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)