docstr: Fits a training batch.
docstr_tok: ["Fits","a","training","batch","."]
code: def fit_batch(self, batch):
      """Fits a training batch."""
      inputs = batch.mix_sig.data.to(self.device)
      targets = torch.cat(
          [
              batch.source1.data.unsqueeze(-1),
              batch.source2.data.unsqueeze(-1),
          ],
          dim=-1,
      ).to(self.device)
  
      predictions = self.compute_forward(inputs, sb.Stage.TRAIN)
      loss = self.compute_objectives(predictions, targets)
  
      loss.backward()
      self.optimizer.step()
      self.optimizer.zero_grad()
      return loss.detach()
  
file_path: speechbrain/tests/integration/separation/example_conv_tasnet.py
imports: import torch
  import pathlib
  import speechbrain
  import torch.nn.functional
  from hyperpyyaml import load_hyperpyyaml
  from speechbrain.nnet.losses import get_si_snr_with_pitwrapper
label_desc: Use image node_id 3 for calling the SepBrain obj's underlying member method code with example usage: obj.fit_batch(batch) and returns: loss