def test_deserialize_config_missing_key(self):
config_missing_key = {
'config': {
# Dtype is missing and should cause a failure.
# 'dtype': 'int32',
'default_value': None,
'key': 'a',
'normalizer_fn': None,
'shape': (2, )
},
'class_name': 'NumericColumn'
}
with self.assertRaisesRegexp(ValueError,
'Invalid config:.*expected keys.*dtype'):
serialization.deserialize_feature_column(config_missing_key)
def from_config(cls, config, custom_objects=None, columns_by_name=None):
"""See 'FeatureColumn` base class."""
from tensorflow.python.feature_column.serialization import \
deserialize_feature_column # pylint: disable=g-import-not-at-top
_check_config_keys(config, cls._fields)
kwargs = _standardize_and_copy_config(config)
kwargs['categorical_column'] = deserialize_feature_column(
config['categorical_column'], custom_objects, columns_by_name)
return cls(**kwargs)
def from_config(cls, config, custom_objects=None):
# Import here to avoid circular imports.
from tensorflow.python.feature_column import serialization # pylint: disable=g-import-not-at-top
config_cp = config.copy()
columns_by_name = {}
config_cp['feature_columns'] = [serialization.deserialize_feature_column(
c, custom_objects, columns_by_name) for c in config['feature_columns']]
config_cp['partitioner'] = generic_utils.deserialize_keras_object(
config['partitioner'], custom_objects)
return cls(**config_cp)
def from_config(cls, config, custom_objects=None, columns_by_name=None):
"""See 'FeatureColumn` base class."""
from tensorflow.python.feature_column.serialization import (
deserialize_feature_column, ) # pylint: disable=g-import-not-at-top
fc_lib._check_config_keys(config, cls._fields)
kwargs = fc_lib._standardize_and_copy_config(config)
kwargs["categorical_columns"] = tuple([
deserialize_feature_column(c, custom_objects, columns_by_name)
for c in config["categorical_columns"]
])
return cls(**kwargs)
def test_serialization(self):
"""Tests that column can be serialized."""
def _custom_fn(input_tensor):
return input_tensor + 42
column = sfc.sequence_numeric_column(
key='my-key', shape=(2,), default_value=3, dtype=dtypes.int32,
normalizer_fn=_custom_fn)
configs = serialization.serialize_feature_column(column)
column = serialization.deserialize_feature_column(
configs, custom_objects={_custom_fn.__name__: _custom_fn})
self.assertEqual(column.key, 'my-key')
self.assertEqual(column.shape, (2,))
self.assertEqual(column.default_value, 3)
self.assertEqual(column.normalizer_fn(3), 45)
with self.assertRaisesRegex(ValueError,
'Instance: 0 is not a FeatureColumn'):
serialization.serialize_feature_column(int())
def test_deserialize_invalid_config(self):
with self.assertRaisesRegexp(ValueError, 'Improper config format: {}'):
serialization.deserialize_feature_column({})