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c579b8e18e
* implement validation for darts service * Update pkg/suggestion/v1beta1/nas/darts/service.py Co-authored-by: Jaeyeon Kim(김재연) <[email protected]> * Update pkg/suggestion/v1beta1/nas/darts/service.py Co-authored-by: Jaeyeon Kim(김재연) <[email protected]> * [review] delete todo comment * [review] change function name validate_algorithm_settings to validate_algorithm_spec * [review] fix vaiolation comments * [review] fix condition to validate batch_size * [review] add comment for developers * [review] use set instead of list Co-authored-by: Jaeyeon Kim(김재연) <[email protected]>
181 lines
6.8 KiB
Python
181 lines
6.8 KiB
Python
# Copyright 2022 The Kubeflow Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from pkg.apis.manager.v1beta1.python import api_pb2
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from pkg.suggestion.v1beta1.nas.common.validation import validate_operations
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class TestNasCommon(unittest.TestCase):
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def test_validate_operations(self):
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# Valid Case
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valid_operations = [
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api_pb2.Operation(
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operation_type="separable_convolution",
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parameter_specs=api_pb2.Operation.ParameterSpecs(
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parameters=[
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api_pb2.ParameterSpec(
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name="filter_size",
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parameter_type=api_pb2.CATEGORICAL,
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feasible_space=api_pb2.FeasibleSpace(
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max=None, min=None, list=["3", "5"]),
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),
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api_pb2.ParameterSpec(
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name="pool_size",
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parameter_type=api_pb2.INT,
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feasible_space=api_pb2.FeasibleSpace(
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max="2", min="3", step="1", list=[]),
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),
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api_pb2.ParameterSpec(
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name="valid_type_double_example",
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parameter_type=api_pb2.DOUBLE,
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feasible_space=api_pb2.FeasibleSpace(
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max="1.0", min="3.0", step="0.1", list=[]),
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),
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],
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),
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),
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]
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is_valid, _ = validate_operations(valid_operations)
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self.assertEqual(is_valid, True)
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# Invalid OperationType
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invalid_operation_type = [
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api_pb2.Operation(
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parameter_specs=api_pb2.Operation.ParameterSpecs(
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parameters=[
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api_pb2.ParameterSpec(
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name="filter_size",
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parameter_type=api_pb2.CATEGORICAL,
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feasible_space=api_pb2.FeasibleSpace(
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max=None, min=None, list=["3", "5"])
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),
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],
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),
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),
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]
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is_valid, _ = validate_operations(invalid_operation_type)
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self.assertEqual(is_valid, False)
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# Invalid ParameterConfigs
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invalid_parameter_configs = [
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api_pb2.Operation(
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operation_type="separable_convolution",
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parameter_specs=api_pb2.Operation.ParameterSpecs(),
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),
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]
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is_valid, _ = validate_operations(invalid_parameter_configs)
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self.assertEqual(is_valid, False)
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# Invalid ParameterName
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invalid_parameter_name = [
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api_pb2.Operation(
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operation_type="separable_convolution",
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parameter_specs=api_pb2.Operation.ParameterSpecs(
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parameters=[
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api_pb2.ParameterSpec(
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name="",
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parameter_type=api_pb2.CATEGORICAL,
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feasible_space=api_pb2.FeasibleSpace(
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max=None, min=None, list=["3", "5"]),
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),
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],
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),
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),
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]
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is_valid, _ = validate_operations(invalid_parameter_name)
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self.assertEqual(is_valid, False)
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# Invalid ParameterType
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invalid_parameter_type = [
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api_pb2.Operation(
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operation_type="separable_convolution",
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parameter_specs=api_pb2.Operation.ParameterSpecs(
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parameters=[
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api_pb2.ParameterSpec(
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name="filter_size",
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feasible_space=api_pb2.FeasibleSpace(
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max=None, min=None, list=["3", "5"]),
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),
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],
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),
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),
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]
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is_valid, _ = validate_operations(invalid_parameter_type)
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self.assertEqual(is_valid, False)
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# invalid List in Categorical
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invalid_categorical_list = [
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api_pb2.Operation(
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operation_type="separable_convolution",
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parameter_specs=api_pb2.Operation.ParameterSpecs(
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parameters=[
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api_pb2.ParameterSpec(
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name="filter_size",
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parameter_type=api_pb2.CATEGORICAL,
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feasible_space=api_pb2.FeasibleSpace(
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max="1", min="2", list=None),
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),
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],
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),
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),
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]
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is_valid, _ = validate_operations(invalid_categorical_list)
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self.assertEqual(is_valid, False)
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# invalid Min and Max
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invalid_min_max = [
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api_pb2.Operation(
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operation_type="separable_convolution",
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parameter_specs=api_pb2.Operation.ParameterSpecs(
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parameters=[
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api_pb2.ParameterSpec(
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name="pool_size",
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parameter_type=api_pb2.INT,
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feasible_space=api_pb2.FeasibleSpace(
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max=None, min=None, step=None, list=["1", "2"]),
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),
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],
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),
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),
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]
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is_valid, _ = validate_operations(invalid_min_max)
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self.assertEqual(is_valid, False)
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# Invalid Double type parameter
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invalid_double_parameter = [
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api_pb2.Operation(
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operation_type="separable_convolution",
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parameter_specs=api_pb2.Operation.ParameterSpecs(
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parameters=[
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api_pb2.ParameterSpec(
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name="invalid_type_double_example",
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parameter_type=api_pb2.DOUBLE,
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feasible_space=api_pb2.FeasibleSpace(
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max="1.0", min="3.0", step=None, list=None),
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),
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],
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),
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),
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]
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is_valid, _ = validate_operations(invalid_double_parameter)
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self.assertEqual(is_valid, False)
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if __name__ == '__main__':
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unittest.main()
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