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25 lines
1.0 KiB
Python
25 lines
1.0 KiB
Python
from trains import Task
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from trains.automation.controller import PipelineController
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task = Task.init(project_name='examples', task_name='pipeline demo', task_type=Task.TaskTypes.controller)
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pipe = PipelineController(default_execution_queue='default')
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pipe.add_step(name='stage_data', base_task_project='examples', base_task_name='pipeline step 1 dataset artifact')
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pipe.add_step(name='stage_process', parents=['stage_data', ],
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base_task_project='examples', base_task_name='pipeline step 2 process dataset',
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parameter_override={'General/dataset_url': '${stage_data.artifacts.dataset.url}',
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'General/test_size': '0.25'})
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pipe.add_step(name='stage_train', parents=['stage_process', ],
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base_task_project='examples', base_task_name='pipeline step 3 train model',
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parameter_override={'General/dataset_task_id': '${stage_process.id}'})
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# Starting the pipeline (in the background)
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pipe.start()
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# Wait until pipeline terminates
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pipe.wait()
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# cleanup everything
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pipe.stop()
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print('done')
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