Merge pull request #264776 from cloga/lochen/pipelinecomponent-ga

remove preview tag for pipeline component

Author: prmerger-automator[bot]

articles/machine-learning/how-to-create-component-pipelines-ui.md

@@ -62,6 +62,7 @@ This example uses `train.yml` [in the directory](https://github.com/Azure/azurem
 >[!Note]
 > When register components in UI, `code` defined in the component YAML file can only point to the current folder where YAML file locates or the subfolders, which means you cannot specify `../` for `code` as UI cannot recognize the parent directory.
 > `additional_includes` can only point to the current or sub folder.
+> Currently, UI only supports registering components with `command` type.
 
 2. Select Upload from **Folder**, and select the `1b_e2e_registered_components` folder to upload. Select `train.yml` from the drop-down list.
 

articles/machine-learning/how-to-share-models-pipelines-across-workspaces-with-registries.md

@@ -209,6 +209,9 @@ For more information on components, see the following articles:
 * [How to use components in pipelines (CLI)](how-to-create-component-pipelines-cli.md)
 * [How to use components in pipelines (SDK)](how-to-create-component-pipeline-python.md)
 
+  > [!IMPORTANT]
+  > Registry only support to have named assets (data/model/component/environment). If you to reference an asset in a registry, you need to create it in the registry first. Especially for pipeline component case, if you want reference component or environment in pipeline component, you need first create the component or environment in the registry.
+
 # [Azure CLI](#tab/cli)
 
 Make sure you are in the folder `cli/jobs/pipelines-with-components/nyc_taxi_data_regression`. You'll find the component definition file `train.yml` that packages a Scikit Learn training script `train_src/train.py` and the [curated environment](resource-curated-environments.md) `AzureML-sklearn-0.24-ubuntu18.04-py37-cpu`. We'll use the Scikit Learn environment created in pervious step instead of the curated environment. You can edit `environment` field in the `train.yml` to refer to your Scikit Learn environment. The resulting component definition file `train.yml` will be similar to the following example: 

articles/machine-learning/how-to-use-pipeline-component.md

@@ -17,7 +17,7 @@ ms.custom:
   - ignite-2023
 ---
 
-# How to use pipeline component to build nested pipeline job (V2) (preview)
+# How to use pipeline component to build nested pipeline job (V2)
 
 [!INCLUDE [dev v2](includes/machine-learning-dev-v2.md)]
 
@@ -27,8 +27,6 @@ By using a pipeline component, the author can focus on developing sub-tasks and
 
 In this article, you'll learn how to use pipeline component in Azure Machine Learning pipeline.
 
-[!INCLUDE [machine-learning-preview-generic-disclaimer](includes/machine-learning-preview-generic-disclaimer.md)]
-
 ## Prerequisites
 
 - Understand how to use Azure Machine Learning pipeline with [CLI v2](how-to-create-component-pipelines-cli.md) and [SDK v2](how-to-create-component-pipeline-python.md).

articles/machine-learning/reference-yaml-component-pipeline.md

@@ -13,16 +13,14 @@ ms.date: 04/12/2023
 ms.reviewer: lagayhar
 ---
 
-# CLI (v2) pipeline component YAML schema (preview)
+# CLI (v2) pipeline component YAML schema
 
 [!INCLUDE [cli v2](includes/machine-learning-cli-v2.md)]
 
 The source JSON schema can be found at https://azuremlschemas.azureedge.net/latest/pipelineComponent.schema.json.
 
 [!INCLUDE [schema note](includes/machine-learning-preview-old-json-schema-note.md)]
 
-[!INCLUDE [machine-learning-preview-generic-disclaimer](includes/machine-learning-preview-generic-disclaimer.md)]
-
 ## YAML syntax
 
 | Key | Type | Description | Allowed values | Default value |