def __init__(self, outputs, column_names, column_types, **kwargs): inputs = input_module.StructuredDataInput() inputs.column_types = column_types inputs.column_names = column_names self.check(column_names, column_types) super().__init__(inputs=inputs, outputs=outputs, **kwargs) self._target_col_name = None
def test_structured_data_input_get_pps_cast_to_string(): input_node = nodes.StructuredDataInput() input_node.dtype = tf.float32 assert isinstance( input_node.get_hyper_preprocessors()[0].preprocessor, preprocessors.CastToString, )
def __init__(self, outputs, column_names, column_types, **kwargs): inputs = input_module.StructuredDataInput() inputs.column_types = column_types inputs.column_names = column_names if column_types: for column_type in column_types.values(): if column_type not in ['categorical', 'numerical']: raise ValueError( 'Column_types should be either "categorical" ' 'or "numerical", but got {name}'.format( name=column_type)) if column_names and column_types: for column_name in column_types: if column_name not in column_names: raise ValueError( 'Column_names and column_types are ' 'mismatched. Cannot find column name ' '{name} in the data.'.format(name=column_name)) super().__init__(inputs=inputs, outputs=outputs, **kwargs) self._target_col_name = None
def __init__(self, outputs, column_names, column_types, **kwargs): inputs = input_module.StructuredDataInput( column_names=column_names, column_types=column_types ) super().__init__(inputs=inputs, outputs=outputs, **kwargs)