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