Merge pull request #89424 from MicrosoftDocs/repo_sync_working_branch

Confirm merge from repo_sync_working_branch to master to sync with https://github.com/Microsoft/azure-docs (branch master)

articles/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis.md

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: text-analytics
 ms.topic: sample
-ms.date: 07/30/2019
+ms.date: 09/23/2019
 ms.author: aahi
 ---
 
@@ -134,7 +134,7 @@ The [next version of Sentiment Analysis](https://westcentralus.dev.cognitive.mic
 > [!NOTE]
 > * The Sentiment Analysis v3 request format and [data limits](../overview.md#data-limits) are the same as the previous version.
 > * At this time, Sentiment Analysis v3:
->    * Currently supports English, Simplified Chinese, and Japanese languages.
+>    * Currently supports English, French, Italian, Japanese, Simplified-Chinese, and Traditional-Chinese languages.
 >    * Is available in the following regions: `Australia East`, `Central Canada`, `Central US`, `East Asia`, `East US`, `East US 2`, `North Europe`, `Southeast Asia`, `South Central US`, `UK South`, `West Europe`, and `West US 2`.
 
 |Feature |Description  |

articles/machine-learning/service/how-to-deploy-custom-docker-image.md

@@ -218,9 +218,9 @@ To use an image from a __private container registry__ that is not in your worksp
 
 ```python
 # Set the container registry information
-myenv.docker.base_image_repository.address = "myregistry.azurecr.io"
-myenv.docker.base_image_repository.username = "username"
-myenv.docker.base_image_repository.password = "password"
+myenv.docker.base_image_registry.address = "myregistry.azurecr.io"
+myenv.docker.base_image_registry.username = "username"
+myenv.docker.base_image_registry.password = "password"
 ```
 
 After defining the environment, use it with an [InferenceConfig](https://docs.microsoft.com/python/api/azureml-core/azureml.core.model.inferenceconfig?view=azure-ml-py) object to define the inference environment in which the model and web service will run.

articles/machine-learning/service/how-to-train-ml-models.md

@@ -92,13 +92,14 @@ You should have already created your [compute target](how-to-set-up-training-tar
 
 ```Python
 from azureml.train.estimator import Estimator
+from azureml.core.runconfig import MpiConfiguration
 
 estimator = Estimator(source_directory='./my-keras-proj',
                       compute_target=compute_target,
                       entry_script='train.py',
                       node_count=2,
                       process_count_per_node=1,
-                      distributed_backend='mpi',     
+                      distributed_training=MpiConfiguration(),        
                       conda_packages=['tensorflow', 'keras'],
                       custom_docker_image='continuumio/miniconda')
 ```
@@ -110,7 +111,8 @@ Parameter | Description | Default
 `custom_docker_image`| Name of the image you want to use. Only provide images available in public docker repositories (in this case Docker Hub). To use an image from a private docker repository, use the constructor's `environment_definition` parameter instead. [See example](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/training-with-deep-learning/how-to-use-estimator/how-to-use-estimator.ipynb). | `None`
 `node_count`| Number of nodes to use for your training job. | `1`
 `process_count_per_node`| Number of processes (or "workers") to run on each node. In this case, you use the `2` GPUs available on each node.| `1`
-`distributed_backend`| Backend for launching distributed training, which the Estimator offers via MPI.  To carry out parallel or distributed training (e.g., `node_count`>1 or `process_count_per_node`>1 or both), set `distributed_backend='mpi'`. The MPI implementation used by AML is [Open MPI](https://www.open-mpi.org/).| `None`
+`distributed_training`| [MPIConfiguration ]('https://docs.microsoft.com/python/api/azureml-core/azureml.core.runconfig.mpiconfiguration?view=azure-ml-py') object for launching distributed training using MPI backend.  | `None`
+
 
 Finally, submit the training job:
 ```Python

articles/role-based-access-control/resource-provider-operations.md

@@ -1215,9 +1215,9 @@ The resource provider operations are always evolving. To get the latest operatio
 > | DataAction | Microsoft.CognitiveServices/accounts/VisualSearch/search/action | Returns a list of tags relevant to the provided image |
 > | DataAction | Microsoft.CognitiveServices/accounts/WebSearch/search/action | Get web, image, news, & videos results for a given query. |
 > | Action | Microsoft.CognitiveServices/accounts/write | Writes API Accounts. |
-> | Action | Microsoft.CognitiveServices/checkDomainAvailability/action | Reads available SKUs for an subscription. |
-> | Action | Microsoft.CognitiveServices/locations/checkSkuAvailability/action | Reads available SKUs for an subscription. |
-> | Action | Microsoft.CognitiveServices/locations/checkSkuAvailability/action | Reads available SKUs for an subscription. |
+> | Action | Microsoft.CognitiveServices/checkDomainAvailability/action | Reads available SKUs for a subscription. |
+> | Action | Microsoft.CognitiveServices/locations/checkSkuAvailability/action | Reads available SKUs for a subscription. |
+> | Action | Microsoft.CognitiveServices/locations/checkSkuAvailability/action | Reads available SKUs for a subscription. |
 > | Action | Microsoft.CognitiveServices/locations/deleteVirtualNetworkOrSubnets/action | Notification from Microsoft.Network of deleting VirtualNetworks or Subnets. |
 > | Action | Microsoft.CognitiveServices/Operations/read | List all available operations |
 > | Action | Microsoft.CognitiveServices/register/action | Registers Subscription for Cognitive Services |