config/mb-melgan.v1.yaml [6:25]:
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dataset:
  batch_size: 64
  frames_per_clip: 64 # 16384
  clips_per_utterance: 10
  padding_frames: 0
  dataloader_num_workers: 4
  dataloader_prefetch_factor: 4
model:
  # Generator Config
  generator_type: "MelGANGenerator"
  generator_params:
    in_channels: 80               # Number of input channels.
    out_channels: 4               # Number of output channels.
    kernel_size: 7                # Kernel size of initial and final conv layers.
    channels: 384                 # Initial number of channels for conv layers.
    upsample_scales: [5, 5, 3] # List of Upsampling scales.
    stack_kernel_size: 3          # Kernel size of dilated conv layers in residual stack.
    stacks: 4                     # Number of stacks in a single residual stack module.
    use_weight_norm: True         # Whether to use weight normalization.
    use_causal_conv: False        # Whether to use causal convolution.
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config/mb-melgan.yaml [6:25]:
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dataset:
  batch_size: 64
  frames_per_clip: 64
  clips_per_utterance: 10
  padding_frames: 0
  dataloader_num_workers: 4
  dataloader_prefetch_factor: 4
model:
  # Generator Config
  generator_type: "MelGANGenerator"
  generator_params:
    in_channels: 80               # Number of input channels.
    out_channels: 4               # Number of output channels.
    kernel_size: 7                # Kernel size of initial and final conv layers.
    channels: 384                 # Initial number of channels for conv layers.
    upsample_scales: [5, 5, 3] # List of Upsampling scales.
    stack_kernel_size: 3          # Kernel size of dilated conv layers in residual stack.
    stacks: 4                     # Number of stacks in a single residual stack module.
    use_weight_norm: True         # Whether to use weight normalization.
    use_causal_conv: False        # Whether to use causal convolution.
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