Merge pull request #123522 from J-Silvestre/patch-5

Update how-to-use-batch-model-deployments.md

Author: Court72

articles/machine-learning/how-to-use-batch-model-deployments.md

@@ -303,15 +303,15 @@ A model deployment is a set of resources required for hosting the model that doe
     | `environment` | The environment to score the model. The example defines an environment inline using `conda_file` and `image`. The `conda_file` dependencies will be installed on top of the `image`. The environment will be automatically registered with an autogenerated name and version. See the [Environment schema](./reference-yaml-environment.md#yaml-syntax) for more options. As a best practice for production scenarios, you should create the environment separately and reference it here. To reference an existing environment, use the `azureml:<environment-name>:<environment-version>` syntax. |
     | `compute` | The compute to run batch scoring. The example uses the `batch-cluster` created at the beginning and references it using the `azureml:<compute-name>` syntax. |
     | `resources.instance_count` | The number of instances to be used for each batch scoring job. |
-    | `settings.max_concurrency_per_instance` | [Optional] The maximum number of parallel `scoring_script` runs per instance. |
-    | `settings.mini_batch_size` | [Optional] The number of files the `scoring_script` can process in one `run()` call. |
-    | `settings.output_action` | [Optional] How the output should be organized in the output file. `append_row` will merge all `run()` returned output results into one single file named `output_file_name`. `summary_only` won't merge the output results and will only calculate `error_threshold`. |
-    | `settings.output_file_name` | [Optional] The name of the batch scoring output file for `append_row` `output_action`. |
-    | `settings.retry_settings.max_retries` | [Optional] The number of max tries for a failed `scoring_script` `run()`. |
-    | `settings.retry_settings.timeout` | [Optional] The timeout in seconds for a `scoring_script` `run()` for scoring a mini batch. |
-    | `settings.error_threshold` | [Optional] The number of input file scoring failures that should be ignored. If the error count for the entire input goes above this value, the batch scoring job will be terminated. The example uses `-1`, which indicates that any number of failures is allowed without terminating the batch scoring job. |
-    | `settings.logging_level` | [Optional] Log verbosity. Values in increasing verbosity are: WARNING, INFO, and DEBUG. |
-    | `settings.environment_variables` | [Optional] Dictionary of environment variable name-value pairs to set for each batch scoring job.  |
+    | `settings.max_concurrency_per_instance` | The maximum number of parallel `scoring_script` runs per instance. |
+    | `settings.mini_batch_size` | The number of files the `scoring_script` can process in one `run()` call. |
+    | `settings.output_action` | How the output should be organized in the output file. `append_row` will merge all `run()` returned output results into one single file named `output_file_name`. `summary_only` won't merge the output results and will only calculate `error_threshold`. |
+    | `settings.output_file_name` | The name of the batch scoring output file for `append_row` `output_action`. |
+    | `settings.retry_settings.max_retries` | The number of max tries for a failed `scoring_script` `run()`. |
+    | `settings.retry_settings.timeout` | The timeout in seconds for a `scoring_script` `run()` for scoring a mini batch. |
+    | `settings.error_threshold` | The number of input file scoring failures that should be ignored. If the error count for the entire input goes above this value, the batch scoring job will be terminated. The example uses `-1`, which indicates that any number of failures is allowed without terminating the batch scoring job. |
+    | `settings.logging_level` | Log verbosity. Values in increasing verbosity are: WARNING, INFO, and DEBUG. |
+    | `settings.environment_variables` | Dictionary of environment variable name-value pairs to set for each batch scoring job.  |
 
     # [Python](#tab/python)