PaddleSpeech/examples/csmsc/voc5/conf/finetune.yaml

# This is the configuration file for CSMSC dataset.
# This configuration is based on HiFiGAN V1, which is an official configuration. 
# But I found that the optimizer setting does not work well with my implementation.
# So I changed optimizer settings as follows:
# - AdamW -> Adam
# - betas: [0.8, 0.99] -> betas: [0.5, 0.9]
# - Scheduler: ExponentialLR -> MultiStepLR
# To match the shift size difference, the upsample scales is also modified from the original 256 shift setting.

###########################################################
#                FEATURE EXTRACTION SETTING               #
###########################################################
fs: 24000                # Sampling rate.
n_fft: 2048              # FFT size (samples).
n_shift: 300             # Hop size (samples). 12.5ms
win_length: 1200         # Window length (samples). 50ms
                         # If set to null, it will be the same as fft_size.
window: "hann"           # Window function.
n_mels: 80               # Number of mel basis.
fmin: 80                 # Minimum freq in mel basis calculation. (Hz)
fmax: 7600               # Maximum frequency in mel basis calculation. (Hz)

###########################################################
#         GENERATOR NETWORK ARCHITECTURE SETTING          #
###########################################################
generator_params:
    in_channels: 80                       # Number of input channels.
    out_channels: 1                       # Number of output channels.
    channels: 512                         # Number of initial channels.
    kernel_size: 7                        # Kernel size of initial and final conv layers.
    upsample_scales: [5, 5, 4, 3]         # Upsampling scales.
    upsample_kernel_sizes: [10, 10, 8, 6] # Kernel size for upsampling layers.
    resblock_kernel_sizes: [3, 7, 11]     # Kernel size for residual blocks.
    resblock_dilations:                   # Dilations for residual blocks.
        - [1, 3, 5]
        - [1, 3, 5]
        - [1, 3, 5]
    use_additional_convs: True            # Whether to use additional conv layer in residual blocks.
    bias: True                            # Whether to use bias parameter in conv.
    nonlinear_activation: "leakyrelu"     # Nonlinear activation type.
    nonlinear_activation_params:          # Nonlinear activation paramters.
        negative_slope: 0.1
    use_weight_norm: True                 # Whether to apply weight normalization.


###########################################################
#       DISCRIMINATOR NETWORK ARCHITECTURE SETTING        #
###########################################################
discriminator_params:
    scales: 3                              # Number of multi-scale discriminator.
    scale_downsample_pooling: "AvgPool1D"  # Pooling operation for scale discriminator.
    scale_downsample_pooling_params:
        kernel_size: 4                     # Pooling kernel size.
        stride: 2                          # Pooling stride.
        padding: 2                         # Padding size.
    scale_discriminator_params:
        in_channels: 1                     # Number of input channels.
        out_channels: 1                    # Number of output channels.
        kernel_sizes: [15, 41, 5, 3]       # List of kernel sizes.
        channels: 128                      # Initial number of channels.
        max_downsample_channels: 1024      # Maximum number of channels in downsampling conv layers.
        max_groups: 16                     # Maximum number of groups in downsampling conv layers.
        bias: True
        downsample_scales: [4, 4, 4, 4, 1] # Downsampling scales.
        nonlinear_activation: "leakyrelu"  # Nonlinear activation.
        nonlinear_activation_params:
            negative_slope: 0.1
    follow_official_norm: True             # Whether to follow the official norm setting.
    periods: [2, 3, 5, 7, 11]              # List of period for multi-period discriminator.
    period_discriminator_params:
        in_channels: 1                     # Number of input channels.
        out_channels: 1                    # Number of output channels.
        kernel_sizes: [5, 3]               # List of kernel sizes.
        channels: 32                       # Initial number of channels.
        downsample_scales: [3, 3, 3, 3, 1] # Downsampling scales.
        max_downsample_channels: 1024      # Maximum number of channels in downsampling conv layers.
        bias: True                         # Whether to use bias parameter in conv layer."
        nonlinear_activation: "leakyrelu"  # Nonlinear activation.
        nonlinear_activation_params:       # Nonlinear activation paramters.
            negative_slope: 0.1
        use_weight_norm: True              # Whether to apply weight normalization.
        use_spectral_norm: False           # Whether to apply spectral normalization.
    

###########################################################
#                   STFT LOSS SETTING                     #
###########################################################
use_stft_loss: False                 # Whether to use multi-resolution STFT loss.
use_mel_loss: True                   # Whether to use Mel-spectrogram loss.
mel_loss_params:
    fs: 24000
    fft_size: 2048
    hop_size: 300
    win_length: 1200
    window: "hann"
    num_mels: 80
    fmin: 0
    fmax: 12000
    log_base: null
generator_adv_loss_params:
    average_by_discriminators: False # Whether to average loss by #discriminators.
discriminator_adv_loss_params:
    average_by_discriminators: False # Whether to average loss by #discriminators.
use_feat_match_loss: True
feat_match_loss_params:
    average_by_discriminators: False # Whether to average loss by #discriminators.
    average_by_layers: False         # Whether to average loss by #layers in each discriminator.
    include_final_outputs: False     # Whether to include final outputs in feat match loss calculation.

###########################################################
#               ADVERSARIAL LOSS SETTING                  #
###########################################################
lambda_aux: 45.0       # Loss balancing coefficient for STFT loss.
lambda_adv: 1.0        # Loss balancing coefficient for adversarial loss.
lambda_feat_match: 2.0 # Loss balancing coefficient for feat match loss..

###########################################################
#                  DATA LOADER SETTING                    #
###########################################################
batch_size: 16              # Batch size.
batch_max_steps: 8400       # Length of each audio in batch. Make sure dividable by hop_size.
num_workers: 2              # Number of workers in DataLoader.

###########################################################
#             OPTIMIZER & SCHEDULER SETTING               #
###########################################################
generator_optimizer_params:
    beta1: 0.5
    beta2: 0.9
    weight_decay: 0.0                   # Generator's weight decay coefficient.
generator_scheduler_params:
    learning_rate: 2.0e-4               # Generator's learning rate.
    gamma: 0.5                          # Generator's scheduler gamma.
    milestones:                         # At each milestone, lr will be multiplied by gamma.
        - 200000
        - 400000
        - 600000
        - 800000
generator_grad_norm: -1                 # Generator's gradient norm.
discriminator_optimizer_params:
    beta1: 0.5
    beta2: 0.9
    weight_decay: 0.0                   # Discriminator's weight decay coefficient.
discriminator_scheduler_params:
    learning_rate: 2.0e-4               # Discriminator's learning rate.
    gamma: 0.5                          # Discriminator's scheduler gamma.
    milestones:                         # At each milestone, lr will be multiplied by gamma.
        - 200000
        - 400000
        - 600000
        - 800000    
discriminator_grad_norm: -1             # Discriminator's gradient norm.            

###########################################################
#                    INTERVAL SETTING                     #
###########################################################
generator_train_start_steps: 1     # Number of steps to start to train discriminator.
discriminator_train_start_steps: 0 # Number of steps to start to train discriminator.
train_max_steps: 2500000           # Number of training steps.
save_interval_steps: 10000         # Interval steps to save checkpoint.
eval_interval_steps: 1000          # Interval steps to evaluate the network.
log_interval_steps: 100            # Interval steps to record the training log.

###########################################################
#                     OTHER SETTING                       #
###########################################################
num_snapshots: 10                 # max number of snapshots to keep while training
seed: 42                          # random seed for paddle, random, and np.random