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| from models.mossformer2_sr.generator import Mossformer, Generator | |
| import torch.nn as nn | |
| class MossFormer2_SR_48K(nn.Module): | |
| """ | |
| The MossFormer2_SR_48K model for speech super-resolution. | |
| This class encapsulates the functionality of the MossFormer2 and HiFi-Gan | |
| Generator within a higher-level model. It processes input audio data to produce | |
| higher-resolution outputs. | |
| Arguments | |
| --------- | |
| args : Namespace | |
| Configuration arguments that may include hyperparameters | |
| and model settings (not utilized in this implementation but | |
| can be extended for flexibility). | |
| Example | |
| --------- | |
| >>> model = MossFormer2_SR_48K(args).model | |
| >>> x = torch.randn(10, 180, 2000) # Example input | |
| >>> outputs = model(x) # Forward pass | |
| >>> outputs.shape, mask.shape # Check output shapes | |
| """ | |
| def __init__(self, args): | |
| super(MossFormer2_SR_48K, self).__init__() | |
| # Initialize the TestNet model, which contains the MossFormer MaskNet | |
| self.model_m = Mossformer() # Instance of TestNet | |
| self.model_g = Generator(args) | |
| def forward(self, x): | |
| """ | |
| Forward pass through the model. | |
| Arguments | |
| --------- | |
| x : torch.Tensor | |
| Input tensor of dimension [B, N, S], where B is the batch size, | |
| N is the number of mel bins (80 in this case), and S is the | |
| sequence length (e.g., time frames). | |
| Returns | |
| ------- | |
| outputs : torch.Tensor | |
| Bandwidth expanded audio output tensor from the model. | |
| """ | |
| x = self.model_m(x) # Get outputs and mask from TestNet | |
| outpus = self.model_g(x) | |
| return outputs # Return the outputs | |