espnet2.tts.prodiff.loss.SSimLoss

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class espnet2.tts.prodiff.loss.SSimLoss(bias: float = 6.0, window_size: int = 11, channels: int = 1, reduction: str = 'none')

Bases: Module

SSimLoss.

This is an implementation of structural similarity (SSIM) loss. This code is modified from https://github.com/Po-Hsun-Su/pytorch-ssim.

Initialization.

• Parameters:
  • bias (float , optional) – value of the bias. Defaults to 6.0.
  • window_size (int , optional) – Window size. Defaults to 11.
  • channels (int , optional) – Number of channels. Defaults to 1.
  • reduction (str , optional) – Type of reduction during the loss calculation. Defaults to “none”.

forward(outputs: Tensor, target: Tensor)

Calculate forward propagation.

• Parameters:
  • outputs (torch.Tensor) – Batch of output sequences generated by the model (batch, time, mels).
  • target (torch.Tensor) – Batch of sequences with true states (batch, time, mels).
• Returns: Loss scalar value.
• Return type: Tensor

ssim(tensor1: Tensor, tensor2: Tensor)

Calculate SSIM loss.

• Parameters:
  • tensor1 (torch.Tensor) – Generated output.
  • tensor2 (torch.Tensor) – Groundtruth output.
• Returns: Loss scalar value.
• Return type: Tensor