Merge branch 'master' into master

Author: mufaddal-rohawala

CHANGELOG.md

@@ -1,5 +1,12 @@
 # Changelog
 
+## v2.182.0 (2023-08-29)
+
+### Features
+
+ * image url for modelmonitor in TLV region
+ * Enable spot training on remote decorator and executor
+
 ## v2.181.0 (2023-08-28)
 
 ### Features

VERSION

@@ -1 +1 @@
-2.181.1.dev0
+2.182.1.dev0

src/sagemaker/image_uri_config/model-monitor.json

@@ -26,7 +26,8 @@
                 "us-east-1": "156813124566",
                 "us-east-2": "777275614652",
                 "us-west-1": "890145073186",
-                "us-west-2": "159807026194"
+                "us-west-2": "159807026194",
+                "il-central-1": "843974653677"
             },
             "repository": "sagemaker-model-monitor-analyzer"
         }

src/sagemaker/image_uris.py

@@ -619,6 +619,7 @@ def _format_tag(tag_prefix, processor, py_version, container_version, inference_
     return "-".join(x for x in (tag_prefix, processor, py_version, container_version) if x)
 
 
+@override_pipeline_parameter_var
 def get_training_image_uri(
     region,
     framework,

src/sagemaker/workflow/utilities.py

@@ -390,8 +390,10 @@ def override_pipeline_parameter_var(func):
     We should remove this decorator after the grace period.
     """
     warning_msg_template = (
-        "The input argument %s of function (%s) is a pipeline variable (%s), which is not allowed. "
-        "The default_value of this Parameter object will be used to override it. "
+        "The input argument %s of function (%s) is a pipeline variable (%s), "
+        "which is interpreted in pipeline execution time only. "
+        "As the function needs to evaluate the argument value in SDK compile time, "
+        "the default_value of this Parameter object will be used to override it. "
         "Please make sure the default_value is valid."
     )
 

tests/unit/sagemaker/image_uris/test_model_monitor.py

@@ -40,6 +40,7 @@
     "us-east-2": "777275614652",
     "us-west-1": "890145073186",
     "us-west-2": "159807026194",
+    "il-central-1": "843974653677",
 }
 
 

tests/unit/sagemaker/workflow/test_processing_step.py

@@ -69,6 +69,7 @@
 from tests.unit import DATA_DIR
 from tests.unit.sagemaker.workflow.conftest import ROLE, BUCKET, IMAGE_URI, INSTANCE_TYPE
 
+HF_INSTANCE_TYPE = "ml.p3.2xlarge"
 DUMMY_S3_SCRIPT_PATH = "s3://dummy-s3/dummy_script.py"
 LOCAL_SCRIPT_PATH = os.path.join(DATA_DIR, "workflow/abalone/preprocessing.py")
 SPARK_APP_JAR_PATH = os.path.join(
@@ -142,7 +143,7 @@
             pytorch_version="1.7",
             role=ROLE,
             instance_count=1,
-            instance_type="ml.p3.2xlarge",
+            instance_type=HF_INSTANCE_TYPE,
         ),
         {"code": DUMMY_S3_SCRIPT_PATH},
     ),
@@ -446,8 +447,15 @@ def test_processing_step_with_framework_processor(
 ):
 
     processor, run_inputs = framework_processor
+    default_instance_type = (
+        HF_INSTANCE_TYPE if type(processor) is HuggingFaceProcessor else INSTANCE_TYPE
+    )
+    instance_type_param = ParameterString(
+        name="ProcessingInstanceType", default_value=default_instance_type
+    )
     processor.sagemaker_session = pipeline_session
     processor.role = ROLE
+    processor.instance_type = instance_type_param
 
     processor.volume_kms_key = "volume-kms-key"
     processor.network_config = network_config
@@ -465,6 +473,7 @@ def test_processing_step_with_framework_processor(
         name="MyPipeline",
         steps=[step],
         sagemaker_session=pipeline_session,
+        parameters=[instance_type_param],
     )
 
     step_args = get_step_args_helper(step_args, "Processing")
@@ -475,6 +484,12 @@ def test_processing_step_with_framework_processor(
         step_args["ProcessingOutputConfig"]["Outputs"][0]["S3Output"]["S3Uri"]
         == processing_output.destination
     )
+    assert (
+        type(step_args["ProcessingResources"]["ClusterConfig"]["InstanceType"]) is ParameterString
+    )
+    step_args["ProcessingResources"]["ClusterConfig"]["InstanceType"] = step_args[
+        "ProcessingResources"
+    ]["ClusterConfig"]["InstanceType"].expr
 
     del step_args["ProcessingInputs"][0]["S3Input"]["S3Uri"]
     del step_def["Arguments"]["ProcessingInputs"][0]["S3Input"]["S3Uri"]