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69 lines
2.3 KiB
69 lines
2.3 KiB
# Licensed to the Apache Software Foundation (ASF) under one |
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# or more contributor license agreements. See the NOTICE file |
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# distributed with this work for additional information |
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# regarding copyright ownership. The ASF licenses this file |
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# to you under the Apache License, Version 2.0 (the |
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# "License"); you may not use this file except in compliance |
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# with the License. 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, |
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# software distributed under the License is distributed on an |
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
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# KIND, either express or implied. See the License for the |
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# specific language governing permissions and limitations |
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# under the License. |
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# Define variable `mlflow_tracking_uri` |
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mlflow_tracking_uri: &mlflow_tracking_uri "http://127.0.0.1:5000" |
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# Define the workflow |
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workflow: |
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name: "MLflow" |
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# Define the tasks under the workflow |
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tasks: |
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- name: train_xgboost_native |
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task_type: MLFlowProjectsCustom |
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repository: https://github.com/mlflow/mlflow#examples/xgboost/xgboost_native |
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mlflow_tracking_uri: *mlflow_tracking_uri |
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parameters: -P learning_rate=0.2 -P colsample_bytree=0.8 -P subsample=0.9 |
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experiment_name: xgboost |
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- name: train_automl |
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task_type: MLFlowProjectsAutoML |
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mlflow_tracking_uri: *mlflow_tracking_uri |
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parameters: time_budget=30;estimator_list=['lgbm'] |
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experiment_name: automl_iris |
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model_name: iris_A |
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automl_tool: flaml |
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data_path: /data/examples/iris |
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- name: deploy_docker |
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task_type: MLflowModels |
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deps: [train_automl] |
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model_uri: models:/iris_A/Production |
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mlflow_tracking_uri: *mlflow_tracking_uri |
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deploy_mode: DOCKER |
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port: 7002 |
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- name: train_basic_algorithm |
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task_type: MLFlowProjectsBasicAlgorithm |
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mlflow_tracking_uri: *mlflow_tracking_uri |
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parameters: n_estimators=200;learning_rate=0.2 |
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experiment_name: basic_algorithm_iris |
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model_name: iris_B |
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algorithm: lightgbm |
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data_path: /data/examples/iris |
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search_params: max_depth=[5, 10];n_estimators=[100, 200] |
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- name: deploy_mlflow |
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deps: [train_basic_algorithm] |
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task_type: MLflowModels |
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model_uri: models:/iris_B/Production |
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mlflow_tracking_uri: *mlflow_tracking_uri |
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deploy_mode: MLFLOW |
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port: 7001 |
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