How to use _mock_create method in autotest
Best Python code snippet using autotest_python
runner_test.py
Source:runner_test.py 
1# Lint as: python2, python32# Copyright 2019 Google LLC. All Rights Reserved.3#4# Licensed under the Apache License, Version 2.0 (the "License");5# you may not use this file except in compliance with the License.6# You may obtain a copy of the License at7#8# http://www.apache.org/licenses/LICENSE-2.09#10# Unless required by applicable law or agreed to in writing, software11# distributed under the License is distributed on an "AS IS" BASIS,12# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.13# See the License for the specific language governing permissions and14# limitations under the License.15"""Tests for tfx.extensions.google_cloud_ai_platform.runner."""16from __future__ import absolute_import17from __future__ import division18from __future__ import print_function19import copy20import os21import sys22from typing import Any, Dict, Text23# Standard Imports24import mock25import tensorflow as tf26from tfx import version27from tfx.extensions.google_cloud_ai_platform import runner28from tfx.extensions.google_cloud_ai_platform.trainer import executor29from tfx.utils import json_utils30from tfx.utils import telemetry_utils31class RunnerTest(tf.test.TestCase):32 def setUp(self):33 super(RunnerTest, self).setUp()34 self._output_data_dir = os.path.join(35 os.environ.get('TEST_UNDECLARED_OUTPUTS_DIR', self.get_temp_dir()),36 self._testMethodName)37 self._project_id = '12345'38 self._mock_api_client = mock.Mock()39 self._inputs = {}40 self._outputs = {}41 self._training_inputs = {42 'project': self._project_id,43 }44 self._job_id = 'my_jobid'45 # Dict format of exec_properties. custom_config needs to be serialized46 # before being passed into start_aip_training function.47 self._exec_properties = {48 'custom_config': {49 executor.TRAINING_ARGS_KEY: self._training_inputs,50 },51 }52 self._model_name = 'model_name'53 self._ai_platform_serving_args = {54 'model_name': self._model_name,55 'project_id': self._project_id,56 }57 self._executor_class_path = 'my.executor.Executor'58 def _setUpTrainingMocks(self):59 self._mock_create = mock.Mock()60 self._mock_api_client.projects().jobs().create = self._mock_create61 self._mock_get = mock.Mock()62 self._mock_api_client.projects().jobs().get.return_value = self._mock_get63 self._mock_get.execute.return_value = {64 'state': 'SUCCEEDED',65 }66 def _serialize_custom_config_under_test(self) -> Dict[Text, Any]:67 """Converts self._exec_properties['custom_config'] to string."""68 result = copy.deepcopy(self._exec_properties)69 result['custom_config'] = json_utils.dumps(result['custom_config'])70 return result71 @mock.patch(72 'tfx.extensions.google_cloud_ai_platform.runner.discovery'73 )74 def testStartAIPTraining(self, mock_discovery):75 mock_discovery.build.return_value = self._mock_api_client76 self._setUpTrainingMocks()77 class_path = 'foo.bar.class'78 runner.start_aip_training(self._inputs, self._outputs,79 self._serialize_custom_config_under_test(),80 class_path,81 self._training_inputs, None)82 self._mock_create.assert_called_with(83 body=mock.ANY, parent='projects/{}'.format(self._project_id))84 (_, kwargs) = self._mock_create.call_args85 body = kwargs['body']86 default_image = 'gcr.io/tfx-oss-public/tfx:{}'.format(version.__version__)87 self.assertDictContainsSubset(88 {89 'masterConfig': {90 'imageUri': default_image,91 },92 'args': [93 '--executor_class_path', class_path, '--inputs', '{}',94 '--outputs', '{}', '--exec-properties', '{"custom_config": '95 '"{\\"ai_platform_training_args\\": {\\"project\\": \\"12345\\"'96 '}}"}'97 ],98 }, body['trainingInput'])99 self.assertStartsWith(body['jobId'], 'tfx_')100 self._mock_get.execute.assert_called_with()101 @mock.patch(102 'tfx.extensions.google_cloud_ai_platform.runner.discovery'103 )104 def testStartAIPTrainingWithUserContainer(self, mock_discovery):105 