File size: 4,686 Bytes
fddf1eb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
# This is the hyperparameter configuration file for MelGAN.
# Please make sure this is adjusted for the LJSpeech dataset. If you want to
# apply to the other dataset, you might need to carefully change some parameters.
# This configuration performs 4000k iters.
###########################################################
# FEATURE EXTRACTION SETTING #
###########################################################
sampling_rate: 22050 # Sampling rate of dataset.
hop_size: 256 # Hop size.
format: "npy"
###########################################################
# GENERATOR NETWORK ARCHITECTURE SETTING #
###########################################################
model_type: "melgan_generator"
melgan_generator_params:
out_channels: 1 # Number of output channels.
kernel_size: 7 # Kernel size of initial and final conv layers.
filters: 512 # Initial number of channels for conv layers.
upsample_scales: [8, 8, 2, 2] # List of Upsampling scales.
stack_kernel_size: 3 # Kernel size of dilated conv layers in residual stack.
stacks: 3 # Number of stacks in a single residual stack module.
is_weight_norm: false # Use weight-norm or not.
###########################################################
# DISCRIMINATOR NETWORK ARCHITECTURE SETTING #
###########################################################
melgan_discriminator_params:
out_channels: 1 # Number of output channels.
scales: 3 # Number of multi-scales.
downsample_pooling: "AveragePooling1D" # Pooling type for the input downsampling.
downsample_pooling_params: # Parameters of the above pooling function.
pool_size: 4
strides: 2
kernel_sizes: [5, 3] # List of kernel size.
filters: 16 # Number of channels of the initial conv layer.
max_downsample_filters: 1024 # Maximum number of channels of downsampling layers.
downsample_scales: [4, 4, 4, 4] # List of downsampling scales.
nonlinear_activation: "LeakyReLU" # Nonlinear activation function.
nonlinear_activation_params: # Parameters of nonlinear activation function.
alpha: 0.2
is_weight_norm: false # Use weight-norm or not.
###########################################################
# ADVERSARIAL LOSS SETTING #
###########################################################
lambda_feat_match: 10.0
###########################################################
# DATA LOADER SETTING #
###########################################################
batch_size: 16 # Batch size for each GPU with assuming that gradient_accumulation_steps == 1.
batch_max_steps: 8192 # Length of each audio in batch for training. Make sure dividable by hop_size.
batch_max_steps_valid: 81920 # Length of each audio for validation. Make sure dividable by hope_size.
remove_short_samples: true # Whether to remove samples the length of which are less than batch_max_steps.
allow_cache: true # Whether to allow cache in dataset. If true, it requires cpu memory.
is_shuffle: true # shuffle dataset after each epoch.
###########################################################
# OPTIMIZER & SCHEDULER SETTING #
###########################################################
generator_optimizer_params:
lr: 0.0001 # Generator's learning rate.
beta_1: 0.5
beta_2: 0.9
discriminator_optimizer_params:
lr: 0.0001 # Discriminator's learning rate.
beta_1: 0.5
beta_2: 0.9
gradient_accumulation_steps: 1
###########################################################
# INTERVAL SETTING #
###########################################################
train_max_steps: 4000000 # Number of training steps.
save_interval_steps: 3 # Interval steps to save checkpoint.
eval_interval_steps: 2 # Interval steps to evaluate the network.
log_interval_steps: 1 # Interval steps to record the training log.
discriminator_train_start_steps: 0 # step to start training discriminator.
###########################################################
# OTHER SETTING #
###########################################################
num_save_intermediate_results: 1 # Number of batch to be saved as intermediate results.
|