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Fix pipeline code snippets (#118)
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@ -29,7 +29,7 @@ and lastly we want to create a new version of the data.
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```python
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```python
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# create a task for the data processing part
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# create a task for the data processing part
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task = Task.init(project_name='data', task_name='ingest', task_type='data_processing')
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task = Task.init(project_name='data', task_name='create', task_type='data_processing')
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# get the v1 dataset
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# get the v1 dataset
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dataset = Dataset.get(dataset_project='data', dataset_name='dataset_v1')
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dataset = Dataset.get(dataset_project='data', dataset_name='dataset_v1')
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@ -86,20 +86,24 @@ It is important to remember that pipelines are Tasks by themselves and can also
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```python
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```python
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pipe = PipelineController(
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pipe = PipelineController(
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always_create_task=True,
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project='data',
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pipeline_project='data', pipeline_name='pipeline demo',
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name='pipeline demo',
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version="1.0"
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)
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)
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pipe.add_step(
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pipe.add_step(
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name='step 1 data',
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name='step 1 data',
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base_task_id='cbc84a74288e459c874b54998d650214', # Put the task ID here
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base_project_name='data',
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base_task_name='create'
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)
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)
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pipe.add_step(
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pipe.add_step(
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name='step 2 train',
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name='step 2 train',
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parents=['step 1 data', ],
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parents=['step 1 data', ],
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base_task_id='cbc84a74288e459c874b54998d650214', # Put the task ID here
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base_project_name='data',
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base_task_name='ingest'
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)
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)
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```
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```
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We could also pass the parameters from one step to the other (for example `Task.id`).
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We could also pass the parameters from one step to the other (for example `Task.id`).
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See more in the full pipeline documentation [here](../../fundamentals/pipelines.md).
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In addition to pipelines made up of Task steps, ClearML also supports pipelines consisting of function steps. See more in the
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full pipeline documentation [here](../../fundamentals/pipelines.md).
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