def testSerializeDeserializeEvalConfig(self):
output_path = self._getTempDir()
options = config_pb2.Options()
options.compute_confidence_intervals.value = False
options.min_slice_size.value = 1
eval_config = config_pb2.EvalConfig(slicing_specs=[
config_pb2.SlicingSpec(feature_keys=['country'],
feature_values={
'age': '5',
'gender': 'f'
}),
config_pb2.SlicingSpec(feature_keys=['interest'],
feature_values={
'age': '6',
'gender': 'm'
})
],
options=options)
data_location = '/path/to/data'
file_format = 'tfrecords'
model_location = '/path/to/model'
with tf.io.gfile.GFile(os.path.join(output_path, 'eval_config.json'),
'w') as f:
f.write(
eval_config_writer._serialize_eval_run(eval_config,
data_location,
file_format,
{'': model_location}))
got_eval_config, got_data_location, got_file_format, got_model_locations = (
eval_config_writer.load_eval_run(output_path))
self.assertEqual(eval_config, got_eval_config)
self.assertEqual(data_location, got_data_location)
self.assertEqual(file_format, got_file_format)
self.assertEqual({'': model_location}, got_model_locations)
def testSerializeDeserializeLegacyEvalConfig(self):
output_path = self._getTempDir()
old_config = LegacyConfig(
model_location='/path/to/model',
data_location='/path/to/data',
slice_spec=[
slicer.SingleSliceSpec(columns=['country'],
features=[('age', 5), ('gender', 'f')]),
slicer.SingleSliceSpec(columns=['interest'],
features=[('age', 6), ('gender', 'm')])
],
example_count_metric_key=None,
example_weight_metric_key='key',
compute_confidence_intervals=False,
k_anonymization_count=1)
final_dict = {}
final_dict['tfma_version'] = tfma_version.VERSION
final_dict['eval_config'] = old_config
with tf.io.TFRecordWriter(os.path.join(output_path,
'eval_config')) as w:
w.write(pickle.dumps(final_dict))
got_eval_config, got_data_location, _, got_model_locations = (
eval_config_writer.load_eval_run(output_path))
options = config_pb2.Options()
options.compute_confidence_intervals.value = (
old_config.compute_confidence_intervals)
options.min_slice_size.value = old_config.k_anonymization_count
eval_config = config_pb2.EvalConfig(slicing_specs=[
config_pb2.SlicingSpec(feature_keys=['country'],
feature_values={
'age': '5',
'gender': 'f'
}),
config_pb2.SlicingSpec(feature_keys=['interest'],
feature_values={
'age': '6',
'gender': 'm'
})
],
options=options)
self.assertEqual(eval_config, got_eval_config)
self.assertEqual(old_config.data_location, got_data_location)
self.assertLen(got_model_locations, 1)
self.assertEqual(old_config.model_location,
list(got_model_locations.values())[0])