espnet2.gan_svs.abs_gan_svs.AbsGANSVS

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class espnet2.gan_svs.abs_gan_svs.AbsGANSVS(*args, **kwargs)

Bases: AbsSVS, ABC

Abstract class for GAN-based Singing Voice Synthesis (SVS) models.

This class serves as a base for implementing GAN-based models for singing voice synthesis. It inherits from the AbsSVS class and enforces the implementation of the forward method, which computes the loss for either the generator or the discriminator in the GAN framework.

None

• Parameters:
  • forward_generator – A callable that represents the generator function.
  • *args – Additional positional arguments to be passed to the generator.
  • **kwargs – Additional keyword arguments to be passed to the generator.
• Returns:
  • A tensor representing the generator or discriminator loss.
  • Optionally, a dictionary of tensors related to losses.
  • An integer that may represent the status or additional information.
• Return type: A dictionary containing
• Yields: None
• Raises:
  • NotImplementedError – If the forward method is not implemented in a
  • subclass. –

####### Examples

class MyGANSVS(AbsGANSVS): : def forward(self, forward_generator, <br/>

*

<br/> args, <br/>

**

<br/> kwargs): : # Implementation of the forward method pass

NOTE

This class is intended to be subclassed and should not be instantiated directly.

Initialize internal Module state, shared by both nn.Module and ScriptModule.

abstract forward(forward_generator, *args, **kwargs) → Dict[str, Tensor | Dict[str, Tensor] | int]

Compute the generator or discriminator loss based on the given inputs.

This method must be implemented by subclasses to define the specific behavior of the forward pass in the GAN-based SVS model. The method takes a generator function and additional arguments to calculate the losses.

• Parameters:
  • forward_generator (Callable) – A function that defines the forward pass of the generator or discriminator.
  • *args – Variable length argument list to be passed to the forward_generator.
  • **kwargs – Arbitrary keyword arguments to be passed to the forward_generator.
• Returns: A dictionary containing the loss values. The structure of the dictionary may vary depending on the implementation, but it should include keys for the generator and discriminator losses, as well as any additional metrics or values.
• Return type: Dict[str, Union[torch.Tensor, Dict[str, torch.Tensor], int]]
• Raises:NotImplementedError – If the method is not implemented by the subclass.

####### Examples

To use this method, a subclass must implement it as follows:

``

`

python class MyGANSVS(AbsGANSVS):

def forward(self, forward_generator,

*

args,

**

kwargs): : # Implement the forward logic loss = forward_generator( <br/>

*

<br/> args, <br/>

**

<br/> kwargs) return

``

`

NOTE

The actual computation of the losses will depend on the specific implementation of the forward_generator.