parameters: (self, example_indices, feature_indices, feature_values)
docstring: Creates a `SparseFeatureColumn` representation.
  
      Args:
        example_indices: A 1-D int64 tensor of shape `[N]`. Also, accepts
        python lists, or numpy arrays.
        feature_indices: A 1-D int64 tensor of shape `[N]`. Also, accepts
        python lists, or numpy arrays.
        feature_values: An optional 1-D tensor float tensor of shape `[N]`. Also,
        accepts python lists, or numpy arrays.
  
      Returns:
        A `SparseFeatureColumn`
docstring_summary: Creates a `SparseFeatureColumn` representation.
docstring_tokens: Creates a SparseFeatureColumn representation .
function: def __init__(self, example_indices, feature_indices, feature_values):
      """Creates a `SparseFeatureColumn` representation.
  
      Args:
        example_indices: A 1-D int64 tensor of shape `[N]`. Also, accepts
        python lists, or numpy arrays.
        feature_indices: A 1-D int64 tensor of shape `[N]`. Also, accepts
        python lists, or numpy arrays.
        feature_values: An optional 1-D tensor float tensor of shape `[N]`. Also,
        accepts python lists, or numpy arrays.
  
      Returns:
        A `SparseFeatureColumn`
      """
      with op_scope([example_indices, feature_indices], None,
                    'SparseFeatureColumn'):
        self._example_indices = convert_to_tensor(example_indices,
                                                  name='example_indices',
                                                  dtype=dtypes.int64)
        self._feature_indices = convert_to_tensor(feature_indices,
                                                  name='feature_indices',
                                                  dtype=dtypes.int64)
      self._feature_values = None
      if feature_values is not None:
        with op_scope([feature_values], None, 'SparseFeatureColumn'):
          self._feature_values = convert_to_tensor(feature_values,
                                                   name='feature_values',
                                                   dtype=dtypes.float32)
function_tokens: def __init__ ( self , example_indices , feature_indices , feature_values ) : with op_scope ( [ example_indices , feature_indices ] , None , 'SparseFeatureColumn' ) : self . _example_indices = convert_to_tensor ( example_indices , name = 'example_indices' , dtype = dtypes . int64 ) self . _feature_indices = convert_to_tensor ( feature_indices , name = 'feature_indices' , dtype = dtypes . int64 ) self . _feature_values = None if feature_values is not None : with op_scope ( [ feature_values ] , None , 'SparseFeatureColumn' ) : self . _feature_values = convert_to_tensor ( feature_values , name = 'feature_values' , dtype = dtypes . float32 )