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4
docs/clearml_agent.md
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@ -17,7 +17,7 @@ title: ClearML Agent
**ClearML Agent** is a virtual environment and execution manager for DL / ML solutions on GPU machines. It integrates with the **ClearML Python Package** and ClearML Server to provide a full AI cluster solution. <br/> **ClearML Agent** is a virtual environment and execution manager for DL / ML solutions on GPU machines. It integrates with the **ClearML Python Package** and ClearML Server to provide a full AI cluster solution. <br/>
Its main focus is around: Its main focus is around:
- Reproducing tasks, including their complete environments. - Reproducing task runs, including their complete environments.
- Scaling workflows on multiple target machines. - Scaling workflows on multiple target machines.
ClearML Agent executes a task or other workflow by reproducing the state of the code from the original machine ClearML Agent executes a task or other workflow by reproducing the state of the code from the original machine
@ -46,7 +46,7 @@ install Python, so make sure to use a container or environment with the version
While the agent is running, it continuously reports system metrics to the ClearML Server (these can be monitored in the While the agent is running, it continuously reports system metrics to the ClearML Server (these can be monitored in the
[**Orchestration**](webapp/webapp_workers_queues.md) page). [**Orchestration**](webapp/webapp_workers_queues.md) page).
Continue using ClearML Agent once it is running on a target machine. Reproduce tasks and execute Continue using ClearML Agent once it is running on a target machine. Reproducing task runs and execute
automated workflows in one (or both) of the following ways: automated workflows in one (or both) of the following ways:
* Programmatically (using [`Task.enqueue()`](references/sdk/task.md#taskenqueue) or [`Task.execute_remotely()`](references/sdk/task.md#execute_remotely)) * Programmatically (using [`Task.enqueue()`](references/sdk/task.md#taskenqueue) or [`Task.execute_remotely()`](references/sdk/task.md#execute_remotely))
* Through the ClearML Web UI (without working directly with code), by cloning tasks and enqueuing them to the * Through the ClearML Web UI (without working directly with code), by cloning tasks and enqueuing them to the

2
docs/getting_started/remote_execution.md
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@ -14,7 +14,7 @@ powerful remote machine. This is useful for:
* Managing execution through ClearML's queue system. * Managing execution through ClearML's queue system.
This guide focuses on transitioning a locally executed process to a remote machine for scalable execution. To learn how This guide focuses on transitioning a locally executed process to a remote machine for scalable execution. To learn how
to reproduce a previously executed process on a remote machine, see [Reproducing Tasks](reproduce_tasks.md). to reproduce a previously executed process on a remote machine, see [Reproducing Task Runs](reproduce_tasks.md).
## Running a Task Remotely ## Running a Task Remotely

2
docs/getting_started/reproduce_tasks.md
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@ -1,5 +1,5 @@
--- ---
title: Reproducing Tasks title: Reproducing Task Runs
--- ---
:::note :::note

4
docs/integrations/autokeras.md
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@ -77,7 +77,7 @@ See more information about explicitly logging information to a ClearML Task:
See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md). See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md).
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -93,7 +93,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/catboost.md
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@ -76,7 +76,7 @@ See more information about explicitly logging information to a ClearML Task:
See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md). See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md).
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -92,7 +92,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/fastai.md
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@ -75,7 +75,7 @@ See more information about explicitly logging information to a ClearML Task:
See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md). See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md).
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -91,7 +91,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/keras.md
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@ -87,7 +87,7 @@ and debug samples, plots, and scalars logged to TensorBoard
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -103,7 +103,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/lightgbm.md
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@ -76,7 +76,7 @@ See more information about explicitly logging information to a ClearML Task:
See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md). See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md).
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -92,7 +92,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/megengine.md
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@ -72,7 +72,7 @@ See more information about explicitly logging information to a ClearML Task:
See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md). See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md).
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -88,7 +88,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/pytorch.md
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@ -97,7 +97,7 @@ additional tools, like argparse, TensorBoard, and matplotlib:
* [PyTorch Distributed](../guides/frameworks/pytorch/pytorch_distributed_example.md) - Demonstrates using ClearML with the [PyTorch Distributed Communications Package (`torch.distributed`)](https://pytorch.org/tutorials/beginner/dist_overview.html) * [PyTorch Distributed](../guides/frameworks/pytorch/pytorch_distributed_example.md) - Demonstrates using ClearML with the [PyTorch Distributed Communications Package (`torch.distributed`)](https://pytorch.org/tutorials/beginner/dist_overview.html)
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -113,7 +113,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/pytorch_lightning.md
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@ -102,7 +102,7 @@ See more information about explicitly logging information to a ClearML Task:
See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md). See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md).
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -118,7 +118,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md), to
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/scikit_learn.md
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@ -78,7 +78,7 @@ additional tools, like Matplotlib:
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -94,7 +94,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/tao.md
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@ -94,7 +94,7 @@ You can view all of this captured information in the [ClearML Web UI](../webapp/
![TAO UI plots](../img/integrations_nvidia_tao_plots.png) ![TAO UI plots](../img/integrations_nvidia_tao_plots.png)
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is
enqueued, the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the enqueued, the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -111,7 +111,7 @@ cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents:
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/tensorflow.md
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@ -89,7 +89,7 @@ TensorBoard scalars, histograms, images, and text, as well as all console output
ClearML's automatic logging of parameters defined using `absl.flags` ClearML's automatic logging of parameters defined using `absl.flags`
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -105,7 +105,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

