docstr: Given the network predictions and targets computed the binary CE
docstr_tok: ["Given","the","network","predictions","and","targets","computed","the","binary","CE"]
code: def compute_objectives(self, predictions, batch, stage=True):
      "Given the network predictions and targets computed the binary CE"
      inputs = torch.tensor([10.0, -6.0], requires_grad=True)
      targets = torch.tensor([1, 0])
      loss = self.hparams.compute_loss(inputs, targets)
      return loss
  
file_path: speechbrain/tests/integration/sampling/example_sorting.py
imports: import os
  import torch
  import pickle
  import pathlib
  import itertools
  import speechbrain
  import torch.multiprocessing
  from hyperpyyaml import load_hyperpyyaml
label_desc: Use image node_id 2 for calling the SamplingBrain obj's underlying member method code with example usage: obj.compute_objectives(predictions, batch, stage) and returns: loss