code: def testWarmStart_ExplicitCheckpointFile(self):
      # Create vocab for sparse column "sc_vocab".
      vocab_path = self._write_vocab(
          ["apple", "banana", "guava", "orange"], "vocab"
      )
      # Create feature column.
      sc_vocab = fc.categorical_column_with_vocabulary_file(
          "sc_vocab", vocabulary_file=vocab_path, vocabulary_size=4
      )
  
      # Save checkpoint from which to warm-start.
      _, prev_vocab_val = self._create_prev_run_var(
          "linear_model/sc_vocab/weights",
          shape=[4, 1],
          initializer=ones(),
      )
  
      partitioner = lambda shape, dtype: [1] * len(shape)
      # New graph, new session WITHOUT warm-starting.
      with ops.Graph().as_default() as g:
          with self.session(graph=g) as sess:
              cols_to_vars = self._create_linear_model(
                  [sc_vocab], partitioner
              )
              self.evaluate(variables.global_variables_initializer())
              # Without warm-starting, the weights should be initialized using default
              # initializer (which is init_ops.zeros_initializer).
              self._assert_cols_to_vars(
                  cols_to_vars, {sc_vocab: [np.zeros([4, 1])]}, sess
              )
  
      # New graph, new session with warm-starting.
      with ops.Graph().as_default() as g:
          with self.session(graph=g) as sess:
              cols_to_vars = self._create_linear_model(
                  [sc_vocab], partitioner
              )
              # Since old vocab is not explicitly set in WarmStartSettings, the old
              # vocab is assumed to be same as new vocab.
              ws_util.warm_start(
                  # Explicitly provide the file prefix instead of just the dir.
                  os.path.join(self.get_temp_dir(), "model-0"),
                  vars_to_warm_start=".*sc_vocab.*",
              )
              self.evaluate(variables.global_variables_initializer())
              # Verify weights were correctly warm-started.
              self._assert_cols_to_vars(
                  cols_to_vars, {sc_vocab: [prev_vocab_val]}, sess
              )
  
imports: import os
  import numpy
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.feature_column import feature_column_lib
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import checkpoint_utils
  from tensorflow.python.training import saver
  from tensorflow.python.training import warm_starting_util
label_desc: Use image node_id 28 for calling the WarmStartingUtilTest obj's underlying member method code with example usage: obj.testWarmStart_ExplicitCheckpointFile() without return types