2
docs/integrations/transformers.md
View File

@ -60,7 +60,7 @@ You can also select multiple tasks and directly [compare](../webapp/webapp_exp_c
See an example of Transformers and ClearML in action [here](../guides/frameworks/huggingface/transformers.md). See an example of Transformers and ClearML in action [here](../guides/frameworks/huggingface/transformers.md).
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is
enqueued, the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the enqueued, the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.

4
docs/integrations/xgboost.md
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@ -103,7 +103,7 @@ additional tools, like Matplotlib and scikit-learn:
* [XGBoost and scikit-learn](../guides/frameworks/xgboost/xgboost_sample.md) - Demonstrates ClearML automatic logging of XGBoost scalars and models * [XGBoost and scikit-learn](../guides/frameworks/xgboost/xgboost_sample.md) - Demonstrates ClearML automatic logging of XGBoost scalars and models
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued, uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -119,7 +119,7 @@ Use the ClearML [Autoscalers](../cloud_autoscaling/autoscaling_overview.md) to h
cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents: the autoscaler automatically spins up
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

4
docs/integrations/yolov5.md
View File

@ -150,7 +150,7 @@ python train.py --img 640 --batch 16 --epochs 3 --data clearml://<your_dataset_i
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is
enqueued, the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the enqueued, the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -167,7 +167,7 @@ cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents:
and shuts down instances as needed, according to a resource budget that you set. and shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif#light-mode-only)
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5_dark.gif#dark-mode-only)

6
docs/integrations/yolov8.md
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@ -95,7 +95,7 @@ Add custom columns to the table, such as mAP values, so you can easily sort and
You can also select multiple tasks and directly [compare](../webapp/webapp_exp_comparing.md) them. You can also select multiple tasks and directly [compare](../webapp/webapp_exp_comparing.md) them.
## Remote Execution ## Remote Execution
ClearML logs all the information required to reproduce a task on a different machine (installed packages, ClearML logs all the information required to reproduce a task run on a different machine (installed packages,
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is
enqueued, the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the enqueued, the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
task manager. task manager.
@ -112,9 +112,9 @@ cloud of your choice (AWS, GCP, Azure) and automatically deploy ClearML agents:
shuts down instances as needed, according to a resource budget that you set. shuts down instances as needed, according to a resource budget that you set.
### Reproducing Tasks ### Reproducing Task Runs
ClearML logs all the information required to reproduce a task, but you may also want to change a few parameters ClearML logs all the information required to reproduce a task run, but you may also want to change a few parameters
and task details when you re-run it, which you can do through ClearML's UI. and task details when you re-run it, which you can do through ClearML's UI.
In order to be able to override parameters via the UI, In order to be able to override parameters via the UI,

4
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@ -1,8 +1,8 @@
--- ---
title: Reproducing Tasks title: Reproducing Task Runs
--- ---
Reproduce tasks on local or remote machines in one of the following ways: Reproducing task runs on local or remote machines in one of the following ways:
* Cloning any task - Make an exact copy, while maintaining the original task * Cloning any task - Make an exact copy, while maintaining the original task
* Resetting a task whose status is not *Published* - Delete the previous run's logs and output * Resetting a task whose status is not *Published* - Delete the previous run's logs and output