mock_discovery.build.return_value = self._mock_api_client106 self._setUpTrainingMocks()107 class_path = 'foo.bar.class'108 self._training_inputs['masterConfig'] = {'imageUri': 'my-custom-image'}109 self._exec_properties['custom_config'][executor.JOB_ID_KEY] = self._job_id110 runner.start_aip_training(self._inputs, self._outputs,111 self._serialize_custom_config_under_test(),112 class_path,113 self._training_inputs, self._job_id)114 self._mock_create.assert_called_with(115 body=mock.ANY, parent='projects/{}'.format(self._project_id))116 (_, kwargs) = self._mock_create.call_args117 body = kwargs['body']118 self.assertDictContainsSubset(119 {120 'masterConfig': {121 'imageUri': 'my-custom-image',122 },123 'args': [124 '--executor_class_path', class_path, '--inputs', '{}',125 '--outputs', '{}', '--exec-properties', '{"custom_config": '126 '"{\\"ai_platform_training_args\\": '127 '{\\"masterConfig\\": {\\"imageUri\\": \\"my-custom-image\\"}, '128 '\\"project\\": \\"12345\\"}, '129 '\\"ai_platform_training_job_id\\": \\"my_jobid\\"}"}'130 ],131 }, body['trainingInput'])132 self.assertEqual(body['jobId'], 'my_jobid')133 self._mock_get.execute.assert_called_with()134 def _setUpPredictionMocks(self):135 self._serving_path = os.path.join(self._output_data_dir, 'serving_path')136 self._model_version = 'model_version'137 self._mock_models_create = mock.Mock()138 self._mock_api_client.projects().models().create = self._mock_models_create139 self._mock_versions_create = mock.Mock()140 self._mock_versions_create.return_value.execute.return_value = {141 'name': 'versions_create_op_name'142 }143 self._mock_api_client.projects().models().versions(144 ).create = self._mock_versions_create145 self._mock_get = mock.Mock()146 self._mock_api_client.projects().operations().get = self._mock_get147 self._mock_set_default = mock.Mock()148 self._mock_api_client.projects().models().versions(149 ).setDefault = self._mock_set_default150 self._mock_set_default_execute = mock.Mock()151 self._mock_api_client.projects().models().versions().setDefault(152 ).execute = self._mock_set_default_execute153 self._mock_get.return_value.execute.return_value = {154 'done': True,155 'response': {156 'name': self._model_version,157 },158 }159 def _assertDeployModelMockCalls(self,160 expected_models_create_body=None,161 expected_versions_create_body=None,162 expect_set_default=True):163 if not expected_models_create_body:164 expected_models_create_body = {165 'name':166 self._model_name,167 'regions':168 [],169 }170 if not expected_versions_create_body:171 with telemetry_utils.scoped_labels(172 {telemetry_utils.LABEL_TFX_EXECUTOR: self._executor_class_path}):173 labels = telemetry_utils.get_labels_dict()174 expected_versions_create_body = {175 'name':176 self._model_version,177 'deployment_uri':178 self._serving_path,179 'runtime_version':180 runner._get_tf_runtime_version(tf.__version__),181 'python_version':182 runner._get_caip_python_version(183 runner._get_tf_runtime_version(tf.__version__)),184 'labels': labels185 }186 self._mock_models_create.assert_called_with(187 body=mock.ANY,188 parent='projects/{}'.format(self._project_id),189 )190 (_, models_create_kwargs) = self._mock_models_create.call_args191 self.assertDictEqual(expected_models_create_body,192 models_create_kwargs['body'])193 self._mock_versions_create.assert_called_with(194 body=mock.ANY,195 parent='projects/{}/models/{}'.format(self._project_id,196 self._model_name))197 (_, versions_create_kwargs) = self._mock_versions_create.call_args198 self.assertDictEqual(expected_versions_create_body,199 versions_create_kwargs['body'])200 if not expect_set_default:201 return202 self._mock_set_default.assert_called_with(203 name='projects/{}/models/{}/versions/{}'.format(204 self._project_id, self._model_name, self._model_version))205 self._mock_set_default_execute.assert_called_with()206 @mock.patch(207 'tfx.extensions.google_cloud_ai_platform.runner.discovery'208 )209 def