pipelines/components/gcp/automl/create_model_for_tables/component.py

72 lines
2.9 KiB
Python

# Copyright 2019 The Kubeflow Authors
#
# 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.
from typing import NamedTuple
def automl_create_model_for_tables(
gcp_project_id: str,
gcp_region: str,
display_name: str,
dataset_id: str,
target_column_path: str = None,
input_feature_column_paths: list = None,
optimization_objective: str = 'MAXIMIZE_AU_PRC',
train_budget_milli_node_hours: int = 1000,
) -> NamedTuple('Outputs', [('model_path', str), ('model_id', str), ('model_page_url', 'URI'),]):
from google.cloud import automl
client = automl.AutoMlClient()
location_path = client.location_path(gcp_project_id, gcp_region)
model_dict = {
'display_name': display_name,
'dataset_id': dataset_id,
'tables_model_metadata': {
'target_column_spec': automl.types.ColumnSpec(name=target_column_path),
'input_feature_column_specs': [automl.types.ColumnSpec(name=path) for path in input_feature_column_paths] if input_feature_column_paths else None,
'optimization_objective': optimization_objective,
'train_budget_milli_node_hours': train_budget_milli_node_hours,
},
}
create_model_response = client.create_model(location_path, model_dict)
print('Create model operation: {}'.format(create_model_response.operation))
result = create_model_response.result()
print(result)
model_name = result.name
model_id = model_name.rsplit('/', 1)[-1]
model_url = 'https://console.cloud.google.com/automl-tables/locations/{region}/datasets/{dataset_id};modelId={model_id};task=basic/train?project={project_id}'.format(
project_id=gcp_project_id,
region=gcp_region,
dataset_id=dataset_id,
model_id=model_id,
)
return (model_name, model_id, model_url)
if __name__ == '__main__':
from kfp.components import create_component_from_func
automl_create_model_for_tables_op = create_component_from_func(
automl_create_model_for_tables,
output_component_file='component.yaml',
base_image='python:3.7',
packages_to_install=['google-cloud-automl==0.4.0'],
annotations={
"author": "Alexey Volkov <alexey.volkov@ark-kun.com>",
"canonical_location": "https://raw.githubusercontent.com/Ark-kun/pipeline_components/master/components/gcp/automl/create_model_for_tables/component.yaml",
},
)