m", | |
| "audio_upscaler.comparison.flashsr_worker" | |
| ], | |
| "flashsr_implementation_revision": "2a69326250613c0a0f6c1c8d9f0c48cb779842b8", | |
| "flashsr_model_id": "YatharthS/FlashSR", | |
| "flashsr_model_revision": "3e19cc92e655c2e0661e6268efdade60f42fd0b8", | |
| "flashsr_repository": "https://github.com/ysharma3501/FlashSR", | |
| "maximum_items": 0, | |
| "output_root": "/home/kadir/kadir_projects/github/VyvoUp/artifacts/comparisons/vyvoup-final-vs-flashsr-v2", | |
| "schema_version": 1, | |
| "seed": 20260813, | |
| "split": "test", | |
| "vyvoup_checkpoint": "/home/kadir/kadir_projects/github/VyvoUp/artifacts/efficient-hbr-validation-soup-v4/checkpoints/step-00000300.pt", | |
| "working_directory": "/home/kadir/kadir_projects/github/VyvoUp" | |
| }, | |
| "config_sha256": "8b0b3765dd4509ae03fcba132d5b7e1504583860f6d65dbbca244f6c9d61cbc8", | |
| "dataset": { | |
| "duration_seconds": 1803.001625, | |
| "generation_sha256": "fd8064558142ae4d45f109227cc837e9c21a61908309112122cfa79ba267f77c", | |
| "held_out_speakers": true, | |
| "items": 527, | |
| "prior_use_disclosure": "This VCTK test split was previously evaluated for VyvoUp v1; the comparison is descriptive and is not used to tune v2.", | |
| "root": "/home/kadir/kadir_projects/github/VyvoUp/datasets/vctk-pcm-10h", | |
| "split": "test" | |
| }, | |
| "examples": [ | |
| { | |
| "directory": "examples/01-p260_062_mic1", | |
| "id": "p260_062_mic1", | |
| "sha256": { | |
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| "id": "p347_025_mic1", | |
| "sha256": { | |
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| }, | |
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| "directory": "examples/03-p280_127_mic1", | |
| "id": "p280_127_mic1", | |
| "sha256": { | |
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| { | |
| "directory": "examples/04-p276_418_mic1", | |
| "id": "p276_418_mic1", | |
| "sha256": { | |
| "flashsr_48khz.wav": "b14b3b63d5299182d65026871db000f24072c6249fa52e572c4e14a68e349791", | |
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| ], | |
| "format_version": 1, | |
| "implementation_caveats": [ | |
| "FlashSR accepts 16 kHz while VyvoUp accepts 24 kHz, so native inputs carry different information.", | |
| "The official FlashSR FASR.run wrapper peak-normalizes every output to 0.999.", | |
| "FlashSR's linked repository describes a tiny HiFi-GAN/HierSpeech++-style upsampler, not the diffusion FlashSR paper implementation.", | |
| "The compared official FlashSR PyTorch graph uses same-padded noncausal convolutions. Its repository also provides a distinct ONNX streaming wrapper, which is outside this quality comparison.", | |
| "Objective spectral distance does not replace blinded listening tests.", | |
| "Both RTF measurements include host-to-device input transfer and device-to-host output transfer; model loading and one real-input warm-up are excluded." | |
| ], | |
| "models": { | |
| "flashsr": { | |
| "active_forward_parameter_count": 88128, | |
| "architecture": { | |
| "activation": "anti-aliased SnakeBeta", | |
| "active_residual_blocks": [ | |
| 0, | |
| 2 | |
| ], | |
| "causality": "noncausal same-padded convolutions", | |
| "constructed_but_inactive_residual_blocks": [ | |
| 1 | |
| ], | |
| "initial_channels": 32, | |
| "input_sample_rate_hz": 16000, | |
| "output_sample_rate_hz": 48000, | |
| "residual_block_kernel_sizes": [ | |
| 3, | |
| 11 | |
| ], | |
| "upsampling": "3x linear interpolation" | |
| }, | |
| "checkpoint": { | |
| "bytes": 1715101, | |
| "path": "/home/kadir/kadir_projects/github/VyvoUp/.model-sources/flashsr/FastAudioSR/SR48k.pth", | |
| "sha256": "62c70874ac4efeb4dc9c8aa9dc0a611a951e1c36292abeb4c406d7fb91e0eefc" | |
| }, | |
| "checkpoint_tensor_elements": 132360, | |
| "cuda": "12.8", | |