testDeployModelForAIPPrediction(self, mock_discovery):210 mock_discovery.build.return_value = self._mock_api_client211 self._setUpPredictionMocks()212 runner.deploy_model_for_aip_prediction(self._serving_path,213 self._model_version,214 self._ai_platform_serving_args,215 self._executor_class_path)216 expected_models_create_body = {217 'name': self._model_name,218 'regions': []219 }220 self._assertDeployModelMockCalls(221 expected_models_create_body=expected_models_create_body)222 @mock.patch(223 'tfx.extensions.google_cloud_ai_platform.runner.discovery'224 )225 def testDeployModelForAIPPredictionError(self, mock_discovery):226 mock_discovery.build.return_value = self._mock_api_client227 self._setUpPredictionMocks()228 self._mock_get.return_value.execute.return_value = {229 'done': True,230 'error': {231 'code': 999,232 'message': 'it was an error.'233 },234 }235 with self.assertRaises(RuntimeError):236 runner.deploy_model_for_aip_prediction(self._serving_path,237 self._model_version,238 self._ai_platform_serving_args,239 self._executor_class_path)240 expected_models_create_body = {241 'name': self._model_name,242 'regions': []243 }244 self._assertDeployModelMockCalls(245 expected_models_create_body=expected_models_create_body,246 expect_set_default=False)247 @mock.patch(248 'tfx.extensions.google_cloud_ai_platform.runner.discovery'249 )250 def testDeployModelForAIPPredictionWithCustomRegion(self, mock_discovery):251 mock_discovery.build.return_value = self._mock_api_client252 self._setUpPredictionMocks()253 self._ai_platform_serving_args['regions'] = ['custom-region']254 runner.deploy_model_for_aip_prediction(self._serving_path,255 self._model_version,256 self._ai_platform_serving_args,257 self._executor_class_path)258 expected_models_create_body = {259 'name': self._model_name,260 'regions': ['custom-region'],261 }262 self._assertDeployModelMockCalls(263 expected_models_create_body=expected_models_create_body)264 @mock.patch(265 'tfx.extensions.google_cloud_ai_platform.runner.discovery'266 )267 def testDeployModelForAIPPredictionWithCustomRuntime(self, mock_discovery):268 mock_discovery.build.return_value = self._mock_api_client269 self._setUpPredictionMocks()270 self._ai_platform_serving_args['runtime_version'] = '1.23.45'271 runner.deploy_model_for_aip_prediction(self._serving_path,272 self._model_version,273 self._ai_platform_serving_args,274 self._executor_class_path)275 with telemetry_utils.scoped_labels(276 {telemetry_utils.LABEL_TFX_EXECUTOR: self._executor_class_path}):277 labels = telemetry_utils.get_labels_dict()278 expected_versions_create_body = {279 'name': self._model_version,280 'deployment_uri': self._serving_path,281 'runtime_version': '1.23.45',282 'python_version': runner._get_caip_python_version('1.23.45'),283 'labels': labels,284 }285 self._assertDeployModelMockCalls(286 expected_versions_create_body=expected_versions_create_body)287 def testGetTensorflowRuntime(self):288 self.assertEqual('1.14', runner._get_tf_runtime_version('1.14'))289 self.assertEqual('1.15', runner._get_tf_runtime_version('1.15.0'))290 self.assertEqual('1.15', runner._get_tf_runtime_version('1.15.1'))291 self.assertEqual('1.15', runner._get_tf_runtime_version('2.0.0'))292 self.assertEqual('1.15', runner._get_tf_runtime_version('2.0.1'))293 self.assertEqual('2.1', runner._get_tf_runtime_version('2.1.0'))294 # TODO(b/157039850) Remove this once CAIP model support TF 2.2 runtime.295 self.assertEqual('2.1', runner._get_tf_runtime_version('2.2.0'))296 def testGetCaipPythonVersion(self):297 if sys.version_info.major == 2:298 self.assertEqual('2.7', runner._get_caip_python_version('1.14'))299 self.assertEqual('2.7', runner._get_caip_python_version('1.15'))300 else: # 3.x301 self.assertEqual('3.5', runner._get_caip_python_version('1.14'))302 self.assertEqual('3.7', runner._get_caip_python_version('1.15'))303 self.assertEqual('3.7', runner._get_caip_python_version('2.1'))304if __name__ == '__main__':...
