Small edits (#901)

2025-03-03 02:32:49 +00:00 · 2024-08-12 16:04:50 +03:00 · 2024-08-12 16:04:50 +03:00 · 8b94fa6c1a
commit 8b94fa6c1a
parent 3021efd45c
17 changed files with 67 additions and 58 deletions
--- a/docs/faq.md
+++ b/docs/faq.md
@ -362,7 +362,7 @@ Your firewall may be preventing the connection. Try one of the following solutio
 * Disable certificate verification   
  
  :::warning
-  For security reasons, it is not recommended to disable certificate verification
+  For security reasons, it is not recommended to disable certificate verification.
  :::
    1. Upgrade ClearML to the current version:
       ``` 
--- a/docs/fundamentals/task.md
+++ b/docs/fundamentals/task.md
@ -103,7 +103,7 @@ ClearML can be configured to upload artifacts to any of the supported types of s
 folders, AWS S3 buckets, Google Cloud Storage, and Azure Storage. For more information, see [Storage](../integrations/storage.md). 

 :::note Debug Sample Storage
-Debug samples are handled differently, see [`Logger.set_default_upload_destination`](../references/sdk/logger.md#set_default_upload_destination)
+Debug samples are handled differently, see [`Logger.set_default_upload_destination`](../references/sdk/logger.md#set_default_upload_destination).
 :::

 #### Accessing Artifacts
--- a/docs/guides/advanced/execute_remotely.md
+++ b/docs/guides/advanced/execute_remotely.md
@ -6,7 +6,7 @@ The [execute_remotely_example](https://github.com/allegroai/clearml/blob/master/
 script demonstrates the use of the [`Task.execute_remotely`](../../references/sdk/task.md#execute_remotely) method. 

 :::note
-Make sure to have at least one [ClearML Agent](../../clearml_agent.md) running and assigned to listen to the `default` queue 
+Make sure to have at least one [ClearML Agent](../../clearml_agent.md) running and assigned to listen to the `default` queue: 
 ```
 clearml-agent daemon --queue default
 ```
--- a/docs/guides/clearml_agent/executable_exp_containers.md
+++ b/docs/guides/clearml_agent/executable_exp_containers.md
@ -41,7 +41,7 @@ script.
   ```

   :::tip
-   If the container will not make use of a GPU, add the `--cpu-only` flag
+   If the container will not make use of a GPU, add the `--cpu-only` flag.
   :::

   This command will create a Docker container, set up with the execution environment for this experiment in the 
--- a/docs/guides/clearml_agent/exp_environment_containers.md
+++ b/docs/guides/clearml_agent/exp_environment_containers.md
@ -44,7 +44,7 @@ clearml-agent build --id <TASK_ID> --docker --target new_docker
 ```

 :::tip
-If the container will not make use of a GPU, add the `--cpu-only` flag
+If the container will not make use of a GPU, add the `--cpu-only` flag.
 :::

