nnsvs.mdn.mdn_get_most_probable_sigma_and_mu
- nnsvs.mdn.mdn_get_most_probable_sigma_and_mu(log_pi, log_sigma, mu)[source]
Return the mean and standard deviation of the Gaussian component whose weight coefficient is the largest as the most probable predictions.
- Parameters:
log_pi (torch.Tensor) – Tensor of shape (B, T, G) or (B, T, G, D_out) The log of multinomial distribution of the Gaussians. B is the batch size, T is data length of this batch, G is num_gaussians of class MDNLayer.
log_sigma (torch.Tensor) – Tensor of shape (B, T, G, D_out) The standard deviation of the Gaussians. D_out is out_dim of class MDNLayer.
mu (torch.Tensor) – Tensor of shape (B, T, G, D_out) The means of the Gaussians. D_out is out_dim of class MDNLayer.
- Returns:
- tuple of torch.Tensor
torch.Tensor of shape (B, T, D_out). The standardd deviations of the most probable Gaussian component. torch.Tensor of shape (B, T, D_out). Means of the Gaussians.
- Return type: