code: def _create_linear_model(self, feature_cols, partitioner):
      cols_to_vars = {}
      with variable_scope.variable_scope("", partitioner=partitioner):
          # Create the variables.
          fc.linear_model(
              features=self._create_dummy_inputs(),
              feature_columns=feature_cols,
              units=1,
              cols_to_vars=cols_to_vars,
          )
      # Return a dictionary mapping each column to its variable.
      return cols_to_vars
  
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 6 for calling the WarmStartingUtilTest obj's underlying member method code with example usage: obj._create_linear_model(feature_cols, partitioner) and returns: cols_to_vars