class TestProjectConfig(unittest.TestCase):
def setUp(self):
project_path = get_file_dir(__file__)
config_file = project_path + '/master.yaml'
self.master = AIFlowMaster(config_file=config_file)
self.master.start()
def tearDown(self):
self.master.stop()
self.master._clear_db()
def test_load_project_config(self):
project_path = get_file_dir(__file__)
set_project_config_file(project_path + "/project.yaml")
project_desc = get_project_description_from(project_path)
self.assertEqual(project_desc.project_config.get_master_uri(),
"localhost:50051")
self.assertIsNone(
project_desc.project_config.get('ai_flow config', None))
self.assertEqual(project_desc.project_config['ai_flow_home'],
'/opt/ai_flow')
self.assertEqual(
project_desc.project_config['ai_flow_job_master.host'],
'localhost')
self.assertEqual(
project_desc.project_config['ai_flow_job_master.port'], 8081)
self.assertEqual(project_desc.project_config['ai_flow_conf'],
'taskmanager.slot=2')
def setUp(self):
project_path = get_file_dir(__file__)
config_file = project_path + '/master.yaml'
self.master = AIFlowMaster(config_file=config_file)
self.master.start()
def setUpClass(cls) -> None:
config_file = test_util.get_master_config_file()
cls.master = AIFlowMaster(config_file=config_file)
cls.master.start()
test_util.set_project_config(__file__)
return os.path.dirname(os.path.dirname(__file__))
def project_config_file():
return project_path() + '/project.yaml'
def master_config_file():
return project_path() + '/master.yaml'
def workflow_config_file():
return project_path() + '/resources/workflow.yaml'
master = AIFlowMaster(config_file=master_config_file())
def master_port():
return master.master_config.get('master_port')
def deploy_path():
return master.master_config.get('scheduler').get('properties').get(
'airflow_deploy_path')
class BaseETETest(unittest.TestCase):
@classmethod
def setUpClass(cls) -> None:
master.start()
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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.
#
import argparse
from ai_flow.application_master.master import AIFlowMaster
import logging
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--config', required=True, help='master config file')
args = parser.parse_args()
logging.info(args.config)
config_file = args.config
master = AIFlowMaster(config_file=config_file)
master.start(is_block=True)
model_meta = af.ModelMeta(name="test", model_type="saved_model")
model_version = af.ModelVersionMeta(version="11111",
model_path="./tmp/saved_model/",
model_metric="./tmp/saved_model/",
model_id=0)
processed = af.predict(
input_data_list=[input_example],
model_info=model_meta,
model_version_info=model_version,
executor=faf.flink_executor.FlinkJavaExecutor(
java_class="com.apache.flink.ai.flow.TestPredict"))
af.write_example(input_data=processed,
example_info=example_2,
exec_args=ExecuteArgs(
batch_properties=batch_args_2,
stream_properties=stream_args_2))
g = af.default_graph()
workflow = af.compile_workflow(project_path=test_util.get_project_path())
print(dumps(list(workflow.jobs.values())[0]))
if __name__ == '__main__':
config_file = test_util.get_master_config_file()
master = AIFlowMaster(config_file=config_file)
master.start()
test_util.set_project_config(__file__)
run_flink_predict_job()
master.stop()
def test_master_start_stop(self):
config = MasterConfig()
config.set_db_uri(db_type=DBType.SQLITE, uri="sqlite:///sql.db")
master = AIFlowMaster(config_file=test_util.get_master_config_file())
master.start(is_block=False)
master.stop()