client_test.py
Source:client_test.py
1# Copyright 2019 Google LLC. All Rights Reserved.2#3# Licensed under the Apache License, Version 2.0 (the "License");4# you may not use this file except in compliance with the License.5# You may obtain a copy of the License at6#7# http://www.apache.org/licenses/LICENSE-2.08#9# Unless required by applicable law or agreed to in writing, software10# distributed under the License is distributed on an "AS IS" BASIS,11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.12# See the License for the specific language governing permissions and13# limitations under the License.14"""Tests for cloud_fit.client."""15import os16import tempfile17from unittest import mock18import cloudpickle19from googleapiclient import discovery20import tensorflow as tf21import tensorflow_datasets as tfds22from tensorflow_enterprise_addons.cloud_fit import client23from tensorflow_enterprise_addons.cloud_fit import utils24# Can only export Datasets which were created executing eagerly25utils.enable_eager_for_tf_1()26MIRRORED_STRATEGY_NAME = utils.MIRRORED_STRATEGY_NAME27MULTI_WORKER_MIRRORED_STRATEGY_NAME = utils.MULTI_WORKER_MIRRORED_STRATEGY_NAME28class CloudFitClientTest(tf.test.TestCase):29 def setUp(self):30 super(CloudFitClientTest, self).setUp()31 self._image_uri = 'gcr.io/some_test_image:latest'32 self._project_id = 'test_project_id'33 self._region = 'test_region'34 self._mock_apiclient = mock.Mock()35 self._remote_dir = tempfile.mkdtemp()36 self._job_spec = client._default_job_spec(self._region, self._image_uri, [37 '--remote_dir', self._remote_dir, '--distribution_strategy',38 MULTI_WORKER_MIRRORED_STRATEGY_NAME39 ])40 self._model = self._model()41 self._x = [[9.], [10.], [11.]] * 1042 self._y = [[xi[0] / 2. + 6] for xi in self._x]43 self._dataset = tf.data.Dataset.from_tensor_slices((self._x, self._y))44 self._scalar_fit_kwargs = {'batch_size': 1, 'epochs': 2, 'verbose': 3}45 def _set_up_training_mocks(self):46 self._mock_create = mock.Mock()47 self._mock_apiclient.projects().jobs().create = self._mock_create48 self._mock_get = mock.Mock()49 self._mock_create.return_value = self._mock_get50 self._mock_get.execute.return_value = {51 'state': 'SUCCEEDED',52 }53 def _model(self):54 """Writes SavedModel to compute y = wx + 1, with w trainable."""55 inp = tf.keras.layers.Input(shape=(1,), dtype=tf.float32)56 times_w = tf.keras.layers.Dense(57 units=1,58 kernel_initializer=tf.keras.initializers.Constant([[0.5]]),59 kernel_regularizer=tf.keras.regularizers.l2(0.01),60 use_bias=False)61 plus_1 = tf.keras.layers.Dense(62 units=1,63 kernel_initializer=tf.keras.initializers.Constant([[1.0]]),64 bias_initializer=tf.keras.initializers.Constant([1.0]),65 trainable=False)66 outp = plus_1(times_w(inp))67 model = tf.keras.Model(inp, outp)68 model.compile(69 tf.keras.optimizers.SGD(0.002), 'mean_squared_error', run_eagerly=True)70 return model71 def test_default_job_spec(self):72 self.assertStartsWith(self._job_spec['job_id'], 'cloud_fit_')73 self.assertDictContainsSubset(74 {75 'masterConfig': {76 'imageUri': self._image_uri,77 },78 'args': [79 '--remote_dir', self._remote_dir, '--distribution_strategy',80 