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4
docs/clearml_agent.md
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@ -581,7 +581,7 @@ Do not enqueue training or inference tasks into the services queue. They will pu
### Setting Server Credentials ### Setting Server Credentials
Self hosted [ClearML Server](deploying_clearml/clearml_server.md) comes by default with a services queue. Self hosted [ClearML Server](deploying_clearml/clearml_server.md) comes by default with a services queue.
By default, the server is open and does not require username and password, but it can be [password protected](deploying_clearml/clearml_server_security#user-access-security). By default, the server is open and does not require username and password, but it can be [password-protected](deploying_clearml/clearml_server_security#user-access-security).
In case it is password-protected, the services agent will need to be configured with server credentials (associated with a user). In case it is password-protected, the services agent will need to be configured with server credentials (associated with a user).
To do that, set these environment variables on the ClearML Server machine with the appropriate credentials: To do that, set these environment variables on the ClearML Server machine with the appropriate credentials:
@ -630,7 +630,7 @@ It's possible to add the Docker container as the base Docker image to a Task (ex
ClearML Agent can run on a [Google Colab](https://colab.research.google.com/) instance. This helps users to leverage ClearML Agent can run on a [Google Colab](https://colab.research.google.com/) instance. This helps users to leverage
compute resources provided by Google Colab and send experiments for execution on it. compute resources provided by Google Colab and send experiments for execution on it.
Check out [this](guides/ide/google_colab.md) tutorial on how to run a ClearML Agent on Google Colab! Check out [this tutorial](guides/ide/google_colab.md) on how to run a ClearML Agent on Google Colab!
## Scheduling Working Hours ## Scheduling Working Hours

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docs/deploying_clearml/clearml_server_gcp.md
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@ -12,7 +12,7 @@ provides custom images for each released version of **ClearML Server**. For a li
After deploying **ClearML Server**, configure the **ClearML Python Package** for it, see [Configuring ClearML for ClearML Server](clearml_config_for_clearml_server.md). After deploying **ClearML Server**, configure the **ClearML Python Package** for it, see [Configuring ClearML for ClearML Server](clearml_config_for_clearml_server.md).
For information about upgrading **ClearML server on GCP, see [here](upgrade_server_gcp.md). For information about upgrading ClearML server on GCP, see [here](upgrade_server_gcp.md).
:::important :::important
If **ClearML Server** is being reinstalled, we recommend clearing browser cookies for **ClearML Server**. For example, If **ClearML Server** is being reinstalled, we recommend clearing browser cookies for **ClearML Server**. For example,

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docs/faq.md
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@ -603,20 +603,24 @@ providing the `output_uri` parameter allows you to specify the location in which
For example, to store model checkpoints (snapshots) in `/mnt/shared/folder`: For example, to store model checkpoints (snapshots) in `/mnt/shared/folder`:
task = Task.init(project_name, task_name, output_uri="/mnt/shared/folder") ```python
task = Task.init(project_name, task_name, output_uri="/mnt/shared/folder")
```
ClearML will copy all stored snapshots into a subfolder under `/mnt/shared/folder`. The subfolder's name will contain ClearML will copy all stored snapshots into a subfolder under `/mnt/shared/folder`. The subfolder's name will contain
the experiment's ID. If the experiment's ID is `6ea4f0b56d994320a713aeaf13a86d9d`, the following folder will be used: the experiment's ID. If the experiment's ID is `6ea4f0b56d994320a713aeaf13a86d9d`, the following folder will be used:
```
`/mnt/shared/folder/task.6ea4f0b56d994320a713aeaf13a86d9d/models/` /mnt/shared/folder/task.6ea4f0b56d994320a713aeaf13a86d9d/models/
```
ClearML supports other storage types for `output_uri`, including: ClearML supports other storage types for `output_uri`, including:
```python
# AWS S3 bucket
task = Task.init(project_name, task_name, output_uri="s3://bucket-name/folder")
# AWS S3 bucket # Google Cloud Storage bucket
task = Task.init(project_name, task_name, output_uri="s3://bucket-name/folder") task = Task.init(project_name, task_name, output_uri="gs://bucket-name/folder")
```
# Google Cloud Storage bucket
task = Task.init(project_name, task_name, output_uri="gs://bucket-name/folder")
To use Cloud storage with ClearML, configure the storage credentials in your `~/clearml.conf`. For detailed information, To use Cloud storage with ClearML, configure the storage credentials in your `~/clearml.conf`. For detailed information,
see [ClearML Configuration Reference](configs/clearml_conf.md). see [ClearML Configuration Reference](configs/clearml_conf.md).

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docs/fundamentals/hpo.md
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@ -120,5 +120,5 @@ For more information about `HyperParameterOptimizer` and supported optimization
## Tutorial ## Tutorial
Check out the [Hyperparameter Optimization](../guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt.md) tutorial for a step-by-step guide. Check out the [Hyperparameter Optimization tutorial](../guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt.md) for a step-by-step guide.

2
docs/getting_started/mlops/mlops_first_steps.md
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@ -87,7 +87,7 @@ experiment, and the experiment can be [tracked and its results visualized](../..
