|
|
from __gin__ import dynamic_registration
|
|
|
import cached_conv as cc
|
|
|
from cached_conv import convs
|
|
|
import rave
|
|
|
from rave import blocks
|
|
|
from rave import core
|
|
|
from rave import dataset
|
|
|
from rave import descript_discriminator
|
|
|
from rave import discriminator
|
|
|
from rave import model
|
|
|
from rave import pqmf
|
|
|
import torch
|
|
|
import torch.nn as nn
|
|
|
|
|
|
# Macros:
|
|
|
# ==============================================================================
|
|
|
ACTIVATION = @blocks.Snake
|
|
|
CAPACITY = 96
|
|
|
DILATIONS = [[1, 3, 9], [1, 3, 9], [1, 3, 9], [1, 3]]
|
|
|
KERNEL_SIZE = 3
|
|
|
LATENT_SIZE = 128
|
|
|
N_BAND = 16
|
|
|
NOISE_AUGMENTATION = 0
|
|
|
PHASE_1_DURATION = 0
|
|
|
RATIOS = [4, 4, 4, 2]
|
|
|
SAMPLING_RATE = 48000
|
|
|
|
|
|
# Parameters for blocks.AdaptiveInstanceNormalization:
|
|
|
# ==============================================================================
|
|
|
# None.
|
|
|
|
|
|
# Parameters for variational/blocks.AdaptiveInstanceNormalization:
|
|
|
# ==============================================================================
|
|
|
# None.
|
|
|
|
|
|
# Parameters for core.AudioDistanceV1:
|
|
|
# ==============================================================================
|
|
|
core.AudioDistanceV1.log_epsilon = 1e-07
|
|
|
core.AudioDistanceV1.multiscale_stft = @core.MultiScaleSTFT
|
|
|
|
|
|
# Parameters for model.BetaWarmupCallback:
|
|
|
# ==============================================================================
|
|
|
model.BetaWarmupCallback.initial_value = 1e-06
|
|
|
model.BetaWarmupCallback.log = True
|
|
|
model.BetaWarmupCallback.target_value = 0.05
|
|
|
model.BetaWarmupCallback.warmup_len = 20000
|
|
|
|
|
|
# Parameters for pqmf.CachedPQMF:
|
|
|
# ==============================================================================
|
|
|
pqmf.CachedPQMF.attenuation = 100
|
|
|
pqmf.CachedPQMF.n_band = %N_BAND
|
|
|
|
|
|
# Parameters for cc.Conv1d:
|
|
|
# ==============================================================================
|
|
|
cc.Conv1d.bias = False
|
|
|
|
|
|
# Parameters for variational/cc.Conv1d:
|
|
|
# ==============================================================================
|
|
|
variational/cc.Conv1d.bias = False
|
|
|
|
|
|
# Parameters for cc.ConvTranspose1d:
|
|
|
# ==============================================================================
|
|
|
cc.ConvTranspose1d.bias = False
|
|
|
|
|
|
# Parameters for descript_discriminator.DescriptDiscriminator:
|
|
|
# ==============================================================================
|
|
|
descript_discriminator.DescriptDiscriminator.bands = \
|
|
|
[(0.0, 0.1), (0.1, 0.25), (0.25, 0.5), (0.5, 0.75), (0.75, 1.0)]
|
|
|
descript_discriminator.DescriptDiscriminator.fft_sizes = [2048, 1024, 512]
|
|
|
descript_discriminator.DescriptDiscriminator.periods = [2, 3, 5, 7, 11]
|
|
|
descript_discriminator.DescriptDiscriminator.rates = []
|
|
|
descript_discriminator.DescriptDiscriminator.sample_rate = 44100
|
|
|
|
|
|
# Parameters for variational/blocks.EncoderV2:
|
|
|
# ==============================================================================
|
|
|
variational/blocks.EncoderV2.activation = %ACTIVATION
|
|
|
variational/blocks.EncoderV2.adain = @blocks.AdaptiveInstanceNormalization
|
|
|
variational/blocks.EncoderV2.capacity = %CAPACITY
|
|
|
variational/blocks.EncoderV2.data_size = %N_BAND
|
|
|
variational/blocks.EncoderV2.dilations = %DILATIONS
|
|
|
variational/blocks.EncoderV2.group_resample = False
|
|
|
variational/blocks.EncoderV2.group_size = 65536
|
|
|
variational/blocks.EncoderV2.keep_dim = False
|
|
|
variational/blocks.EncoderV2.kernel_size = %KERNEL_SIZE
|
|
|
variational/blocks.EncoderV2.latent_size = %LATENT_SIZE
|
|
|
variational/blocks.EncoderV2.n_out = 2
|
|
|
variational/blocks.EncoderV2.ratios = %RATIOS
|
|
|
variational/blocks.EncoderV2.recurrent_layer = None
|
|
|
variational/blocks.EncoderV2.spectrogram = None
|
|
|
|
|
|
# Parameters for blocks.GeneratorV2:
|
|
|
# ==============================================================================
|
|
|
blocks.GeneratorV2.activation = %ACTIVATION
|
|
|
blocks.GeneratorV2.adain = @blocks.AdaptiveInstanceNormalization
|
|
|
blocks.GeneratorV2.amplitude_modulation = True
|
|
|
blocks.GeneratorV2.capacity = %CAPACITY
|
|
|
blocks.GeneratorV2.causal_convtranspose = True
|
|
|
blocks.GeneratorV2.data_size = %N_BAND
|
|
|
blocks.GeneratorV2.dilations = %DILATIONS
|
|
|
blocks.GeneratorV2.group_resample = False
|
|
|
blocks.GeneratorV2.group_size = 65536
|
|
|
blocks.GeneratorV2.keep_dim = False
|
|
|