 This will create a container with the specified task's execution environment in the `--target` folder. 
@ -72,7 +72,7 @@ Make use of the container you've just built by having a ClearML agent make use o
   ```

   :::tip
-   If the agent will not make use of a GPU, add the `--cpu-only` flag
+   If the agent will not make use of a GPU, add the `--cpu-only` flag.
   :::

   This agent will pull the enqueued task and run it using the `new_docker` image to create the execution environment. 
--- a/docs/guides/frameworks/pytorch/model_updating.md
+++ b/docs/guides/frameworks/pytorch/model_updating.md
@ -45,7 +45,7 @@ Task.current_task().connect_label_enumeration(enumeration)

 :::note Directly Setting Model Enumeration
 You can set a model's label enumeration directly using the [`OutputModel.update_labels`](../../../references/sdk/model_outputmodel.md#update_labels) 
-method
+method.
 :::

 ## Model Configuration
--- a/docs/guides/ide/remote_jupyter_tutorial.md
+++ b/docs/guides/ide/remote_jupyter_tutorial.md
@ -35,7 +35,7 @@ This sets the following arguments:

 :::note
 Enter a project name using `--project <name>`. If no project is input, the default project 
-name is "DevOps"
+name is `DevOps`.
 :::
   
 After launching the command, the `clearml-agent` listening to the `default` queue spins a remote Jupyter environment with 
--- a/docs/guides/reporting/clearml_logging_example.md
+++ b/docs/guides/reporting/clearml_logging_example.md
@ -23,8 +23,8 @@ The scalar plots appear in the **web UI** in **SCALARS**.
 ```python
 # report two scalar series on two different graphs
 for i in range(10):
-    logger.report_scalar("graph A", "series A", iteration=i, value=1./(i+1))
-    logger.report_scalar("graph B", "series B", iteration=i, value=10./(i+1))
+    logger.report_scalar(title="graph A", series="series A", iteration=i, value=1./(i+1))
+    logger.report_scalar(title="graph B", series="series B", iteration=i, value=10./(i+1))
 ```

 ![Separate scalar plots](../../img/colab_explicit_reporting_01.png)
@ -32,8 +32,8 @@ for i in range(10):
 ```python
 # report two scalar series on the same graph
 for i in range(10):
-    logger.report_scalar("unified graph", "series A", iteration=i, value=1./(i+1))
-    logger.report_scalar("unified graph", "series B", iteration=i, value=10./(i+1))
+    logger.report_scalar(title="unified graph", series="series A", iteration=i, value=1./(i+1))
+    logger.report_scalar(title="unified graph", series="series B", iteration=i, value=10./(i+1))
 ```    

 ![Unified scalar plots](../../img/colab_explicit_reporting_02.png)
--- a/docs/guides/reporting/html_reporting.md
+++ b/docs/guides/reporting/html_reporting.md
@ -15,15 +15,15 @@ When the script runs, it creates an experiment named `html samples reporting` in

 ## Reporting HTML URLs

-Report HTML by URL, using the [Logger.report_media](../../references/sdk/logger.md#report_media) method's `url` parameter.
+Report HTML by URL using [`Logger.report_media()`](../../references/sdk/logger.md#report_media)'s `url` parameter.

-See the example script's [report_html_url](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L16) 
+See the example script's [`report_html_url`](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L16) 
 function, which reports the ClearML documentation's home page.

 ```python
 Logger.current_logger().report_media(
-    "html", 
-    "url_html", 
+    title="html", 
+    series="url_html", 
    iteration=iteration, 
    url="https://clear.ml/docs/latest/docs/index.html"
 )
@ -39,20 +39,23 @@ Report the following using the `Logger.report_media` parameter method `local_pat

 ### Interactive HTML

-See the example script's [report_html_periodic_table](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L26) function, which reports a file created from Bokeh sample data.
+See the example script's [`report_html_periodic_table`](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L26) function, which reports a file created from Bokeh sample data.
 ```python
 Logger.current_logger().report_media(
-    "html", "periodic_html", iteration=iteration, local_path="periodic.html"
+    title="html", 
+    series="periodic_html", 
+    iteration=iteration, 
+    local_path="periodic.html"
 )
 ```

 ### Bokeh GroupBy HTML

-See the example script's [report_html_groupby](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L117) function, which reports a Pandas GroupBy with nested HTML, created from Bokeh sample data.
+See the example script's [`report_html_groupby`](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L117) function, which reports a Pandas GroupBy with nested HTML, created from Bokeh sample data.
 ```python
 Logger.current_logger().report_media(
-    "html",
-    "pandas_groupby_nested_html",
+    title="html",
+    series="pandas_groupby_nested_html",
    iteration=iteration,
    local_path="bar_pandas_groupby_nested.html",
 )
@ -60,20 +63,26 @@ Logger.current_logger().report_media(

 ### Bokeh Graph HTML

-See the example script's [report_html_graph](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L162) function, which reports a Bokeh plot created from Bokeh sample data.
+See the example script's [`report_html_graph`](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L162) function, which reports a Bokeh plot created from Bokeh sample data.

 ```python
 Logger.current_logger().report_media(
-    "html", "Graph_html", iteration=iteration, local_path="graph.html"
+    title="html", 
+    series="Graph_html", 
+    iteration=iteration, 
+    local_path="graph.html"
 )
 ```

 ### Bokeh Image HTML

-See the example script's [report_html_image](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L195) function, which reports an image created from Bokeh sample data.
+See the example script's [`report_html_image`](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L195) function, which reports an image created from Bokeh sample data.

