chore: update integ test

Author: evakravi

src/sagemaker/jumpstart/artifacts.py

@@ -437,6 +437,9 @@ def _retrieve_default_instance_type(
             specified region due to lack of supported computing instances.
     """
 
+    if region is None:
+        region = JUMPSTART_DEFAULT_REGION_NAME
+
     model_specs = verify_model_region_and_return_specs(
         model_id=model_id,
         version=model_version,

tests/integ/sagemaker/jumpstart/script_mode_class/test_inference.py

@@ -13,7 +13,7 @@
 from __future__ import absolute_import
 import os
 
-from sagemaker import image_uris, model_uris, script_uris
+from sagemaker import image_uris, instance_types, model_uris, script_uris
 from sagemaker.jumpstart.constants import INFERENCE_ENTRY_POINT_SCRIPT_NAME
 from sagemaker.model import Model
 from tests.integ.sagemaker.jumpstart.constants import (
@@ -31,8 +31,12 @@
 
 def test_jumpstart_inference_model_class(setup):
 
-    model_id, model_version = "catboost-classification-model", "1.0.0"
-    instance_type, instance_count = "ml.m5.xlarge", 1
+    model_id, model_version = "catboost-classification-model", "1.2.7"
+
+    instance_type = instance_types.retrieve_default(
+        model_id=model_id, model_version=model_version, scope="inference"
+    )
+    instance_count = 1
 
     print("Starting inference...")
 

tests/integ/sagemaker/jumpstart/script_mode_class/test_transfer_learning.py

@@ -13,7 +13,14 @@
 from __future__ import absolute_import
 import os
 
-from sagemaker import hyperparameters, metric_definitions, image_uris, model_uris, script_uris
+from sagemaker import (
+    hyperparameters,
+    instance_types,
+    metric_definitions,
+    image_uris,
+    model_uris,
+    script_uris,
+)
 from sagemaker.estimator import Estimator
 from sagemaker.jumpstart.constants import (
     INFERENCE_ENTRY_POINT_SCRIPT_NAME,
@@ -36,8 +43,13 @@
 def test_jumpstart_transfer_learning_estimator_class(setup):
 
     model_id, model_version = "huggingface-spc-bert-base-cased", "1.2.3"
-    training_instance_type = "ml.p3.2xlarge"
-    inference_instance_type = "ml.p2.xlarge"
+
+    inference_instance_type = instance_types.retrieve_default(
+        model_id=model_id, model_version=model_version, scope="inference"
+    )
+    training_instance_type = instance_types.retrieve_default(
+        model_id=model_id, model_version=model_version, scope="training"
+    )
     instance_count = 1
 
     print("Starting training...")