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pollfly
2024-03-12 11:25:00 +02:00
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5 changed files with 12 additions and 8 deletions
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10
docs/getting_started/mlops/mlops_second_steps.md
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@@ -31,6 +31,8 @@ The second step is to preprocess the data. First access the data, then modify it
and lastly create a new version of the data.
```python
from clearml import Task, Dataset
# create a task for the data processing part
task = Task.init(project_name='data', task_name='create', task_type='data_processing')
@@ -93,6 +95,8 @@ will first run the first and then run the second.
It is important to remember that pipelines are Tasks by themselves and can also be automated by other pipelines (i.e. pipelines of pipelines).
```python
from clearml import PipelineController
pipe = PipelineController(
project='data',
name='pipeline demo',
@@ -112,6 +116,6 @@ pipe.add_step(
)
```
We can also pass the parameters from one step to the other (for example `Task.id`).
In addition to pipelines made up of Task steps, ClearML also supports pipelines consisting of function steps. See more in the
full pipeline documentation [here](../../pipelines/pipelines.md).
You can also pass the parameters from one step to the other (for example `Task.id`).
In addition to pipelines made up of Task steps, ClearML also supports pipelines consisting of function steps. For more
information, see the [full pipeline documentation](../../pipelines/pipelines.md).