| "cuda_peak_allocated_bytes": 415837184, | |
| "device": "cuda:0", | |
| "device_name": "NVIDIA GeForce RTX 5070 Ti", | |
| "format_version": 1, | |
| "implementation": "official FastAudioSR.FASR.run", | |
| "implementation_revision": "2a69326250613c0a0f6c1c8d9f0c48cb779842b8", | |
| "license": "Apache-2.0 (repository README and Hugging Face metadata)", | |
| "model_id": "YatharthS/FlashSR", | |
| "model_load_seconds": 0.1684477689996129, | |
| "model_revision": "3e19cc92e655c2e0661e6268efdade60f42fd0b8", | |
| "official_per_clip_peak_normalization": true, | |
| "parameter_count": 131904, | |
| "precision": "float16", | |
| "process_peak_rss_bytes": 1496055808, | |
| "repository": "https://github.com/ysharma3501/FlashSR", | |
| "restricted_checkpoint_loading": true, | |
| "runtime_boundary": "CPU tensor -> official GPU FASR.run including peak normalization -> CPU tensor", | |
| "torch": "2.11.0+cu128", | |
| "warmup_policy": "first real input once, excluded, then repeated and measured" | |
| }, | |
| "vyvoup": { | |
| "checkpoint": "/home/kadir/kadir_projects/github/VyvoUp/artifacts/efficient-hbr-validation-soup-v4/checkpoints/step-00000300.pt", | |
| "checkpoint_sha256": "133a1d019d05c9a146f3ea618b868021268a58842f09841f85f900e5b05774c7", | |
| "cuda_peak_allocated_bytes": 1013220352, | |
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| "precision": "bfloat16", | |
| "profile": { | |
| "algorithmic_delay_ms": 6.416666666666667, | |
| "algorithmic_delay_output_samples": 308, | |
| "architecture": "EfficientHBR", | |
| "estimated_macs_per_second": 801288000, | |
| "parameter_bytes_fp32": 128448, | |
| "receptive_field_input_samples": 2059, | |
| "receptive_field_ms": 85.79166666666667, | |
| "streaming_state_bytes_fp32": 398932, | |
| "total_parameters": 32112, | |
| "trainable_parameters": 32112 | |
| }, | |
| "runtime_boundary": "CPU tensor -> GPU inference -> aligned FP32 CPU waveform" | |
| } | |
| }, | |
| "objective_result": { | |
| "equal_information_rms_gain_aligned_shared_12_24khz_lsd_margin_db": 3.204423308883298, | |
| "equal_information_rms_gain_aligned_shared_12_24khz_lsd_winner": "vyvoup", | |
| "equal_information_shared_12_24khz_lsd_margin_db": 1.9116385290224152, | |
| "equal_information_shared_12_24khz_lsd_winner": "vyvoup", | |
| "lower_lsd_is_better": true, | |
| "native_rms_gain_aligned_shared_12_24khz_lsd_margin_db": 4.669459507806819, | |
| "native_rms_gain_aligned_shared_12_24khz_lsd_winner": "vyvoup", | |
| "native_shared_12_24khz_lsd_margin_db": 3.3886021022637856, | |
| "native_shared_12_24khz_lsd_winner": "vyvoup", | |
| "raw_metrics_follow_each_official_wrapper": true, | |
| "rms_gain_aligned_metrics_are_diagnostic": true | |
| }, | |
| "protocols": { | |
| "equal_information": { | |
| "common_observation": "48 kHz target -> deterministic 16 kHz Kaiser", | |
| "flashsr_adapter": "none", | |
| "missing_band_hz": [ | |
| 8000, | |
| 24000 | |
| ], | |
| "shared_metric_band_hz": [ | |
| 12000, | |
| 24000 | |
| ], | |
| "vyvoup_adapter": "deterministic 16->24 kHz Kaiser interpolation only" | |
| }, | |
| "native": { | |
| "flashsr_observation": "same target -> deterministic 16 kHz Kaiser", | |
| "native_missing_bands_hz": { | |
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| "shared_metric_band_hz": [ | |
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| "vyvoup_observation": "48 kHz target -> deterministic 24 kHz Kaiser" | |
| }, | |
| "resampling": "scipy.signal.resample_poly, Kaiser beta 12, zero padded", | |
| "target_alignment": "tail cropped to a multiple of six 48 kHz samples" | |
| }, | |
| "runtime_summary": { | |
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| "scope": "objective reconstruction and runtime; no subjective listening claim", | |
| "summary": { | |
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