Update pipeline.py

Fixing bug introduced by a change in the SageMaker SDK.

aws/sagemaker-python-sdk#3141

Author: famestad

ML Pipelines scripts/pipeline.py

@@ -106,12 +106,8 @@ def get_pipeline(
     processing_instance_count = ParameterInteger(
         name="ProcessingInstanceCount", default_value=1
     )
-    processing_instance_type = ParameterString(
-        name="ProcessingInstanceType", default_value="ml.m5.xlarge"
-    )
-    training_instance_type = ParameterString(
-        name="TrainingInstanceType", default_value="ml.m5.xlarge"
-    )
+    processing_instance_type = "ml.m5.xlarge"
+    training_instance_type = "ml.m5.xlarge"
     model_approval_status = ParameterString(
         name="ModelApprovalStatus",
         default_value="PendingManualApproval",  # ModelApprovalStatus can be set to a default of "Approved" if you don't want manual approval.