Example Airflow DAG for Google ML Engine service.
Module Contents
Attributes
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tests.system.providers.google.cloud.ml_engine.example_mlengine.PROJECT_ID[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.ENV_ID[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.DAG_ID = example_gcp_mlengine[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.PREDICT_FILE_NAME = predict.json[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.MODEL_NAME[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.BUCKET_NAME[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.BUCKET_PATH[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.JOB_DIR[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.SAVED_MODEL_PATH[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.PREDICTION_INPUT[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.PREDICTION_OUTPUT[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.TRAINER_URI = gs://system-tests-resources/example_gcp_mlengine/trainer-0.1.tar.gz[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.TRAINER_PY_MODULE = trainer.task[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.SUMMARY_TMP[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.SUMMARY_STAGING[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.BASE_DIR[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.PATH_TO_PREDICT_FILE[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.generate_model_predict_input_data()[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.create_bucket[source]
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tests.system.providers.google.cloud.ml_engine.example_mlengine.test_run[source]