From c4049bbb11aa0bdc16d4395f1edf345e9bafcc48 Mon Sep 17 00:00:00 2001 From: pollfly <75068813+pollfly@users.noreply.github.com> Date: Tue, 23 Aug 2022 15:18:22 +0300 Subject: [PATCH] Add task type decriptions (#317) --- docs/fundamentals/task.md | 27 +++++++++++++++------------ 1 file changed, 15 insertions(+), 12 deletions(-) diff --git a/docs/fundamentals/task.md b/docs/fundamentals/task.md index 2eb246b3..5c4d49a7 100644 --- a/docs/fundamentals/task.md +++ b/docs/fundamentals/task.md @@ -86,19 +86,22 @@ they are attached to, and then retrieving the artifact with one of its following See more details in the [Using Artifacts example](https://github.com/allegroai/clearml/blob/master/examples/reporting/using_artifacts_example.py). ## Task Types -Tasks have a *type* attribute, which denotes their purpose (Training / Testing / Data processing). This helps to further +Tasks have a *type* attribute, which denotes their purpose (e.g. training / testing / data processing). This helps to further organize projects and ensure tasks are easy to [search and find](../clearml_sdk/task_sdk.md#querying--searching-tasks). -The default task type is *training*. Available task types are: -- Experimentation - - - *training*, *testing*, *inference* - -- Other workflows - - - *controller*, *optimizer* - - *monitor*, *service*, *application* - - *data_processing*, *qc* - - *custom* +Available task types are: +* *training* (default) - Training a model +* *testing* - Testing a component, for example model performance +* *inference* - Model inference job (e.g. offline / batch model execution) +* *controller* - A task that lays out the logic for other tasks’ interactions, manual or automatic (e.g. a pipeline + controller) +* *optimizer* - A specific type of controller for optimization tasks (e.g. [hyperparameter optimization](hpo.md)) +* *service* - Long lasting or recurring service (e.g. server cleanup, auto ingress, sync services etc) +* *monitor* - A specific type of service for monitoring +* *application* - A task implementing custom applicative logic, like [auto-scaler](../guides/services/aws_autoscaler.md) + or [clearml-session](../apps/clearml_session.md) +* *data_processing* - Any data ingress / preprocessing (see [ClearML Data](../clearml_data/clearml_data.md)) +* *qc* - Quality Control (e.g. evaluating model performance vs. blind dataset) +* *custom* - A task not matching any of the above ## Task Lifecycle