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25 lines
1.4 KiB
Markdown
25 lines
1.4 KiB
Markdown
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title: Building Pipelines
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---
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Pipelines are a way to streamline and connect multiple processes, plugging the output of one process as the input of another.
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ClearML Pipelines are implemented by a Controller Task that holds the logic of the pipeline steps' interactions. The
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execution logic controls which step to launch based on parent steps completing their execution. Depending on the
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specifications laid out in the controller task, a step's parameters can be overridden, enabling users to leverage other
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steps' execution products such as artifacts and parameters.
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When run, the controller will sequentially launch the pipeline steps. Pipelines can be executed locally or
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on any machine using the [clearml-agent](../clearml_agent.md).
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ClearML pipelines are created from code using one of the following:
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* [PipelineController class](../pipelines/pipelines_sdk_tasks.md) - A pythonic interface for defining and configuring the
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pipeline controller and its steps. The controller and steps can be functions in your Python code or existing ClearML tasks.
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* [PipelineDecorator class](../pipelines/pipelines_sdk_function_decorators.md) - A set of Python decorators which transform
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your functions into the pipeline controller and steps
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For more information, see [ClearML Pipelines](../pipelines/pipelines.md).
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