From fa9878ab851fb95d5ec4ab0836f4d1c8b64aec16 Mon Sep 17 00:00:00 2001 From: pollfly <75068813+pollfly@users.noreply.github.com> Date: Sun, 5 Dec 2021 11:29:59 +0200 Subject: [PATCH] small edits (#129) --- docs/clearml_agent.md | 4 ++-- docs/deploying_clearml/clearml_server_gcp.md | 2 +- docs/faq.md | 20 +++++++++++-------- docs/fundamentals/hpo.md | 2 +- .../mlops/mlops_first_steps.md | 2 +- docs/webapp/webapp_exp_comparing.md | 12 +++++------ docs/webapp/webapp_exp_track_visual.md | 4 ++-- 7 files changed, 25 insertions(+), 21 deletions(-) diff --git a/docs/clearml_agent.md b/docs/clearml_agent.md index de1eec74..2d85e743 100644 --- a/docs/clearml_agent.md +++ b/docs/clearml_agent.md @@ -581,7 +581,7 @@ Do not enqueue training or inference tasks into the services queue. They will pu ### Setting Server Credentials 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). 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 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 diff --git a/docs/deploying_clearml/clearml_server_gcp.md b/docs/deploying_clearml/clearml_server_gcp.md index f1cd8952..536ed7aa 100644 --- a/docs/deploying_clearml/clearml_server_gcp.md +++ b/docs/deploying_clearml/clearml_server_gcp.md @@ -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). -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 If **ClearML Server** is being reinstalled, we recommend clearing browser cookies for **ClearML Server**. For example, diff --git a/docs/faq.md b/docs/faq.md index b49623da..7d70c0cf 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -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`: - 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 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: +```python +# AWS S3 bucket +task = Task.init(project_name, task_name, output_uri="s3://bucket-name/folder") - # AWS S3 bucket - task = Task.init(project_name, task_name, output_uri="s3://bucket-name/folder") - - # Google Cloud Storage bucket - 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, see [ClearML Configuration Reference](configs/clearml_conf.md). diff --git a/docs/fundamentals/hpo.md b/docs/fundamentals/hpo.md index 822b0892..76074f35 100644 --- a/docs/fundamentals/hpo.md +++ b/docs/fundamentals/hpo.md @@ -120,5 +120,5 @@ For more information about `HyperParameterOptimizer` and supported optimization ## 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. diff --git a/docs/getting_started/mlops/mlops_first_steps.md b/docs/getting_started/mlops/mlops_first_steps.md index c0b55a38..1653a07e 100644 --- a/docs/getting_started/mlops/mlops_first_steps.md +++ b/docs/getting_started/mlops/mlops_first_steps.md @@ -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. -### First steps +### First Steps #### 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) method. For example: diff --git a/docs/webapp/webapp_exp_comparing.md b/docs/webapp/webapp_exp_comparing.md index b1736370..a3ad7e03 100644 --- a/docs/webapp/webapp_exp_comparing.md +++ b/docs/webapp/webapp_exp_comparing.md @@ -57,8 +57,8 @@ sorted by sections. ### To Locate the Source Differences: -* Click the **DETAILS** tab **>** Expand highlighted sections, or, in the header, click Left arrow - (Previous diff) or Right arrow (Next diff). +* Click the **DETAILS** tab **>** Expand highlighted sections, or, in the header, click Up arrow + (Previous diff) or Down arrow (Next diff). For example, in the image below, expanding **ARTIFACTS** **>** **Output Model** **>** **Model** shows that the model ID 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. To show only differences, move the **Hide Identical Fields** slider to on. 1. Locate differences by either: - * Clicking Left arrow (Previous diff) or - Right arrow (Next diff). + * Clicking Up arrow (Previous diff) or + Down arrow (Next diff). * Scrolling to see highlighted hyperparameters. For example, expanding **General** shows that the `batch_size` and `epochs` differ between the experiments. @@ -253,8 +253,8 @@ an experiment, click Trash, or - the next difference Right arrow. +* Find the previous difference Up arrow, or + the next difference Down arrow. diff --git a/docs/webapp/webapp_exp_track_visual.md b/docs/webapp/webapp_exp_track_visual.md index f534c409..d2585346 100644 --- a/docs/webapp/webapp_exp_track_visual.md +++ b/docs/webapp/webapp_exp_track_visual.md @@ -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**. 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)) -parameter in `Task.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`). :::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.