MULTI_WORKER_MIRRORED_STRATEGY_NAME81 ],82 }, self._job_spec['trainingInput'])83 @mock.patch.object(discovery, 'build', autospec=True)84 def test_submit_job(self, mock_discovery_build):85 mock_discovery_build.return_value = self._mock_apiclient86 self._set_up_training_mocks()87 client._submit_job(self._job_spec, self._project_id)88 mock_discovery_build.assert_called_once_with(89 'ml', 'v1', cache_discovery=False)90 self._mock_create.assert_called_with(91 body=mock.ANY, parent='projects/{}'.format(self._project_id))92 _, fit_kwargs = list(self._mock_create.call_args)93 body = fit_kwargs['body']94 self.assertDictContainsSubset(95 {96 'masterConfig': {97 'imageUri': self._image_uri,98 },99 'args': [100 '--remote_dir', self._remote_dir, '--distribution_strategy',101 MULTI_WORKER_MIRRORED_STRATEGY_NAME102 ],103 }, body['trainingInput'])104 self.assertStartsWith(body['job_id'], 'cloud_fit_')105 self._mock_get.execute.assert_called_with()106 def test_serialize_assets(self):107 # TF 1.x is not supported108 if utils.is_tf_v1():109 with self.assertRaises(RuntimeError):110 client.cloud_fit(111 self._model,112 x=self._dataset,113 validation_data=self._dataset,114 remote_dir=self._remote_dir,115 job_spec=self._job_spec,116 batch_size=1,117 epochs=2,118 verbose=3)119 return120 tensorboard_callback = tf.keras.callbacks.TensorBoard(121 log_dir=self._remote_dir)122 args = self._scalar_fit_kwargs123 args['callbacks'] = [tensorboard_callback]124 client._serialize_assets(self._remote_dir, self._model, **args)125 self.assertGreaterEqual(126 len(127 tf.io.gfile.listdir(128 os.path.join(self._remote_dir, 'training_assets'))), 1)129 self.assertGreaterEqual(130 len(tf.io.gfile.listdir(os.path.join(self._remote_dir, 'model'))), 1)131 training_assets_graph = tf.saved_model.load(132 os.path.join(self._remote_dir, 'training_assets'))133 pickled_callbacks = tfds.as_numpy(training_assets_graph.callbacks_fn())134 unpickled_callbacks = cloudpickle.loads(pickled_callbacks)135 self.assertIsInstance(unpickled_callbacks[0],136 tf.keras.callbacks.TensorBoard)137 @mock.patch.object(client, '_submit_job', autospec=True)138 def test_fit_kwargs(self, mock_submit_job):139 # TF 1.x is not supported140 if utils.is_tf_v1():141 with self.assertRaises(RuntimeError):142 client.cloud_fit(143 self._model,144 x=self._dataset,145 validation_data=self._dataset,146 remote_dir=self._remote_dir,147 job_spec=self._job_spec,148 batch_size=1,149 epochs=2,150 verbose=3)151 return152 job_id = client.cloud_fit(153 self._model,154 x=self._dataset,155 validation_data=self._dataset,156 remote_dir=self._remote_dir,157 region=self._region,158 project_id=self._project_id,159 image_uri=self._image_uri,160 batch_size=1,161 epochs=2,162 verbose=3)163 kargs, _ = mock_submit_job.call_args164 body, _ = kargs165 self.assertEqual(body['job_id'], job_id)166 remote_dir = body['trainingInput']['args'][1]167 training_assets_graph = tf.saved_model.load(168 os.path.join(remote_dir, 'training_assets'))169 elements = training_assets_graph.fit_kwargs_fn()170 self.assertDictContainsSubset(171 tfds.as_numpy(elements), {172 'batch_size': 1,173 'epochs': 2,174 'verbose': 3175 })176 @mock.patch.object(client, '_submit_job', autospec=True)177 def test_custom_job_spec(self, mock_submit_job):178 # TF 1.x is not supported179 if utils.is_tf_v1():180 with self.assertRaises(RuntimeError):181 client.cloud_fit(182 self._model,183 x=self._dataset,184 validation_data=self._dataset,185 remote_dir=self._remote_dir,186 job_spec=self._job_spec,187 batch_size=1,188 epochs=2,189 verbose=3)190 return191 client.cloud_fit(192 self._model,193 x=self._dataset,194 validation_data=self._dataset,195 remote_dir=self._remote_dir,196 job_spec=self._job_spec,197 batch_size=1,198 epochs=2,199 verbose=3)200 kargs, _ = mock_submit_job.call_args201 body, _ = kargs202 self.assertDictContainsSubset(203 {204 'masterConfig': {205 'imageUri': self._image_uri,206 },207 'args': [208 '--remote_dir', self._remote_dir, '--distribution_strategy',209 MULTI_WORKER_MIRRORED_STRATEGY_NAME210 ],211 }, body['trainingInput'])212 @mock.patch.object(client, '_submit_job', autospec=True)213 @mock.patch.object(client, '_serialize_assets', autospec=True)214 def test_distribution_strategy(self, mock_serialize_assets, mock_submit_job):215 # TF 1.x is not supported216 if utils.is_tf_v1():217 with self.assertRaises(RuntimeError):218 client.cloud_fit(219 self._model, x=self._dataset, remote_dir=self._remote_dir)220 return221 client.cloud_fit(self._model, x=self._dataset, remote_dir=self._remote_dir)222 kargs, _ = mock_submit_job.call_args223 body, _ = kargs224 self.assertDictContainsSubset(225 {226 'args': [227 '--remote_dir', self._remote_dir, '--distribution_strategy',228 MULTI_WORKER_MIRRORED_STRATEGY_NAME229 ],230 }, body['trainingInput'])231 client.cloud_fit(232 self._model,233 x=self._dataset,234 remote_dir=self._remote_dir,235 distribution_strategy=MIRRORED_STRATEGY_NAME,236 job_spec=self._job_spec)237 kargs, _ = mock_submit_job.call_args238 body, _ = kargs239 self.assertDictContainsSubset(240 {241 'args': [242 '--remote_dir', self._remote_dir, '--distribution_strategy',243 MIRRORED_STRATEGY_NAME244 ],245 }, body['trainingInput'])246 with self.assertRaises(ValueError):247 client.cloud_fit(248 self._model,249 x=self._dataset,250 remote_dir=self._remote_dir,251 distribution_strategy='not_implemented_strategy',252 job_spec=self._job_spec)253 @mock.patch.object(client, '_submit_job', autospec=True)254 @mock.patch.object(client, '_serialize_assets', autospec=True)255 def test_job_id(self, mock_serialize_assets, mock_submit_job):256 # TF 1.x is not supported257 if utils.is_tf_v1():258 with self.assertRaises(RuntimeError):259 client.cloud_fit(260 self._model,261 x=self._dataset,262 validation_data=self._dataset,263 remote_dir=self._remote_dir,264 job_spec=self._job_spec,265 batch_size=1,266 epochs=2,267 verbose=3)268 return269 test_job_id = 'test_job_id'270 client.cloud_fit(271 self._model,272 x=self._dataset,273 validation_data=self._dataset,274 remote_dir=self._remote_dir,275 job_spec=self._job_spec,276 job_id=test_job_id,277 batch_size=1,278 epochs=2,279 verbose=3)280 kargs, _ = mock_submit_job.call_args281 body, _ = kargs282 self.assertDictContainsSubset({283 'job_id': test_job_id,284 }, body)285if __name__ == '__main__':...
