Re-route instance count to resource config for Model Batch Deployment (#34249)

* Re-route instance count to resource config

* fix

* fix

* unittest model batch deployment settings

Author: nemanjarajic

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_deployment/model_batch_deployment.py

@@ -94,6 +94,11 @@ def __init__(
                 error_threshold=settings.error_threshold,
                 logging_level=settings.logging_level,
             )
+            if self.resources is not None:
+                if self.resources.instance_count is None and settings.instance_count is not None:
+                    self.resources.instance_count = settings.instance_count
+            if self.resources is None and settings.instance_count is not None:
+                self.resources = ResourceConfiguration(instance_count=settings.instance_count)
 
     # pylint: disable=arguments-differ
     def _to_rest_object(self, location: str) -> BatchDeploymentData:  # type: ignore

sdk/ml/azure-ai-ml/tests/batch_services/unittests/test_model_batch_deployment_schema.py

@@ -0,0 +1,37 @@
+from pathlib import Path
+
+import pytest
+import yaml
+
+from azure.ai.ml._schema._deployment.batch.model_batch_deployment import ModelBatchDeploymentSchema
+from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY
+from azure.ai.ml.constants._deployment import BatchDeploymentOutputAction
+from azure.ai.ml.entities import BatchDeployment
+from azure.ai.ml.entities._util import load_from_dict
+
+
+def load_batch_deployment_entity_from_yaml(path: str, context={}) -> BatchDeployment:
+    """batch deployment yaml -> batch deployment entity"""
+    with open(path, "r") as f:
+        cfg = yaml.safe_load(f)
+    context.update({BASE_PATH_CONTEXT_KEY: Path(path).parent})
+    deployment = load_from_dict(ModelBatchDeploymentSchema, cfg, context)
+    return deployment
+
+
+@pytest.mark.unittest
+@pytest.mark.production_experiences_test
+class TestModelBatchDeploymentSchema:
+    def test_serialize_model_batch_deployment(self) -> None:
+        test_path = "./tests/test_configs/deployments/batch/model_batch_deployment.yaml"
+        mbd_entity = load_batch_deployment_entity_from_yaml(test_path)
+
+        assert mbd_entity
+        assert mbd_entity.environment == "AzureML-sklearn-1.0-ubuntu20.04-py38-cpu:33"
+        assert mbd_entity.compute == "cpu-cluster"
+        assert mbd_entity.model_deployment_settings.output_action == BatchDeploymentOutputAction.APPEND_ROW
+        assert mbd_entity.model_deployment_settings.output_file_name == "append_row.txt"
+        assert mbd_entity.model_deployment_settings.error_threshold == 10
+        assert mbd_entity.model_deployment_settings.mini_batch_size == 5
+        assert mbd_entity.model_deployment_settings.max_concurrency_per_instance == 5
+        assert mbd_entity.resources.instance_count == 2

sdk/ml/azure-ai-ml/tests/test_configs/deployments/batch/model_batch_deployment.yaml

@@ -0,0 +1,24 @@
+name: blue
+endpoint_name: myBatchEndpoint
+model:
+  name: model-1
+  version: 5
+  path: ../model-1/model/sklearn_regression_model.pkl
+code_configuration:
+  code: ../endpoint_scoring
+  scoring_script: ./main.py
+environment: azureml:AzureML-sklearn-1.0-ubuntu20.04-py38-cpu:33
+compute: "azureml:cpu-cluster"
+settings:
+  instance_count: 2
+  retry_settings: #optional
+    max_retries: 3
+    timeout: 30
+  mini_batch_size: 5
+  logging_level: info  #optional, default is info
+  error_threshold: 10 #optional, default is -1
+  output_action: append_row #optional, Allowed Values: append_row, summary_only
+  output_file_name: append_row.txt #optional
+  max_concurrency_per_instance: 5
+  environment_variables:
+    AZUREML_BE: bla