parameters: (mode=None, run_eagerly=None)
return_statement: return result
docstring: Returns the default test combinations for tf.keras tests.
  
    Note that if tf2 is enabled, then v1 session test will be skipped.
  
    Args:
      mode: List of modes to run the tests. The valid options are 'graph' and
        'eager'. Default to ['graph', 'eager'] if not specified. If a empty list
        is provide, then the test will run under the context based on tf's
        version, eg graph for v1 and eager for v2.
      run_eagerly: List of `run_eagerly` value to be run with the tests.
        Default to [True, False] if not specified. Note that for `graph` mode,
        run_eagerly value will only be False.
  
    Returns:
      A list contains all the combinations to be used to generate test cases.
docstring_summary: Returns the default test combinations for tf.keras tests.
docstring_tokens: Returns the default test combinations for tf . keras tests .
function: def keras_mode_combinations(mode=None, run_eagerly=None):
    """Returns the default test combinations for tf.keras tests.
  
    Note that if tf2 is enabled, then v1 session test will be skipped.
  
    Args:
      mode: List of modes to run the tests. The valid options are 'graph' and
        'eager'. Default to ['graph', 'eager'] if not specified. If a empty list
        is provide, then the test will run under the context based on tf's
        version, eg graph for v1 and eager for v2.
      run_eagerly: List of `run_eagerly` value to be run with the tests.
        Default to [True, False] if not specified. Note that for `graph` mode,
        run_eagerly value will only be False.
  
    Returns:
      A list contains all the combinations to be used to generate test cases.
    """
    if mode is None:
      mode = ['eager'] if tf2.enabled() else ['graph', 'eager']
    if run_eagerly is None:
      run_eagerly = [True, False]
    result = []
    if 'eager' in mode:
      result += combinations.combine(mode=['eager'], run_eagerly=run_eagerly)
    if 'graph' in mode:
      result += combinations.combine(mode=['graph'], run_eagerly=[False])
    return result
function_tokens: def keras_mode_combinations ( mode = None , run_eagerly = None ) : if mode is None : mode = [ 'eager' ] if tf2 . enabled ( ) else [ 'graph' , 'eager' ] if run_eagerly is None : run_eagerly = [ True , False ] result = [ ] if 'eager' in mode : result += combinations . combine ( mode = [ 'eager' ] , run_eagerly = run_eagerly ) if 'graph' in mode : result += combinations . combine ( mode = [ 'graph' ] , run_eagerly = [ False ] ) return result