fix batch scoring

Author: j-so

.pipelines/diabetes_regression-batchscoring-ci.yml

@@ -49,11 +49,6 @@ stages:
 timeoutInMinutes: 0
 steps:
  - template: code-quality-template.yml
- - template: diabetes_regression-get-model-id-artifact-template.yml
-parameters:
-projectId: '$(resources.pipeline.model-train-ci.projectID)'
-pipelineId: '$(resources.pipeline.model-train-ci.pipelineID)'
-artifactBuildId: ${{parameters.artifactBuildId }}
  - task: AzureCLI@1
 name: publish_batchscore
 inputs:
@@ -66,19 +61,32 @@ stages:
  # Invoke the Python building and publishing a training pipeline
  python -m ml_service.pipelines.diabetes_regression_build_parallel_batchscore_pipeline
 
+ - job: "Get_Model_Artifact"
+displayName: "Get Model Artifact"
+container: mlops
+timeoutInMinutes: 0
+steps:
+ - template: diabetes_regression-get-model-id-artifact-template.yml
+parameters:
+projectId: '$(resources.pipeline.model-train-ci.projectID)'
+pipelineId: '$(resources.pipeline.model-train-ci.pipelineID)'
+artifactBuildId: ${{parameters.artifactBuildId }}
+
  - job: "Run_Batch_Score_Pipeline"
 displayName: "Run Batch Scoring Pipeline"
-dependsOn: "Build_Batch_Scoring_Pipeline"
+dependsOn: ["Build_Batch_Scoring_Pipeline", "Get_Model_Artifact"]
 timeoutInMinutes: 240
 pool: server
 variables:
 pipeline_id: $[ dependencies.Build_Batch_Scoring_Pipeline.outputs['publish_batchscore.pipeline_id']]
+model_name: $[ dependencies.Get_Model_Artifact.outputs['MODEL_NAME']]
+model_version: $[ dependencies.Get_Model_Artifact.outputs['MODEL_VERSION']]
 steps:
  - task: ms-air-aiagility.vss-services-azureml.azureml-restApi-task.MLPublishedPipelineRestAPITask@0
 displayName: 'Invoke Batch Scoring pipeline'
 inputs:
 azureSubscription: '$(WORKSPACE_SVC_CONNECTION)'
 PipelineId: '$(pipeline_id)'
 ExperimentName: '$(EXPERIMENT_NAME)'
-PipelineParameters: '"ParameterAssignments":{"model_name": "$(MODEL_NAME)", "model_version": "$(MODEL_VERSION)"}'
+PipelineParameters: '"ParameterAssignments":{"model_name": "$(model_name)", "model_version": "$(model_version)"}'
 

diabetes_regression/scoring/parallel_batchscore.py

@@ -30,6 +30,7 @@
 importsys
 fromtypingimportList
 fromutil.model_helperimportget_model
+fromazureml.coreimportModel
 
 model=None
 
@@ -64,13 +65,12 @@ def parse_args() -> List[str]:
 foridx, itminenumerate(sys.argv)
 ifitm=="--model_version"
  ]
-
-iflen(model_version_param) ==0:
-raiseValueError(
-"Model name is required but no model name parameter was passed to the script"# NOQA: E501
- )
-
-model_version=model_version_param[0][1]
+model_version= (
+None
+iflen(model_version_param) <1
+orlen(model_version_param[0][1].strip()) ==0# NOQA: E501
+elsemodel_version_param[0][1]
+ )
 
 model_tag_name_param= [
  (sys.argv[idx], sys.argv[idx+1])
@@ -107,15 +107,17 @@ def init():
 try:
 print("Initializing batch scoring script...")
 
+# Get the model using name/version/tags filter
 model_filter=parse_args()
 amlmodel=get_model(
 model_name=model_filter[0],
 model_version=model_filter[1],
 tag_name=model_filter[2],
 tag_value=model_filter[3])
 
+# Load the model using name/version found
 globalmodel
-modelpath=Model.get_model_path(model_name=model_filter[0])
+modelpath=Model.get_model_path(model_name=amlmodel.name, version=amlmodel.version)
 model=joblib.load(modelpath)
 print("Loaded model{}".format(model_filter[0]))
 exceptExceptionasex:

diabetes_regression/util/model_helper.py

@@ -46,19 +46,19 @@ def get_model(
 print("No workspace defined - using current experiment workspace.")
 aml_workspace=get_current_workspace()
 
-iftagnameisnotNoneandtagvalueisnotNone:
+iftag_nameisnotNoneandtag_valueisnotNone:
 model=AMLModel(
 aml_workspace,
 name=model_name,
 version=model_version,
 tags=[[tag_name, tag_value]])
-elif (tagnameisNoneandtagvalueisnotNone) or (
-tagvalueisNoneandtagnameisnotNone
+elif (tag_nameisNoneandtag_valueisnotNone) or (
+tag_valueisNoneandtag_nameisnotNone
  ):
 raiseValueError(
 "model_tag_name and model_tag_value should both be supplied"
 +"or excluded"# NOQA: E501
  )
 else:
-model=AMLModel(aml_workspace, name=env.model_name, version=env.model_version) # NOQA: E501
+model=AMLModel(aml_workspace, name=model_name, version=model_version)# NOQA: E501
 returnmodel

ml_service/pipelines/diabetes_regression_build_parallel_batchscore_pipeline.py

@@ -33,7 +33,6 @@
 Workspace,
 Dataset,
 Datastore,
-Model,
 RunConfiguration,
 )
 fromazureml.pipeline.coreimportPipeline, PipelineData, PipelineParameter
@@ -44,24 +43,6 @@
 fromtypingimportTuple
 
 
-defparse_args() ->Namespace:
-"""
- Parse arguments supplied to the pipeline creation script.
- The only allowed arguments are model_tag_name and model_tag_value
- specifying a custom tag/value pair to help locate a specific model.
-
-
- :returns: Namespace with two attributes model_tag_name and model_tag_value
- and corresponding values
-
- """
-parser=ArgumentParser()
-parser.add_argument("--model_tag_name", default=None, type=str)
-parser.add_argument("--model_tag_value", default=None, type=str)
-args=parser.parse_args()
-returnargs
-
-
 defget_or_create_datastore(
 datastorename: str, ws: Workspace, env: Env, input: bool=True
 ) ->Datastore:
@@ -312,7 +293,6 @@ def get_scoring_pipeline(
 """
  Creates the scoring pipeline.
 
- :param model: The model to use for scoring
  :param scoring_dataset: Data to score
  :param output_loc: Location to save the scoring results
  :param score_run_config: Parallel Run configuration to support
@@ -399,8 +379,6 @@ def build_batchscore_pipeline():
 try:
 env=Env()
 
-args=parse_args()
-
 # Get Azure machine learning workspace
 aml_workspace=Workspace.get(
 name=env.workspace_name,