docstr: Evaluates a batch
docstr_tok: ["Evaluates","a","batch"]
code: def evaluate_batch(self, batch, stage):
      """Evaluates a 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, stage)
      loss = self.compute_objectives(predictions, targets)
      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 4 for calling the SepBrain obj's underlying member method code with example usage: obj.evaluate_batch(batch, stage) and returns: loss