56 lines
2.0 KiB
Python
56 lines
2.0 KiB
Python
# Copyright 2021 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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import kfp.deprecated.dsl as dsl
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from kfp.deprecated.components import create_component_from_func
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# Advanced function
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# Demonstrates imports, helper functions and multiple outputs
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from typing import NamedTuple
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@create_component_from_func
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def roc_visualization(roc_csv_uri: str='https://raw.githubusercontent.com/kubeflow/pipelines/master/samples/core/visualization/roc.csv') -> NamedTuple('VisualizationOutput', [('mlpipeline_ui_metadata', 'UI_metadata')]):
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"""Provide roc curve csv file to visualize as metrics."""
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import json
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metadata = {
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'outputs': [{
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'type': 'roc',
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'format': 'csv',
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'schema': [
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{'name': 'fpr', 'type': 'NUMBER'},
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{'name': 'tpr', 'type': 'NUMBER'},
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{'name': 'thresholds', 'type': 'NUMBER'},
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],
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'source': roc_csv_uri
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}]
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}
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from collections import namedtuple
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visualization_output = namedtuple('VisualizationOutput', [
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'mlpipeline_ui_metadata'])
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return visualization_output(json.dumps(metadata))
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@dsl.pipeline(
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name='roc-curve-pipeline',
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description='A sample pipeline to generate ROC Curve for UI visualization.'
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)
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def roc_curve_pipeline():
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roc_visualization_task = roc_visualization()
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# You can also upload samples/core/visualization/roc.csv to Google Cloud Storage.
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# And call the component function with gcs path parameter like below:
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# roc_visualization_task2 = roc_visualization('gs://<bucket-name>/<path>/roc.csv')
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