class_docstr: Test cases for LM library.
class_docstr_tok: ["Test","cases","for","LM","library","."]
code: def test_train_and_evaluate(self):
      config = default.get_config()
      config.max_corpus_chars = 1000
      config.vocab_size = 32
      config.per_device_batch_size = 2
      config.num_train_steps = 1
      config.num_eval_steps = 1
      config.num_predict_steps = 1
  
      config.num_layers = 1
      config.qkv_dim = 128
      config.emb_dim = 128
      config.mlp_dim = 512
      config.num_heads = 2
  
      config.max_target_length = 32
      config.max_eval_target_length = 32
      config.max_predict_length = 32
  
      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
  
      with tfds.testing.mock_data(num_examples=128, data_dir=data_dir):
          train.train_and_evaluate(config, workdir)
      logging.info("workdir content: %s", tf.io.gfile.listdir(workdir))
  
file_path: flax/examples/lm1b/train_test.py
imports: import pathlib
  import tempfile
  from absl import logging
  from absl.testing import absltest
  import jax
  import tensorflow
  import tensorflow_datasets
  from configs import default
  import train
label_desc: Use image node_id 2 for calling the TrainTest obj's underlying member method code with example usage: obj.test_train_and_evaluate() without return types