Merge pull request #204340 from laujan/204230-update-Lu-neural-model-pr

204230 update lu neural model pr

Author: BCS2022

articles/applied-ai-services/form-recognizer/compose-custom-models-preview.md

@@ -38,7 +38,7 @@ To get started, you'll need the following resources:
     :::image border="true" type="content" source="media/containers/keys-and-endpoint.png" alt-text="Still photo showing how to access resource key and endpoint URL.":::
 
     > [!TIP]
-    > For more information, see* [**create a Form Recognizer resource**](create-a-form-recognizer-resource.md).
+    > For more information, see [**create a Form Recognizer resource**](create-a-form-recognizer-resource.md).
 
 * **An Azure storage account.** If you don't know how to create an Azure storage account, follow the [Azure Storage quickstart for Azure portal](../../storage/blobs/storage-quickstart-blobs-portal.md). You can use the free pricing tier (F0) to try the service, and upgrade later to a paid tier for production.
 

articles/applied-ai-services/form-recognizer/concept-custom-neural.md

@@ -7,7 +7,7 @@ manager: nitinme
 ms.service: applied-ai-services
 ms.subservice: forms-recognizer
 ms.topic: conceptual
-ms.date: 06/06/2022
+ms.date: 07/11/2022
 ms.author: lajanuar
 ms.custom: references_regions
 recommendations: false
@@ -37,8 +37,8 @@ Custom neural models currently only support key-value pairs and selection marks,
 
 With the release of API version **2022-06-30-preview**, custom neural models will support tabular fields (tables):
 
-* Models trained with API version 2022-06-30-preview or later will accept tabular field labels. 
-* Documents analyzed with custom neural models using API version 2022-06-30-preview or later will produce tabular fields aggregated across the tables. 
+* Models trained with API version 2022-06-30-preview or later will accept tabular field labels.
+* Documents analyzed with custom neural models using API version 2022-06-30-preview or later will produce tabular fields aggregated across the tables.
 * The results can be found in the ```analyzeResult``` object's ```documents``` array that is returned following an analysis operation.
 
 Tabular fields support **cross page tables** by default:
@@ -50,34 +50,22 @@ Tabular fields are also useful when extracting repeating information within a do
 
 ## Supported regions
 
-For the **2022-06-30-preview**, custom neural models can only be trained in the following Azure regions:
-
-* AustraliaEast
-* BrazilSouth
-* CanadaCentral
-* CentralIndia
-* CentralUS
-* EastUS
-* EastUS2
-* FranceCentral
-* JapanEast
-* JioIndiaWest
-* KoreaCentral
-* NorthEurope
-* SouthCentralUS
-* SoutheastAsia
-* UKSouth
-* WestEurope
-* WestUS
-* WestUS2
-* WestUS3
+As of August 01 2022, Form Recognizer custom neural model training will only be available in the following Azure regions until further notice:
+
+* Brazil South
+* Canada Central
+* Central India
+* Japan East
+* North Europe
+* South Central US
+* Southeast Asia
 
 > [!TIP]
-> You can copy a model trained in one of the select regions listed above to **any other region** and use it accordingly.
+> You can [copy a model](disaster-recovery.md) trained in one of the select regions listed above to **any other region** and use it accordingly.
 
 ## Best practices
 
-Custom neural models differ from custom template models in a few different ways. The custom template or model relies on a consistent visual template to extract the labeled data. Custom neural models support structured, semi-structured, and unstructured documents to extract fields. When you're choosing between the two model types, start with a neural model and test to determine if it supports your functional needs.
+Custom neural models differ from custom template models in a few different ways. The custom template or model relies on a consistent visual template to extract the labeled data. Custom neural models support structured, semi-structured, and unstructured documents to extract fields. When you're choosing between the two model types, start with a neural model, and test to determine if it supports your functional needs.
 
 ### Dealing with variations
 
@@ -98,7 +86,6 @@ Value tokens/words of one field must be either
 
 Values in training cases should be diverse and representative. For example, if a field is named "date", values for this field should be a date. synthetic value like a random string can affect model performance.
 