The cloning, modifying, and enqueuing actions described above can also be performed programmatically. The cloning, modifying, and enqueuing actions described above can also be performed programmatically.
### First steps ### First Steps
#### Access Previously Executed Experiments #### Access Previously Executed Experiments
All Tasks in the system can be accessed through their unique Task ID, or based on their properties using the [`Task.get_task`](../../references/sdk/task.md#taskget_task) All Tasks in the system can be accessed through their unique Task ID, or based on their properties using the [`Task.get_task`](../../references/sdk/task.md#taskget_task)
method. For example: method. For example:

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docs/webapp/webapp_exp_comparing.md
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@ -57,8 +57,8 @@ sorted by sections.
### To Locate the Source Differences: ### To Locate the Source Differences:
* Click the **DETAILS** tab **>** Expand highlighted sections, or, in the header, click <img src="/docs/latest/icons/ico-previous-diff.svg" alt="Left arrow" className="icon size-md" /> * Click the **DETAILS** tab **>** Expand highlighted sections, or, in the header, click <img src="/docs/latest/icons/ico-previous-diff.svg" alt="Up arrow" className="icon size-md" />
(Previous diff) or <img src="/docs/latest/icons/ico-next-diff.svg" alt="Right arrow" className="icon size-md space-sm" /> (Next diff). (Previous diff) or <img src="/docs/latest/icons/ico-next-diff.svg" alt="Down arrow" className="icon size-md space-sm" /> (Next diff).
For example, in the image below, expanding **ARTIFACTS** **>** **Output Model** **>** **Model** shows that the model ID For example, in the image below, expanding **ARTIFACTS** **>** **Output Model** **>** **Model** shows that the model ID
and name are different. and name are different.
@ -81,8 +81,8 @@ The Values mode is a side-by-side comparison that shows hyperparameter value dif
1. In the dropdown menu (on the upper left, next to **+ Add Experiments**), choose **Values**. 1. In the dropdown menu (on the upper left, next to **+ Add Experiments**), choose **Values**.
1. To show only differences, move the **Hide Identical Fields** slider to on. 1. To show only differences, move the **Hide Identical Fields** slider to on.
1. Locate differences by either: 1. Locate differences by either:
* Clicking <img src="/docs/latest/icons/ico-previous-diff.svg" alt="Left arrow" className="icon size-md space-sm" /> (Previous diff) or * Clicking <img src="/docs/latest/icons/ico-previous-diff.svg" alt="Up arrow" className="icon size-md space-sm" /> (Previous diff) or
<img src="/docs/latest/icons/ico-next-diff.svg" alt="Right arrow" className="icon size-md space-sm" /> (Next diff). <img src="/docs/latest/icons/ico-next-diff.svg" alt="Down arrow" className="icon size-md space-sm" /> (Next diff).
* Scrolling to see highlighted hyperparameters. * Scrolling to see highlighted hyperparameters.
For example, expanding **General** shows that the `batch_size` and `epochs` differ between the experiments. For example, expanding **General** shows that the `batch_size` and `epochs` differ between the experiments.
@ -253,8 +253,8 @@ an experiment, click <img src="/docs/latest/icons/ico-trash.svg" alt="Trash" cla
### Finding the Next or Previous Difference ### Finding the Next or Previous Difference
* Find the previous difference <img src="/docs/latest/icons/ico-previous-diff.svg" alt="Left arrow" className="icon size-md space-sm" />, or * Find the previous difference <img src="/docs/latest/icons/ico-previous-diff.svg" alt="Up arrow" className="icon size-md space-sm" />, or
the next difference <img src="/docs/latest/icons/ico-next-diff.svg" alt="Right arrow" className="icon size-md space-sm" />. the next difference <img src="/docs/latest/icons/ico-next-diff.svg" alt="Down arrow" className="icon size-md space-sm" />.

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docs/webapp/webapp_exp_track_visual.md
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@ -205,8 +205,8 @@ except experiments whose status is *Published* (read-only).
**ClearML** tracks experiment (Task) model configuration objects, which appear in **Configuration Objects** **>** **General**. **ClearML** tracks experiment (Task) model configuration objects, which appear in **Configuration Objects** **>** **General**.
These objects include those that are automatically tracked, and those connected to a Task in code (see [Task.connect_configuration](../references/sdk/task.md#connect_configuration)). These objects include those that are automatically tracked, and those connected to a Task in code (see [Task.connect_configuration](../references/sdk/task.md#connect_configuration)).
**ClearML** supports providing a name for a Task model configuration object (see the [name](../references/sdk/task.md#connect_configuration)) **ClearML** supports providing a name for a Task model configuration object (see the [name](../references/sdk/task.md#connect_configuration)
parameter in `Task.connect_configuration`. parameter in `Task.connect_configuration`).
:::important :::important
In older versions of **ClearML Server**, the Task model configuration appeared in the **ARTIFACTS** tab, **MODEL CONFIGURATION** section. Task model configurations now appear in the **Configuration Objects** section, in the **CONFIGURATION** tab. In older versions of **ClearML Server**, the Task model configuration appeared in the **ARTIFACTS** tab, **MODEL CONFIGURATION** section. Task model configurations now appear in the **Configuration Objects** section, in the **CONFIGURATION** tab.