ai_platform_training_executor_test.py
Source:ai_platform_training_executor_test.py
1# Copyright 2020 Google LLC. All Rights Reserved.2#3# Licensed under the Apache License, Version 2.0 (the "License");4# you may not use this file except in compliance with the License.5# You may obtain a copy of the License at6#7# http://www.apache.org/licenses/LICENSE-2.08#9# Unless required by applicable law or agreed to in writing, software10# distributed under the License is distributed on an "AS IS" BASIS,11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.12# See the License for the specific language governing permissions and13# limitations under the License.14"""Tests for AI Platform Training component executor."""15import copy16from unittest import mock17from googleapiclient import discovery18import tensorflow as tf # pylint: disable=g-explicit-tensorflow-version-import19from tfx.dsl.component.experimental import placeholders20from tfx.orchestration.kubeflow.v2.components.experimental import ai_platform_training_executor21from tfx.types import artifact_utils22from tfx.types import standard_artifacts23from tfx.utils import json_utils24from tfx.utils import test_case_utils25_EXAMPLE_LOCATION = 'root/ExampleGen/1/examples/'26_MODEL_LOCATION = 'root/Training/2/model/'27class AiPlatformTrainingExecutorTest(test_case_utils.TfxTest):28 def setUp(self):29 super().setUp()30 self._project_id = 'my-project'31 self._job_id = 'my-job-123'32 self._labels = ['label1', 'label2']33 examples_artifact = standard_artifacts.Examples()34 examples_artifact.split_names = artifact_utils.encode_split_names(35 ['train', 'eval'])36 examples_artifact.uri = _EXAMPLE_LOCATION37 self._inputs = {'examples': [examples_artifact]}38 model_artifact = standard_artifacts.Model()39 model_artifact.uri = _MODEL_LOCATION40 self._outputs = {'model': [model_artifact]}41 training_job = {42 'training_input': {43 'scaleTier':44 'CUSTOM',45 'region':46 'us-central1',47 'masterType':48 'n1-standard-8',49 'masterConfig': {50 'imageUri': 'gcr.io/my-project/caip-training-test:latest'51 },52 'workerType':53 'n1-standard-8',54 'workerCount':55 8,56 'workerConfig': {57 'imageUri': 'gcr.io/my-project/caip-training-test:latest'58 },59 'args': [60 '--examples',61 placeholders.InputUriPlaceholder('examples'), '--n-steps',62 placeholders.InputValuePlaceholder('n_step'), '--model-dir',63 placeholders.OutputUriPlaceholder('model')64 ]65 },66 'labels': self._labels,67 }68 aip_training_config = {69 ai_platform_training_executor.PROJECT_CONFIG_KEY: self._project_id,70 ai_platform_training_executor.TRAINING_JOB_CONFIG_KEY: training_job,71 ai_platform_training_executor.JOB_ID_CONFIG_KEY: self._job_id,72 ai_platform_training_executor.LABELS_CONFIG_KEY: self._labels,73 }74 self._exec_properties = {75 ai_platform_training_executor.CONFIG_KEY:76 json_utils.dumps(aip_training_config),77 'n_step':78 10079 }80 resolved_training_input = copy.deepcopy(training_job['training_input'])81 resolved_training_input['args'] = [82 '--examples', _EXAMPLE_LOCATION, '--n-steps', '100', '--model-dir',83 _MODEL_LOCATION84 ]85 self._expected_job_spec = {86 'job_id': self._job_id,87 'training_input': resolved_training_input,88 'labels': self._labels,89 }90 self._mock_api_client = mock.Mock()91 mock_discovery = self.enter_context(92 mock.patch.object(93 discovery,94 'build',95 autospec=True))96 mock_discovery.return_value = self._mock_api_client97 self._setUpTrainingMocks()98 def _setUpTrainingMocks(self):99 self._mock_create = mock.Mock()100 self._mock_api_client.projects().jobs().create = self._mock_create101 self._mock_get = mock.Mock()102 self._mock_api_client.projects().jobs().get.return_value = self._mock_get103 self._mock_get.execute.return_value = {104 'state': 'SUCCEEDED',105 }106 def testRunAipTraining(self):107 aip_executor = ai_platform_training_executor.AiPlatformTrainingExecutor()108 aip_executor.Do(109 input_dict=self._inputs,110 output_dict=self._outputs,111 exec_properties=self._exec_properties)112 self._mock_create.assert_called_once_with(113 body=self._expected_job_spec,114 parent='projects/{}'.format(self._project_id))115 def testRunAipTrainingWithDefaultJobId(self):116 aip_executor = ai_platform_training_executor.AiPlatformTrainingExecutor()117 # Delete job_id in the exec_properties.118 training_config = json_utils.loads(119 self._exec_properties[ai_platform_training_executor.CONFIG_KEY])120 training_config[ai_platform_training_executor.JOB_ID_CONFIG_KEY] = None121 self._exec_properties[ai_platform_training_executor.CONFIG_KEY] = (122 json_utils.dumps(training_config))123 aip_executor.Do(124 input_dict=self._inputs,125 output_dict=self._outputs,126 exec_properties=self._exec_properties)127 self._mock_create.assert_called_once()128 print(self._mock_create.call_args[1])129 print(self._mock_create.call_args[1]['body'])130 self.assertEqual('tfx_',131 self._mock_create.call_args[1]['body']['job_id'][:4])132if __name__ == '__main__':...
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