espnet2.gan_tts.style_melgan.tade_res_block.TADELayer

source

class espnet2.gan_tts.style_melgan.tade_res_block.TADELayer(in_channels: int = 64, aux_channels: int = 80, kernel_size: int = 9, bias: bool = True, upsample_factor: int = 2, upsample_mode: str = 'nearest')

Bases: Module

TADE Layer module.

Initilize TADELayer module.

• Parameters:
  • in_channels (int) – Number of input channles.
  • aux_channels (int) – Number of auxirialy channles.
  • kernel_size (int) – Kernel size.
  • bias (bool) – Whether to use bias parameter in conv.
  • upsample_factor (int) – Upsample factor.
  • upsample_mode (str) – Upsample mode.

forward(x: Tensor, c: Tensor) → Tensor

Calculate forward propagation.

• Parameters:
  • x (Tensor) – Input tensor (B, in_channels, T).
  • c (Tensor) – Auxiliary input tensor (B, aux_channels, T’).
• Returns: Output tensor (B, in_channels, T * in_upsample_factor). Tensor: Upsampled aux tensor (B, in_channels, T * aux_upsample_factor).
• Return type: Tensor