class_docstr: Test cases for train.
class_docstr_tok: ["Test","cases","for","train","."]
docstr: Tests training and evaluation code by running a single step.
docstr_tok: ["Tests","training","and","evaluation","code","by","running","a","single","step","."]
code: def test_train_and_evaluate(self):
      """Tests training and evaluation code by running a single step."""
      # Create a temporary directory where tensorboard metrics are written.
      workdir = tempfile.mkdtemp()
  
      # Go two directories up to the root of the flax directory.
      flax_root_dir = pathlib.Path(__file__).parents[2]
      data_dir = (
          str(flax_root_dir) + "/.tfds/metadata"
      )  # pylint: disable=unused-variable
  
      # Define training configuration.
      config = default.get_config()
      config.num_epochs = 1
      config.batch_size = 8
  
      with tfds.testing.mock_data(num_examples=8, data_dir=data_dir):
          train.train_and_evaluate(config=config, workdir=workdir)
  
file_path: flax/examples/mnist/train_test.py
imports: import pathlib
  import tempfile
  from absl.testing import absltest
  import jax
  from jax import numpy
  import numpy
  import tensorflow
  import tensorflow_datasets
  from configs import default
  import train
label_desc: Use image node_id 3 for calling the TrainTest obj's underlying member method code with example usage: obj.test_train_and_evaluate() without return types