no-op-ul-se
commited on
Commit
•
cf618e5
1
Parent(s):
59ba853
add multivoice checkpoint+streaming
Browse files- README.md +7 -1
- checkpoints/voice_multi_b2048_r48000/config.gin +197 -0
- checkpoints/voice_multi_b2048_r48000/version_0/checkpoints/last.ckpt +3 -0
- checkpoints/voice_multi_b2048_r48000/version_0/events.out.tfevents.1713292613.honest-annie.1422133.0 +3 -0
- checkpoints/voice_multi_b2048_r48000/version_0/hparams.yaml +1 -0
- voice-multi-b2048-r48000-z11.ts +3 -0
README.md
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@@ -77,12 +77,18 @@ Dataset: [Hi-Fi TTS](https://www.openslr.org/109/) speaker 9017 (John Van Stan).
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Model: RAVE v3, 44.1kHz, block size 2048, 16 latent dimensions.
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-
###
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Dataset: [CSTR VCTK Corpus](https://datashare.ed.ac.uk/handle/10283/3443) multispeaker read speech dataset.
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Model: RAVE v3, 44.1kHz, block size 2048, 22 latent dimensions.
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## Birds
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### birds_motherbird_b2048_r48000_z16.ts
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Model: RAVE v3, 44.1kHz, block size 2048, 16 latent dimensions.
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### voice_vctk_b2048_r44100_z22.ts
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Dataset: [CSTR VCTK Corpus](https://datashare.ed.ac.uk/handle/10283/3443) multispeaker read speech dataset.
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Model: RAVE v3, 44.1kHz, block size 2048, 22 latent dimensions.
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### voice_multivoice_b2048_r48000_z11.ts
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Dataset: combination of speaking and singing voice datasets: [CSTR VCTK Corpus](https://datashare.ed.ac.uk/handle/10283/3443), [VocalSet](https://zenodo.org/record/1193957), [Children's Song Dataset](https://zenodo.org/records/4785016), [NUS-48E](https://ieeexplore.ieee.org/document/6694316/), [attHACK](https://arxiv.org/abs/2004.04410).
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Model: RAVE v3 with spectral discriminator, 48kHz, block size 2048, 11 latent dimensions.
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## Birds
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### birds_motherbird_b2048_r48000_z16.ts
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checkpoints/voice_multi_b2048_r48000/config.gin
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from __gin__ import dynamic_registration
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import cached_conv as cc
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from cached_conv import convs
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import rave
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from rave import blocks
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from rave import core
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from rave import dataset
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from rave import descript_discriminator
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from rave import discriminator
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from rave import model
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from rave import pqmf
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import torch
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import torch.nn as nn
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# Macros:
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# ==============================================================================
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ACTIVATION = @blocks.Snake
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CAPACITY = 96
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DILATIONS = [[1, 3, 9], [1, 3, 9], [1, 3, 9], [1, 3]]
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KERNEL_SIZE = 3
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LATENT_SIZE = 128
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N_BAND = 16
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NOISE_AUGMENTATION = 0
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PHASE_1_DURATION = 50000
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RATIOS = [4, 4, 4, 2]
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SAMPLING_RATE = 48000
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# Parameters for blocks.AdaptiveInstanceNormalization:
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# ==============================================================================
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# None.
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# Parameters for variational/blocks.AdaptiveInstanceNormalization:
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# ==============================================================================
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# None.
