Update docs for ClearML server 1.6 (#280)

docs/clearml_data/clearml_data.md

@@ -26,6 +26,9 @@ Dataset changes are stored using differentiable storage, meaning a version will
 Local copies of datasets are always cached, so the same data never needs to be downloaded twice.
 When a dataset is pulled it will automatically pull all parent datasets and merge them into one output folder for you to work with.
 
+The [Dataset Versions](../webapp/pipelines/webapp_pipeline_viewing.md) page in the web UI displays dataset versions' 
+lineage and content information. See [dataset UI](../webapp/datasets/webapp_dataset_page.md) for more details.
+
 ## Setup
 
 `clearml-data` comes built-in with the `clearml` python package! Just check out the [Getting Started](../getting_started/ds/ds_first_steps.md) 
@@ -39,59 +42,15 @@ ClearML Data offers two interfaces:
 
 For an overview of our recommendations for ClearML Data workflows and practices, see [Best Practices](best_practices.md).
 
-## WebApp 
-
-ClearML's WebApp provides a visual interface to your datasets through dataset tasks. Dataset tasks are categorized 
-as data-processing [task type](../fundamentals/task.md#task-types), and they are labeled with a `DATASET` system tag.
-
-Full log (calls / CLI) of the dataset creation process can be found in a dataset's **EXECUTION** section.
-
-Listing of the dataset differential snapshot, summary of files added / modified / removed and details of files in the 
-differential snapshot (location / size / hash), is available in the **ARTIFACTS** section. Download the dataset 
-by clicking  <img src="/docs/latest/icons/ico-download-json.svg" alt="Download" className="icon size-sm space-sm" />,
-next to the **FILE PATH**.
-
-The full dataset listing (all files included) is available in the **CONFIGURATION** section under **Dataset Content**. 
-This allows you to quickly compare two dataset contents and visually see the difference.
-The dataset genealogy DAG and change-set summary table is visualized in **PLOTS**
-
-
-<details className="cml-expansion-panel screenshot">
-<summary className="cml-expansion-panel-summary">Dataset Contents</summary>
-<div className="cml-expansion-panel-content">
-
-![Dataset data WebApp](../img/dataset_data.png)
-
-</div>
-</details>
-
-<br/>
-
-View a DAG of the dataset dependencies (all previous dataset versions and their parents) in the dataset's page **> ARTIFACTS > state**.
-
-<details className="cml-expansion-panel screenshot">
-<summary className="cml-expansion-panel-summary">Data Dependency DAG</summary>
-<div className="cml-expansion-panel-content">
-
-![Dataset state WebApp](../img/dataset_data_state.png)
-
-</div>
-</details>
-
-
-Once a dataset has been finalized, view its genealogy in the dataset's
-page **>** **PLOTS**
-
-<details className="cml-expansion-panel screenshot">
-<summary className="cml-expansion-panel-summary">Dataset Genealogy</summary>
-<div className="cml-expansion-panel-content">
-
-![Dataset genealogy and summary](../img/dataset_genealogy_summary.png)
-
-</div>
-</details>
-
-
+## Dataset Version States
+The following table displays the possible states for a dataset version. 
 
 
+| State | Description |
+|---|---|
+|*Uploading*| Dataset creation is in progress  |
+|*Failed*| Dataset creation was terminated with an error|
+|*Aborted*| Dataset creation was aborted by user before it was finalization |
+|*Final*| A dataset was created and finalized successfully | 
+|*Published*| The dataset is read-only. Publish a dataset to prevent changes to it | 
 

docs/clearml_data/clearml_data_cli.md

@@ -7,6 +7,11 @@ This page covers `clearml-data`, ClearML's file-based data management solution.
 See [Hyper-Datasets](../hyperdatasets/overview.md) for ClearML's advanced queryable dataset management solution.
 :::
 
+:::tip version compatibility 
+To use the WebApp's [Dataset pages](../webapp/datasets/webapp_dataset_page.md), you must use `clearml` and 
+`clearml-server` versions 1.6+.  
+:::
+
 The `clearml-data` utility is a CLI tool for controlling and managing your data with ClearML.  
 