-
 ## Current Limitations
 
 * The model doesn't recognize values split across page boundaries.
@@ -130,6 +117,7 @@ https://{endpoint}/formrecognizer/documentModels:build?api-version=2022-06-30
   }
 }
 ```
+
 ## Next steps
 
 * Train a custom model:
@@ -145,4 +133,4 @@ https://{endpoint}/formrecognizer/documentModels:build?api-version=2022-06-30
 * View the REST API:
 
     > [!div class="nextstepaction"]
-    > [Form Recognizer API v3.0](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-2/operations/AnalyzeDocument)
+    > [Form Recognizer API v3.0](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-2/operations/AnalyzeDocument)

articles/applied-ai-services/form-recognizer/deploy-label-tool.md

@@ -17,7 +17,7 @@ ms.author: lajanuar
 >
 > * For an enhanced experience and advanced model quality, try the [Form Recognizer v3.0 Studio (preview)](https://formrecognizer.appliedai.azure.com/studio).
 > * The v3.0 Studio supports any model trained with v2.1 labeled data.
-> * You can refer to the API migration guide for detailed information about migrating from v2.1 to v3.0.
+> * You can refer to the [API migration guide](v3-migration-guide.md) for detailed information about migrating from v2.1 to v3.0.
 > * *See* our [**REST API**](quickstarts/try-v3-rest-api.md) or [**C#**](quickstarts/try-v3-csharp-sdk.md), [**Java**](quickstarts/try-v3-java-sdk.md), [**JavaScript**](quickstarts/try-v3-javascript-sdk.md), or [Python](quickstarts/try-v3-python-sdk.md) SDK quickstarts to get started with the V3.0 preview.
 
 > [!NOTE]

articles/applied-ai-services/form-recognizer/how-to-guides/build-custom-model-v3.md

@@ -49,7 +49,7 @@ The Form Recognizer Studio provides and orchestrates all the API calls required
     1. On the next step in the workflow, choose or create a Form Recognizer resource before you select continue.
 
     > [!IMPORTANT]
-    > Custom neural models models are only available in a few regions. If you plan on training a neural model, please select or create a resource in one of [these supported regions](../concept-custom-neural.md).
+    > Custom neural models models are only available in a few regions. If you plan on training a neural model, please select or create a resource in one of [these supported regions](../concept-custom-neural.md#supported-regions).
 
     :::image type="content" source="../media/how-to/studio-select-resource.png" alt-text="Screenshot: Select the Form Recognizer resource.":::
 

articles/applied-ai-services/form-recognizer/includes/how-to-guides/csharp-sdk.md

@@ -6,7 +6,7 @@ manager: nitinme
 ms.service: applied-ai-services
 ms.subservice: forms-recognizer
 ms.topic: include
-ms.date: 11/02/2021
+ms.date: 07/11/2022
 ms.author: lajanuar
 ms.custom: devx-track-csharp, ignite-fall-2021
 ---
@@ -28,8 +28,10 @@ ms.custom: devx-track-csharp, ignite-fall-2021
 * The [Visual Studio IDE](https://visualstudio.microsoft.com/vs/) or current version of [.NET Core](https://dotnet.microsoft.com/download/dotnet-core).
 * An Azure Storage blob that contains a set of training data. See [Build a training data set for a custom model](../../build-training-data-set.md) for tips and options for putting together your training data set. For this project, you can use the files under the **Train** folder of the [sample data set](https://go.microsoft.com/fwlink/?linkid=2090451) (download and extract *sample_data.zip*).
 * Once you have your Azure subscription, <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesFormRecognizer"  title="Create a Form Recognizer resource"  target="_blank">create a Form Recognizer resource </a> in the Azure portal to get your key and endpoint. After it deploys, select **Go to resource**.
-  * You will need the key and endpoint from the resource you create to connect your application to the Form Recognizer API. Paste your key and endpoint into the code below later in the project.
+  * You'll need the key and endpoint from the resource you create to connect your application to the Form Recognizer API. Paste your key and endpoint into the code below later in the project.
   * You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
+> [!TIP]
+> Create a Cognitive Services resource if you plan to access multiple cognitive services under a single endpoint/key. For Form Recognizer access only, create a Form Recognizer resource. Please note that you'll  need a single-service resource if you intend to use [Azure Active Directory authentication](../../../../active-directory/authentication/overview-authentication.md).
 
 ## Setting up
 
@@ -76,7 +78,7 @@ In the application's **Program** class, create variables for your resource's key
 
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/FormRecognizer/FormRecognizerQuickstart.cs?name=snippet_creds)]
 
-In the application's **Main** method, add a call to the asynchronous tasks used in this project. You will implement them later:
+In the application's **Main** method, add a call to the asynchronous tasks used in this project. You'll implement them later:
 
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/FormRecognizer/FormRecognizerQuickstart-preview.cs?name=snippet_main)]
 
@@ -86,11 +88,11 @@ With Form Recognizer, you can create two different client types. The first, `For
 
 ### FormRecognizerClient
 
-`FormRecognizerClient` provides operations for:
+`FormRecognizerClient` provides the following operations:
 
-* Recognizing form fields and content, using custom models trained to analyze your custom forms.  These values are returned in a collection of `RecognizedForm` objects. See example [Analyze custom forms](#analyze-forms-with-a-custom-model).
-* Recognizing form content, including tables, lines and words, without the need to train a model.  Form content is returned in a collection of `FormPage` objects. See example [Analyze layout](#analyze-layout).
-* Recognizing common fields from US receipts, business cards, invoices, and ID documents using a pre-trained model on the Form Recognizer service.
+* Recognize form fields and content, using custom models trained to analyze your custom forms.  These values are returned in a collection of `RecognizedForm` objects. See example [Analyze custom forms](#analyze-forms-with-a-custom-model).
+* Recognize form content, including tables, lines and words, without the need to train a model.  Form content is returned in a collection of `FormPage` objects. See example [Analyze layout](#analyze-layout).
+* Recognize common fields from US receipts, business cards, invoices, and ID documents using a pre-trained model on the Form Recognizer service.
 
 ### FormTrainingClient
 
@@ -289,7 +291,7 @@ The following code processes the ID document at the given URI and prints the maj
 
 ## Train a custom model
 
-This section demonstrates how to train a model with your own data. A trained model can output structured data that includes the key/value relationships in the original form document. After you train the model, you can test and retrain it and eventually use it to reliably extract data from more forms according to your needs.
+This section demonstrates how to train a model with your own data. A trained model can output structured data that includes the key/value relationships in the original form document. After you train the model, you can test, retrain, and eventually use it to reliably extract data from more forms according to your needs.
 
 > [!NOTE]
 > You can also train models with a graphical user interface such as the [Form Recognizer Sample Labeling tool](../../label-tool.md).
@@ -366,7 +368,7 @@ Submodel Form Type: form-0
 
 ### Train a model with labels
 
-You can also train custom models by manually labeling the training documents. Training with labels leads to better performance in some scenarios. To train with labels, you need to have special label information files (`\<filename\>.pdf.labels.json`) in your blob storage container alongside the training documents. The [Form Recognizer Sample Labeling tool](../../label-tool.md) provides a UI to help you create these label files. Once you have them, you can call the `StartTrainingAsync` method with the `uselabels` parameter set to `true`.
+You can also train custom models by manually labeling the training documents. Training with labels leads to better performance in some scenarios. To train with labels, you need to have special label information files (`\<filename\>.pdf.labels.json`) in your blob storage container alongside the training documents. The [Form Recognizer Sample Labeling tool](../../label-tool.md) provides a UI to help you create these label files. Once you've them, you can call the `StartTrainingAsync` method with the `uselabels` parameter set to `true`.
 
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/FormRecognizer/FormRecognizerQuickstart.cs?name=snippet_trainlabels)]
 
@@ -503,7 +505,7 @@ This section demonstrates how to manage the custom models stored in your account
 
 ### Check the number of models in the FormRecognizer resource account
 
-The following code block checks how many models you have saved in your Form Recognizer account and compares it to the account limit.
+The following code block checks how many models you've saved in your Form Recognizer account and compares it to the account limit.
 
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/FormRecognizer/FormRecognizerQuickstart.cs?name=snippet_manage_model_count)]
 
@@ -516,7 +518,7 @@ It can have at most 5000 models.
 
 ### List the models currently stored in the resource account
 
-The following code block lists the current models in your account and prints their details to the console.
+The following code blocklists the current models in your account and prints their details to the console.
 
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/FormRecognizer/FormRecognizerQuickstart.cs?name=snippet_manage_model_list)]