blocks.GeneratorV2.kernel_size = %KERNEL_SIZE
|
|
|
blocks.GeneratorV2.latent_size = @core.get_augmented_latent_size()
|
|
|
blocks.GeneratorV2.noise_module = @blocks.NoiseGeneratorV2
|
|
|
blocks.GeneratorV2.ratios = %RATIOS
|
|
|
blocks.GeneratorV2.recurrent_layer = None
|
|
|
|
|
|
# Parameters for core.get_augmented_latent_size:
|
|
|
# ==============================================================================
|
|
|
core.get_augmented_latent_size.latent_size = %LATENT_SIZE
|
|
|
core.get_augmented_latent_size.noise_augmentation = %NOISE_AUGMENTATION
|
|
|
|
|
|
# Parameters for dataset.get_dataset:
|
|
|
# ==============================================================================
|
|
|
dataset.get_dataset.augmentations = []
|
|
|
|
|
|
# Parameters for convs.get_padding:
|
|
|
# ==============================================================================
|
|
|
convs.get_padding.dilation = 1
|
|
|
convs.get_padding.mode = 'causal'
|
|
|
convs.get_padding.stride = 1
|
|
|
|
|
|
# Parameters for variational/convs.get_padding:
|
|
|
# ==============================================================================
|
|
|
variational/convs.get_padding.dilation = 1
|
|
|
variational/convs.get_padding.mode = 'causal'
|
|
|
variational/convs.get_padding.stride = 1
|
|
|
|
|
|
# Parameters for core.MultiScaleSTFT:
|
|
|
# ==============================================================================
|
|
|
core.MultiScaleSTFT.magnitude = True
|
|
|
core.MultiScaleSTFT.normalized = False
|
|
|
core.MultiScaleSTFT.num_mels = None
|
|
|
core.MultiScaleSTFT.random_crop = False
|
|
|
core.MultiScaleSTFT.sample_rate = %SAMPLING_RATE
|
|
|
core.MultiScaleSTFT.scales = [2048, 1024, 512, 256, 128]
|
|
|
|
|
|
# Parameters for blocks.NoiseGeneratorV2:
|
|
|
# ==============================================================================
|
|
|
blocks.NoiseGeneratorV2.activation = %ACTIVATION
|
|
|
blocks.NoiseGeneratorV2.data_size = %N_BAND
|
|
|
blocks.NoiseGeneratorV2.hidden_size = 128
|
|
|
blocks.NoiseGeneratorV2.noise_bands = 5
|
|
|
blocks.NoiseGeneratorV2.ratios = [2, 2, 2]
|
|
|
|
|
|
# Parameters for blocks.normalization:
|
|
|
# ==============================================================================
|
|
|
blocks.normalization.mode = 'weight_norm'
|
|
|
|
|
|
# Parameters for variational/blocks.normalization:
|
|
|
# ==============================================================================
|
|
|
variational/blocks.normalization.mode = 'weight_norm'
|
|
|
|
|
|
# Parameters for model.RAVE:
|
|
|
# ==============================================================================
|
|
|
model.RAVE.audio_distance = @core.AudioDistanceV1
|
|
|
model.RAVE.audio_monitor_epochs = 1
|
|
|
model.RAVE.balancer = None
|
|
|
model.RAVE.decoder = @blocks.GeneratorV2
|
|
|
model.RAVE.discriminator = @descript_discriminator.DescriptDiscriminator
|
|
|
model.RAVE.enable_pqmf_decode = None
|
|
|
model.RAVE.enable_pqmf_encode = None
|
|
|
model.RAVE.encoder = @blocks.VariationalEncoder
|
|
|
model.RAVE.feature_matching_fun = @feature_matching/core.mean_difference
|
|
|
model.RAVE.freeze_encoder = False
|
|
|
model.RAVE.gan_loss = @core.hinge_gan
|
|
|
model.RAVE.input_mode = 'pqmf'
|
|
|
model.RAVE.is_mel_input = None
|
|
|
model.RAVE.latent_size = %LATENT_SIZE
|
|
|
model.RAVE.loss_weights = None
|
|
|
model.RAVE.multiband_audio_distance = @core.AudioDistanceV1
|
|
|
model.RAVE.n_bands = 16
|
|
|
model.RAVE.n_channels = 1
|
|
|
model.RAVE.num_skipped_features = 1
|
|
|
model.RAVE.output_mode = 'pqmf'
|
|
|
model.RAVE.phase_1_duration = %PHASE_1_DURATION
|
|
|
model.RAVE.pqmf = @pqmf.CachedPQMF
|
|
|
model.RAVE.sampling_rate = %SAMPLING_RATE
|
|
|
model.RAVE.spectrogram = None
|
|
|
model.RAVE.update_discriminator_every = 4
|
|
|
model.RAVE.valid_signal_crop = True
|
|
|
model.RAVE.warmup_quantize = None
|
|
|
model.RAVE.weights = {'feature_matching': 20}
|
|
|
|
|
|
# Parameters for blocks.Snake:
|
|
|
# ==============================================================================
|
|
|
# None.
|
|
|
|
|
|
# Parameters for variational/blocks.Snake:
|
|
|
# ==============================================================================
|
|
|
# None.
|
|
|
|
|
|
# Parameters for dataset.split_dataset:
|
|
|
# ==============================================================================
|
|
|
dataset.split_dataset.max_residual = 1000
|
|
|
|
|
|
# Parameters for blocks.VariationalEncoder:
|
|
|
# ==============================================================================
|
|
|
blocks.VariationalEncoder.beta = 1.0
|
|
|
blocks.VariationalEncoder.encoder = @variational/blocks.EncoderV2
|
|
|
|