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# Parameters for core.AudioDistanceV1:
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# ==============================================================================
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core.AudioDistanceV1.log_epsilon = 1e-07
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core.AudioDistanceV1.multiscale_stft = @core.MultiScaleSTFT
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# Parameters for model.BetaWarmupCallback:
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# ==============================================================================
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model.BetaWarmupCallback.initial_value = 1e-06
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model.BetaWarmupCallback.log = True
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model.BetaWarmupCallback.target_value = 0.002
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model.BetaWarmupCallback.warmup_len = 20000
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# Parameters for pqmf.CachedPQMF:
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# ==============================================================================
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pqmf.CachedPQMF.attenuation = 100
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pqmf.CachedPQMF.n_band = %N_BAND
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# Parameters for cc.Conv1d:
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# ==============================================================================
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cc.Conv1d.bias = False
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# Parameters for variational/cc.Conv1d:
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# ==============================================================================
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variational/cc.Conv1d.bias = False
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# Parameters for cc.ConvTranspose1d:
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# ==============================================================================
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cc.ConvTranspose1d.bias = False
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# Parameters for descript_discriminator.DescriptDiscriminator:
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# ==============================================================================
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descript_discriminator.DescriptDiscriminator.bands = \
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[(0.0, 0.1), (0.1, 0.25), (0.25, 0.5), (0.5, 0.75), (0.75, 1.0)]
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descript_discriminator.DescriptDiscriminator.fft_sizes = [2048, 1024, 512]
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descript_discriminator.DescriptDiscriminator.periods = [2, 3, 5, 7, 11]
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descript_discriminator.DescriptDiscriminator.rates = []
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descript_discriminator.DescriptDiscriminator.sample_rate = 44100
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# Parameters for variational/blocks.EncoderV2:
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# ==============================================================================
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variational/blocks.EncoderV2.activation = %ACTIVATION
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variational/blocks.EncoderV2.adain = @blocks.AdaptiveInstanceNormalization
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variational/blocks.EncoderV2.capacity = %CAPACITY
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variational/blocks.EncoderV2.data_size = %N_BAND
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variational/blocks.EncoderV2.dilations = %DILATIONS
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variational/blocks.EncoderV2.keep_dim = False
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variational/blocks.EncoderV2.kernel_size = %KERNEL_SIZE
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variational/blocks.EncoderV2.latent_size = %LATENT_SIZE
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variational/blocks.EncoderV2.n_out = 2
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variational/blocks.EncoderV2.ratios = %RATIOS
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variational/blocks.EncoderV2.recurrent_layer = None
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variational/blocks.EncoderV2.spectrogram = None
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# Parameters for blocks.GeneratorV2:
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# ==============================================================================
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blocks.GeneratorV2.activation = %ACTIVATION
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blocks.GeneratorV2.adain = @blocks.AdaptiveInstanceNormalization
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blocks.GeneratorV2.amplitude_modulation = True
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blocks.GeneratorV2.capacity = %CAPACITY
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blocks.GeneratorV2.causal_convtranspose = True
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blocks.GeneratorV2.data_size = %N_BAND
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blocks.GeneratorV2.dilations = %DILATIONS
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blocks.GeneratorV2.keep_dim = False
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blocks.GeneratorV2.kernel_size = %KERNEL_SIZE
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blocks.GeneratorV2.latent_size = @core.get_augmented_latent_size()
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blocks.GeneratorV2.noise_module = @blocks.NoiseGeneratorV2
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blocks.GeneratorV2.ratios = %RATIOS
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blocks.GeneratorV2.recurrent_layer = None
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# Parameters for core.get_augmented_latent_size:
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# ==============================================================================
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core.get_augmented_latent_size.latent_size = %LATENT_SIZE
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core.get_augmented_latent_size.noise_augmentation = %NOISE_AUGMENTATION
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# Parameters for dataset.get_dataset:
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# ==============================================================================
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dataset.get_dataset.augmentations = []
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# Parameters for convs.get_padding:
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# ==============================================================================
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convs.get_padding.dilation = 1
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convs.get_padding.mode = 'causal'
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convs.get_padding.stride = 1
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# Parameters for variational/convs.get_padding:
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# ==============================================================================
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variational/convs.get_padding.dilation = 1
