espnet2.gan_tts.hifigan.residual_block.ResidualBlock
Less than 1 minute
espnet2.gan_tts.hifigan.residual_block.ResidualBlock
class espnet2.gan_tts.hifigan.residual_block.ResidualBlock(kernel_size: int = 3, channels: int = 512, dilations: List[int] = [1, 3, 5], bias: bool = True, use_additional_convs: bool = True, nonlinear_activation: str = 'LeakyReLU', nonlinear_activation_params: Dict[str, Any] = {'negative_slope': 0.1})
Bases: Module
Residual block module in HiFiGAN.
Initialize ResidualBlock module.
- Parameters:
- kernel_size (int) – Kernel size of dilation convolution layer.
- channels (int) – Number of channels for convolution layer.
- dilations (List *[*int ]) – List of dilation factors.
- use_additional_convs (bool) – Whether to use additional convolution layers.
- bias (bool) – Whether to add bias parameter in convolution layers.
- nonlinear_activation (str) – Activation function module name.
- nonlinear_activation_params (Dict *[*str , Any ]) – Hyperparameters for activation function.
forward(x: Tensor) → Tensor
Calculate forward propagation.
- Parameters:x (Tensor) – Input tensor (B, channels, T).
- Returns: Output tensor (B, channels, T).
- Return type: Tensor