 ```python
 Logger.current_logger().report_media(
-    "html", "Spectral_html", iteration=iteration, local_path="image.html"
+    title="html", 
+    series="Spectral_html", 
+    iteration=iteration, 
+    local_path="image.html"
 )
 ```
--- a/docs/guides/reporting/image_reporting.md
+++ b/docs/guides/reporting/image_reporting.md
@ -22,17 +22,17 @@ Report images using several formats by calling [`Logger.report_image()`](../../r
 ```python
 # report image as float image
 m = np.eye(256, 256, dtype=np.float)
-Logger.current_logger().report_image("image", "image float", iteration=iteration, image=m)
+Logger.current_logger().report_image(title="image", series="image float", iteration=iteration, image=m)
        
 # report image as uint8
 m = np.eye(256, 256, dtype=np.uint8) * 255
-Logger.current_logger().report_image("image", "image uint8", iteration=iteration, image=m)
+Logger.current_logger().report_image(title="image", series="image uint8", iteration=iteration, image=m)
        
 # report image as uint8 RGB
 m = np.concatenate((np.atleast_3d(m), np.zeros((256, 256, 2), dtype=np.uint8)), axis=2)
 Logger.current_logger().report_image(
-    "image", 
-    "image color red", 
+    title="image", 
+    series="image color red", 
    iteration=iteration, 
    image=m
 )
@ -40,8 +40,8 @@ Logger.current_logger().report_image(
 # report PIL Image object
 image_open = Image.open(os.path.join("data_samples", "picasso.jpg"))
 Logger.current_logger().report_image(
-    "image", 
-    "image PIL", 
+    title="image", 
+    series="image PIL", 
    iteration=iteration, 
    image=image_open
 )
--- a/docs/guides/reporting/pandas_reporting.md
+++ b/docs/guides/reporting/pandas_reporting.md
@ -26,8 +26,8 @@ df = pd.DataFrame(
 )
 df.index.name = "id"
 Logger.current_logger().report_table(
-    "table pd", 
-    "PD with index", 
+    title="table pd", 
+    series="PD with index", 
    iteration=iteration, 
    table_plot=df
 )
@ -43,8 +43,8 @@ Report CSV files by providing the URL location of the CSV file in the `url` para
 # Report table - CSV from path
 csv_url = "https://raw.githubusercontent.com/plotly/datasets/master/Mining-BTC-180.csv"
 Logger.current_logger().report_table(
-    "table csv", 
-    "remote csv", 
+    title="table csv", 
+    series="remote csv", 
    iteration=iteration, 
    url=csv_url
 )
--- a/docs/guides/reporting/scalar_reporting.md
+++ b/docs/guides/reporting/scalar_reporting.md
@ -16,19 +16,19 @@ To report more than one series on the same plot, use the same `title` argument.
 # report two scalar series on the same graph
 for i in range(100):
    Logger.current_logger().report_scalar(
-        "unified graph", "series A", iteration=i, value=1./(i+1)
+        title="unified graph", series="series A", iteration=i, value=1./(i+1)
    )
    Logger.current_logger().report_scalar(
-        "unified graph", "series B", iteration=i, value=10./(i+1)
+        title="unified graph", series="series B", iteration=i, value=10./(i+1)
    )
    
 # report two scalar series on two different graphs
 for i in range(100):
    Logger.current_logger().report_scalar(
-        "graph A", "series A", iteration=i, value=1./(i+1)
+        title="graph A", series="series A", iteration=i, value=1./(i+1)
    )
    Logger.current_logger().report_scalar(
-        "graph B", "series B", iteration=i, value=10./(i+1)
+        title="graph B", series="series B", iteration=i, value=10./(i+1)
    )
 ```

--- a/docs/guides/reporting/scatter_hist_confusion_mat_reporting.md
+++ b/docs/guides/reporting/scatter_hist_confusion_mat_reporting.md
@ -23,8 +23,8 @@ To report more than one series on the same plot, use same the `title` argument.
 # report a single histogram
 histogram = np.random.randint(10, size=10)
 Logger.current_logger().report_histogram(
-    "single_histogram",
-    "random histogram",
+    title="single_histogram",
+    series="random histogram",
    iteration=iteration,
    values=histogram,
    xaxis="title x",
@ -35,8 +35,8 @@ Logger.current_logger().report_histogram(
 histogram1 = np.random.randint(13, size=10)
 histogram2 = histogram * 0.75
 Logger.current_logger().report_histogram(
-    "two_histogram",
-    "series 1",
+    title="two_histogram",
+    series="series 1",
    iteration=iteration,
    values=histogram1,
    xaxis="title x",
@ -65,8 +65,8 @@ Report confusion matrices by calling [`Logger.report_confusion_matrix()`](../../
 # report confusion matrix
 confusion = np.random.randint(10, size=(10, 10))
 Logger.current_logger().report_confusion_matrix(
-    "example_confusion",
-    "ignored",
+    title="example_confusion",
+    series="ignored",
    iteration=iteration,
    matrix=confusion,
    xaxis="title X",
@ -79,8 +79,8 @@ Logger.current_logger().report_confusion_matrix(
 ```python
 # report confusion matrix with 0,0 is at the top left
 Logger.current_logger().report_confusion_matrix(
-    "example_confusion_0_0_at_top",
-    "ignored",
+    title="example_confusion_0_0_at_top",
+    series="ignored",
    iteration=iteration,
    matrix=confusion,
    xaxis="title X",
@ -101,8 +101,8 @@ scatter2d = np.hstack(
    