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variational/convs.get_padding.mode = 'causal'
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variational/convs.get_padding.stride = 1
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# Parameters for core.MultiScaleSTFT:
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# ==============================================================================
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core.MultiScaleSTFT.magnitude = True
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core.MultiScaleSTFT.normalized = False
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core.MultiScaleSTFT.num_mels = None
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core.MultiScaleSTFT.random_crop = False
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core.MultiScaleSTFT.sample_rate = %SAMPLING_RATE
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core.MultiScaleSTFT.scales = [2048, 1024, 512, 256, 128]
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# Parameters for blocks.NoiseGeneratorV2:
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# ==============================================================================
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blocks.NoiseGeneratorV2.activation = %ACTIVATION
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blocks.NoiseGeneratorV2.data_size = %N_BAND
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blocks.NoiseGeneratorV2.hidden_size = 128
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blocks.NoiseGeneratorV2.noise_bands = 5
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blocks.NoiseGeneratorV2.ratios = [2, 2, 2]
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# Parameters for blocks.normalization:
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# ==============================================================================
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blocks.normalization.mode = 'weight_norm'
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# Parameters for variational/blocks.normalization:
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# ==============================================================================
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variational/blocks.normalization.mode = 'weight_norm'
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# Parameters for model.RAVE:
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# ==============================================================================
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model.RAVE.audio_distance = @core.AudioDistanceV1
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model.RAVE.audio_monitor_epochs = 1
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model.RAVE.balancer = None
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model.RAVE.decoder = @blocks.GeneratorV2
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model.RAVE.discriminator = @descript_discriminator.DescriptDiscriminator
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model.RAVE.enable_pqmf_decode = None
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model.RAVE.enable_pqmf_encode = None
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model.RAVE.encoder = @blocks.VariationalEncoder
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model.RAVE.feature_matching_fun = @feature_matching/core.mean_difference
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model.RAVE.freeze_encoder = True
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model.RAVE.gan_loss = @core.hinge_gan
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model.RAVE.input_mode = 'pqmf'
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model.RAVE.is_mel_input = None
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model.RAVE.latent_size = %LATENT_SIZE
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model.RAVE.loss_weights = None
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model.RAVE.multiband_audio_distance = @core.AudioDistanceV1
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model.RAVE.n_bands = 16
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model.RAVE.n_channels = 1
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model.RAVE.num_skipped_features = 1
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model.RAVE.output_mode = 'pqmf'
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model.RAVE.phase_1_duration = %PHASE_1_DURATION
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model.RAVE.pqmf = @pqmf.CachedPQMF
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model.RAVE.sampling_rate = %SAMPLING_RATE
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model.RAVE.spectrogram = None
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model.RAVE.update_discriminator_every = 4
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model.RAVE.valid_signal_crop = True
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model.RAVE.warmup_quantize = None
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model.RAVE.weights = {'feature_matching': 20}
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# Parameters for blocks.Snake:
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# ==============================================================================
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# None.
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# Parameters for variational/blocks.Snake:
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# ==============================================================================
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# None.
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# Parameters for dataset.split_dataset:
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# ==============================================================================
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dataset.split_dataset.max_residual = 1000
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# Parameters for blocks.VariationalEncoder:
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# ==============================================================================
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blocks.VariationalEncoder.beta = 1.0
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blocks.VariationalEncoder.encoder = @variational/blocks.EncoderV2
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checkpoints/voice_multi_b2048_r48000/version_0/checkpoints/last.ckpt
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version https://git-lfs.github.com/spec/v1
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oid sha256:a02d2d61e58dfad6c30f476a7c2e7396e0285a6fbf890dcf135dfbadb28b36c7
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size 898749315
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checkpoints/voice_multi_b2048_r48000/version_0/events.out.tfevents.1713292613.honest-annie.1422133.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:0a61cfcc0020dfe3f8b41ee4349c4d31759d5efbd2de9c8d80f7bd68364531f2
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size 623605058
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checkpoints/voice_multi_b2048_r48000/version_0/hparams.yaml
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{}
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voice-multi-b2048-r48000-z11.ts
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version https://git-lfs.github.com/spec/v1
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oid sha256:5a1b28220e41a9148147286ea80f7286c8c249862639ba985f776492d4631845
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size 150205512
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