# Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for dataset_metadata.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
# GOOGLE-INITIALIZATION
import tensorflow as tf
from tensorflow_transform.tf_metadata import test_common
from tensorflow_transform.tf_metadata import dataset_schema as sch
from tensorflow_transform.tf_metadata import schema_utils
import unittest
class DatasetSchemaTest(unittest.TestCase):
def test_feature_spec_unsupported_dtype(self):
with self.assertRaisesRegexp(ValueError, 'invalid dtype'):
sch.Schema({
'fixed_float': sch.ColumnSchema(
tf.float64, [], sch.FixedColumnRepresentation())
})
def test_manually_create_schema(self):
schema = test_common.get_manually_created_schema()
generated_feature_spec = schema_utils.schema_as_feature_spec(
schema).feature_spec
self.assertEqual(test_common.test_feature_spec, generated_feature_spec)
def test_schema_equality(self):
schema1 = sch.Schema(column_schemas={
'fixed_int': sch.ColumnSchema(
tf.int64, [2], sch.FixedColumnRepresentation()),
'var_float': sch.ColumnSchema(
tf.float32, None, sch.ListColumnRepresentation())
})
schema2 = sch.Schema(column_schemas={
'fixed_int': sch.ColumnSchema(
tf.int64, [2], sch.FixedColumnRepresentation()),
'var_float': sch.ColumnSchema(
tf.float32, None, sch.ListColumnRepresentation())
})
schema3 = sch.Schema(column_schemas={
'fixed_int': sch.ColumnSchema(
tf.int64, [2], sch.FixedColumnRepresentation()),
'var_float': sch.ColumnSchema(
tf.string, None, sch.ListColumnRepresentation())
})
schema4 = sch.Schema(column_schemas={
'fixed_int': sch.ColumnSchema(
tf.int64, [2], sch.FixedColumnRepresentation())
})
self.assertEqual(schema1, schema2)
self.assertNotEqual(schema1, schema3)
self.assertNotEqual(schema1, schema4)
if __name__ == '__main__':
unittest.main()
