class_docstr: Tests for the MultiLabelClassificationModel.
class_docstr_tok: ["Tests","for","the","MultiLabelClassificationModel","."]
docstr: Tests loss_function by checking its output's validity.
docstr_tok: ["Tests","loss_function","by","checking","its","output","'s","validity","."]
code: def test_loss_function(self):
      """Tests loss_function by checking its output's validity."""
      model = FakeMultiLabelClassificationModel()
      batch, output = get_fake_batch_output()
      batch_replicated, outputs_replicated = (
          jax_utils.replicate(batch),
          jax_utils.replicate(output),
      )
  
      # Test loss function in the pmapped setup:
      loss_function_pmapped = jax.pmap(
          model.loss_function, axis_name="batch"
      )
      total_loss = loss_function_pmapped(
          outputs_replicated, batch_replicated
      )
      # Check that loss is returning valid values:
      self.is_valid(
          jax_utils.unreplicate(total_loss), value_name="loss"
      )
  
file_path: scenic/scenic/model_lib/base_models/tests/test_multilabel_classification_model.py
imports: from absl.testing import absltest
  from flax import jax_utils
  import jax
  import jax.numpy
  import ml_collections
  import numpy
  from scenic.model_lib.base_models import multilabel_classification_model
label_desc: Use image node_id 2 for calling the TestMultiLabelClassificationModel obj's underlying member method code with example usage: obj.test_loss_function() without return types