espnet2.gan_tts.parallel_wavegan.upsample.ConvInUpsampleNetwork

source

class espnet2.gan_tts.parallel_wavegan.upsample.ConvInUpsampleNetwork(upsample_scales: List[int], nonlinear_activation: str | None = None, nonlinear_activation_params: Dict[str, Any] = {}, interpolate_mode: str = 'nearest', freq_axis_kernel_size: int = 1, aux_channels: int = 80, aux_context_window: int = 0)

Bases: Module

Convolution + upsampling network module.

Initialize ConvInUpsampleNetwork module.

• Parameters:
  • upsample_scales (list) – List of upsampling scales.
  • nonlinear_activation (Optional *[*str ]) – Activation function name.
  • nonlinear_activation_params (Dict *[*str , Any ]) – Arguments for the specified activation function.
  • mode (str) – Interpolation mode.
  • freq_axis_kernel_size (int) – Kernel size in the direction of frequency axis.
  • aux_channels (int) – Number of channels of pre-conv layer.
  • aux_context_window (int) – Context window size of the pre-conv layer.

forward(c: Tensor) → Tensor

Calculate forward propagation.

• Parameters:c (Tensor) – Input tensor (B, C, T_feats).
• Returns: Upsampled tensor (B, C, T_wav), : where T_wav = T_feats * prod(upsample_scales).
• Return type: Tensor