class_docstr: Tests the default trainer on single device setup.
class_docstr_tok: ["Tests","the","default","trainer","on","single","device","setup","."]
code: def setUp(self):
      super(ClassificationTrainerTest, self).setUp()
      self.test_dir = tempfile.mkdtemp()
      # make sure tf does not allocate gpu memory
      tf.config.experimental.set_visible_devices([], "GPU")
  
imports: import functools
  import shutil
  import tempfile
  from absl.testing import absltest
  from clu import metric_writers
  import flax
  from flax import jax_utils
  import flax.linen
  import jax.numpy
  import jax.random
  import ml_collections
  import numpy
  from scenic.dataset_lib import datasets
  from scenic.model_lib import models
  from scenic.model_lib.base_models import classification_model
  from scenic.model_lib.base_models import multilabel_classification_model
  from scenic.train_lib import classification_trainer
  from scenic.train_lib import lr_schedules
  from scenic.train_lib import optimizers
  from scenic.train_lib import train_utils
  import tensorflow
  import tensorflow_datasets
label_desc: Use image node_id 1 for calling the ClassificationTrainerTest obj's underlying member method code with example usage: obj.setUp() without return types