 # report 2d scatter plot with lines
 Logger.current_logger().report_scatter2d(
-    "example_scatter",
-    "series_xy",
+    title="example_scatter",
+    series="series_xy",
    iteration=iteration,
    scatter=scatter2d,
    xaxis="title x",
@ -111,8 +111,8 @@ Logger.current_logger().report_scatter2d(
    
 # report 2d scatter plot with markers
 Logger.current_logger().report_scatter2d(
-    "example_scatter",
-    "series_markers",
+    title="example_scatter",
+    series="series_markers",
    iteration=iteration,
    scatter=scatter2d,
    xaxis="title x",
@ -122,8 +122,8 @@ Logger.current_logger().report_scatter2d(
    
 # report 2d scatter plot with lines and markers
 Logger.current_logger().report_scatter2d(
-    "example_scatter",
-    "series_lines+markers",
+    title="example_scatter",
+    series="series_lines+markers",
    iteration=iteration,
    scatter=scatter2d,
    xaxis="title x",
--- a/docs/guides/services/slack_alerts.md
+++ b/docs/guides/services/slack_alerts.md
@ -18,7 +18,7 @@ The Slack API token and channel you create are required to configure the Slack a

 1. Login to your Slack account.
 1. Go to [https://api.slack.com/apps/new](https://api.slack.com/apps/new).
-1. In **App Name**, enter an app name; for example, "ClearML Bot".
+1. In **App Name**, enter an app name. For example, "ClearML Bot".
 1. In **Development Slack Workspace**, select a workspace.
 1. Click **Create App**.
 1. In **Basic Information**, under **Display Information**, complete the following:
@ -31,7 +31,7 @@ The Slack API token and channel you create are required to configure the Slack a
    * **channels:read**
    * **chat:write**
 1. In **OAuth Tokens & Redirect URLs**:
-    1. Click **Install App to Workspace**
+    1. Click **Install App to Workspace**.
    1. In the confirmation dialog, click **Allow**.
    1. Click **Copy** to copy the **Bot User OAuth Access Token**.

--- a/docs/integrations/yolov8.md
+++ b/docs/integrations/yolov8.md
@ -137,7 +137,7 @@ task = Task.init(
 # Load a model
 model_variant = "yolov8n"
 # Log "model_variant" parameter to task
-task.set_parameter("model_variant", model_variant)
+task.set_parameter(name="model_variant", value=model_variant)

 # Load the YOLOv8 model
 model = YOLO(f'{model_variant}.pt') 
--- a/docs/webapp/applications/apps_hpo.md
+++ b/docs/webapp/applications/apps_hpo.md
@ -3,7 +3,7 @@ title: Hyperparameter Optimization
 ---

 :::info Pro Plan Offering
-The ClearML HPO App is available under the ClearML Pro plan
+The ClearML HPO App is available under the ClearML Pro plan.
 :::

 The Hyperparameter Optimization Application finds the set of parameter values that optimize a specific metric(s) for your 
--- a/docs/webapp/applications/apps_vscode.md
+++ b/docs/webapp/applications/apps_vscode.md
@ -3,7 +3,7 @@ title: VS Code
 ---

 :::important Enterprise Feature
-The VS Code application is available under the ClearML Enterprise plan
+The VS Code application is available under the ClearML Enterprise plan.
 :::

 The VS Code UI application allows you to launch a remote VS Code session on a machine that better meets resource needs.