65 lines
2.3 KiB
Python
65 lines
2.3 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_dataset_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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description: str = None,
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tables_dataset_metadata: dict = {},
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retry=None, #=google.api_core.gapic_v1.method.DEFAULT,
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timeout: float = None, #=google.api_core.gapic_v1.method.DEFAULT,
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metadata: dict = None,
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) -> NamedTuple('Outputs', [('dataset_path', str), ('create_time', str), ('dataset_id', str), ('dataset_url', 'URI')]):
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'''automl_create_dataset_for_tables creates an empty Dataset for AutoML tables
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'''
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import google
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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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dataset_dict = {
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'display_name': display_name,
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'description': description,
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'tables_dataset_metadata': tables_dataset_metadata,
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}
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dataset = client.create_dataset(
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location_path,
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dataset_dict,
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retry or google.api_core.gapic_v1.method.DEFAULT,
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timeout or google.api_core.gapic_v1.method.DEFAULT,
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metadata,
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)
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print(dataset)
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dataset_id = dataset.name.rsplit('/', 1)[-1]
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dataset_url = 'https://console.cloud.google.com/automl-tables/locations/{region}/datasets/{dataset_id}/schemav2?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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)
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return (dataset.name, str(dataset.create_time), dataset_id, dataset_url)
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if __name__ == '__main__':
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import kfp
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kfp.components.func_to_container_op(
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automl_create_dataset_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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)
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