Ethanfel
af6c225f53
New dataset pipeline nodes: - SelvaDatasetSpectralMatcher: batch spectral EQ toward VAE distribution - SelvaDatasetHfSmoother: batch HF attenuation for codec compatibility - SelvaDatasetAugmenter: gain/pitch/time-stretch variants with npz origin tracking Improvements: - Inspector: silence detection (max_silence_fraction param) - Saver: origin_name lookup for augmented clips' npz pairing - LoRA trainer: latent_mixup_alpha + latent_noise_sigma regularization - LoRA trainer: one-time SR mismatch warning in _load_audio Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
48 lines
4.5 KiB
Python
48 lines
4.5 KiB
Python
NODE_CLASS_MAPPINGS = {}
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NODE_DISPLAY_NAME_MAPPINGS = {}
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_NODES = {
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"SelvaModelLoader": (".selva_model_loader", "SelvaModelLoader", "SelVA Model Loader"),
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"SelvaFeatureExtractor": (".selva_feature_extractor", "SelvaFeatureExtractor", "SelVA Feature Extractor"),
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"SelvaSampler": (".selva_sampler", "SelvaSampler", "SelVA Sampler"),
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"SelvaLoraLoader": (".selva_lora_loader", "SelvaLoraLoader", "SelVA LoRA Loader"),
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"SelvaLoraTrainer": (".selva_lora_trainer", "SelvaLoraTrainer", "SelVA LoRA Trainer"),
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"SelvaLoraScheduler": (".selva_lora_scheduler", "SelvaLoraScheduler", "SelVA LoRA Scheduler"),
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"SelvaDatasetBrowser": (".selva_dataset_browser", "SelvaDatasetBrowser", "SelVA Dataset Browser"),
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"SelvaSkipExperiment": (".selva_skip_experiment", "SelvaSkipExperiment", "SelVA Skip Experiment"),
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"SelvaLoraEvaluator": (".selva_lora_evaluator", "SelvaLoraEvaluator", "SelVA LoRA Evaluator"),
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"SelvaVaeRoundtrip": (".selva_vae_roundtrip", "SelvaVaeRoundtrip", "SelVA VAE Roundtrip"),
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"SelvaHfSmoother": (".selva_audio_preprocessors", "SelvaHfSmoother", "SelVA HF Smoother"),
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"SelvaSpectralMatcher": (".selva_audio_preprocessors", "SelvaSpectralMatcher", "SelVA Spectral Matcher"),
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"SelvaTextualInversionTrainer": (".selva_textual_inversion_trainer", "SelvaTextualInversionTrainer", "SelVA Textual Inversion Trainer"),
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"SelvaTextualInversionLoader": (".selva_textual_inversion_loader", "SelvaTextualInversionLoader", "SelVA Textual Inversion Loader"),
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"SelvaTiScheduler": (".selva_ti_scheduler", "SelvaTiScheduler", "SelVA TI Scheduler"),
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"SelvaActivationSteeringExtractor": (".selva_activation_steering_extractor", "SelvaActivationSteeringExtractor", "SelVA Activation Steering Extractor"),
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"SelvaActivationSteeringLoader": (".selva_activation_steering_loader", "SelvaActivationSteeringLoader", "SelVA Activation Steering Loader"),
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"SelvaBigvganTrainer": (".selva_bigvgan_trainer", "SelvaBigvganTrainer", "SelVA BigVGAN Trainer"),
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"SelvaBigvganLoader": (".selva_bigvgan_loader", "SelvaBigvganLoader", "SelVA BigVGAN Loader"),
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"SelvaBigvganScheduler": (".selva_bigvgan_scheduler", "SelvaBigvganScheduler", "SelVA BigVGAN Scheduler"),
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"SelvaDittoOptimizer": (".selva_ditto_optimizer", "SelvaDittoOptimizer", "SelVA DITTO Optimizer"),
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"SelvaDatasetLoader": (".selva_dataset_pipeline", "SelvaDatasetLoader", "SelVA Dataset Loader"),
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"SelvaDatasetResampler": (".selva_dataset_pipeline", "SelvaDatasetResampler", "SelVA Dataset Resampler"),
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"SelvaDatasetLUFSNormalizer": (".selva_dataset_pipeline", "SelvaDatasetLUFSNormalizer", "SelVA Dataset LUFS Normalizer"),
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"SelvaDatasetCompressor": (".selva_dataset_pipeline", "SelvaDatasetCompressor", "SelVA Dataset Compressor"),
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"SelvaDatasetInspector": (".selva_dataset_pipeline", "SelvaDatasetInspector", "SelVA Dataset Inspector"),
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"SelvaDatasetItemExtractor": (".selva_dataset_pipeline", "SelvaDatasetItemExtractor", "SelVA Dataset Item Extractor"),
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"SelvaDatasetSaver": (".selva_dataset_pipeline", "SelvaDatasetSaver", "SelVA Dataset Saver"),
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"SelvaHarmonicExciter": (".selva_audio_postprocess", "SelvaHarmonicExciter", "SelVA Harmonic Exciter"),
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"SelvaOutputNormalizer": (".selva_audio_postprocess", "SelvaOutputNormalizer", "SelVA Output Normalizer"),
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"SelvaDatasetSpectralMatcher": (".selva_dataset_pipeline", "SelvaDatasetSpectralMatcher", "SelVA Dataset Spectral Matcher"),
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"SelvaDatasetHfSmoother": (".selva_dataset_pipeline", "SelvaDatasetHfSmoother", "SelVA Dataset HF Smoother"),
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"SelvaDatasetAugmenter": (".selva_dataset_pipeline", "SelvaDatasetAugmenter", "SelVA Dataset Augmenter"),
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}
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for key, (module_path, class_name, display_name) in _NODES.items():
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try:
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import importlib
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mod = importlib.import_module(module_path, package=__name__)
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NODE_CLASS_MAPPINGS[key] = getattr(mod, class_name)
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NODE_DISPLAY_NAME_MAPPINGS[key] = display_name
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except (ImportError, AttributeError) as e:
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print(f"[SelVA] Skipping {key}: {e}")
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