 The following page provides a reference to `clearml-data`'s CLI commands. 
@@ -38,9 +43,9 @@ clearml-data create [-h] [--parents [PARENTS [PARENTS ...]]] [--project PROJECT]
 
 
 :::tip Dataset ID
-* To locate a dataset's ID, go to the dataset task's info panel in the [WebApp](../webapp/webapp_exp_track_visual.md). In the top of the panel, 
-to the right of the dataset task name, click `ID` and the dataset ID appears.
-
+* To locate a dataset's ID, go to the dataset version’s info panel in the [Dataset UI](../webapp/datasets/webapp_dataset_viewing.md) 
+  where the ID is listed. If using `clearml` or `clearml-server` versions older than 1.6, go to the [dataset task's info 
+  panel](../webapp/webapp_exp_track_visual.md), where the ID is displayed in the task header.  
 * clearml-data works in a stateful mode so once a new dataset is created, the following commands
 do not require the `--id` flag.
 :::

docs/clearml_data/clearml_data_sdk.md

@@ -7,6 +7,11 @@ This page covers `clearml-data`, ClearML's file-based data management solution.
 See [Hyper-Datasets](../hyperdatasets/overview.md) for ClearML's advanced queryable dataset management solution.
 :::
 
+:::tip version compatibility 
+To use the WebApp's [Dataset pages](../webapp/datasets/webapp_dataset_page.md), you must use `clearml` and 
+`clearml-server` versions 1.6+.  
+:::
+
 Datasets can be created, modified, and managed with ClearML Data's python interface. The following page provides an overview
 for using the most basic methods of the `Dataset` class. See the [Dataset reference page](../references/sdk/dataset.md) 
 for a complete list of available methods.
@@ -43,8 +48,9 @@ dataset = Dataset.create(
 ```
 
 :::tip Locating Dataset ID
-To locate a dataset's ID, go to the dataset task's info panel in the [WebApp](../webapp/webapp_overview.md). In the top of the panel, 
-to the right of the dataset task name, click `ID` and the dataset ID appears
+To locate a dataset's ID, go to the dataset version’s info panel in the [Dataset UI](../webapp/datasets/webapp_dataset_viewing.md) 
+where the ID is listed. If using `clearml` or `clearml-server` versions older than 1.6, go to the [dataset task's info 
+panel](../webapp/webapp_exp_track_visual.md), where the ID is displayed in the task header.
 :::
 
 Use the `output_uri` parameter to specify a network storage target to upload the dataset files, and associated information 

docs/fundamentals/agents_and_queues.md

@@ -36,7 +36,7 @@ A ClearML Agent can service multiple queues in either of the following modes:
 
 ## Agent and Queue Workflow 
 
-![image](../img/clearml_agent_flow_diagram.png)
+![Agent flow diagram](../img/clearml_agent_flow_diagram.png)
 
 The diagram above demonstrates a typical flow where an agent executes a task:  
 

docs/guides/frameworks/keras/jupyter.md

@@ -29,8 +29,6 @@ They appear in **PLOTS**.
 
 ![image](../../../img/examples_keras_jupyter_03a.png)
 
-![image](../../../img/examples_keras_jupyter_03b.png)
-
 ## Debug Samples
 
 The example calls Matplotlib methods to log debug sample images. They appear in **DEBUG SAMPLES**.

docs/guides/frameworks/keras/keras_tensorboard.md

@@ -57,9 +57,12 @@ In the experiment code, a configuration dictionary is connected to the Task by c
 method. 
 
 ```python
-task.connect_configuration({'test': 1337, 'nested': {'key': 'value', 'number': 1}})
+task.connect_configuration(
+   name="MyConfig" 
+   configuration={'test': 1337, 'nested': {'key': 'value', 'number': 1}}
+)
 ```
 
-It appears in **CONFIGURATION** **>** **CONFIGURATION OBJECTS** **>** **General**. 
+It appears in **CONFIGURATION** **>** **CONFIGURATION OBJECTS** **>** **MyConfig**. 
 
 ![image](../../../img/keras_colab_02.png)

docs/guides/frameworks/pytorch_ignite/pytorch_ignite_mnist.md

@@ -159,10 +159,6 @@ View the scalars, including training and validation metrics, in the experiment's
 
 ![image](../../../img/ignite_training.png)
 
-<br/>
-
-![image](../../../img/ignite_validation.png)
-
 ### Model Snapshots
  
 

docs/guides/frameworks/xgboost/xgboost_sample.md

@@ -18,7 +18,10 @@ classification dataset using XGBoost
 The feature importance plot and tree plot appear in the project's page in the **ClearML web UI**, under 
 **PLOTS**.
 
-![image](../../../img/examples_xgboost_sample_06.png)
+![Feature importance plot](../../../img/examples_xgboost_sample_06.png)
+
+![Tree plot](../../../img/examples_xgboost_sample_06a.png)
+
 
 ## Console