fix: disable integration tests for Inference Component based endpoint for non supported regions (#1414)

Author: bhaoz

tests/integ/__init__.py

@@ -182,6 +182,26 @@
     "us-west-1",
     "us-west-2",
 ]
+
+INFERENCE_COMPONENT_SUPPORTED_REGIONS = [
+    "ap-south-1",
+    "us-west-2",
+    "ca-central-1",
+    "us-east-1",
+    "us-east-2",
+    "ap-northeast-2",
+    "eu-west-2",
+    "ap-southeast-2",
+    "eu-west-1",
+    "ap-northeast-1",
+    "eu-central-1",
+    "eu-north-1",
+    "ap-southeast-1",
+    "sa-east-1",
+    "me-central-1",
+    "ap-southeast-3",
+]
+
 # Data parallelism need to be tested with p3.16xlarge.
 # The instance type is expensive and not supported in all the regions.
 # Limiting the test to run in IAD and CMH

tests/integ/sagemaker/jumpstart/model/test_jumpstart_model.py

@@ -67,6 +67,10 @@ def test_non_prepacked_jumpstart_model(setup):
     assert response is not None
 
 
+@pytest.mark.skipif(
+    tests.integ.test_region() not in tests.integ.INFERENCE_COMPONENT_SUPPORTED_REGIONS,
+    reason="inference component based endpoint is not supported in certain regions",
+)
 def test_non_prepacked_jumpstart_model_deployed_on_inference_component_based_endpoint(setup):
 
     model_id = "huggingface-llm-falcon-7b-instruct-bf16"  # default g5.2xlarge

tests/integ/test_huggingface.py

@@ -15,6 +15,7 @@
 import os
 
 import pytest
+import tests.integ
 
 from sagemaker.huggingface import HuggingFace, HuggingFaceProcessor
 from sagemaker.huggingface.model import HuggingFaceModel, HuggingFacePredictor
@@ -179,6 +180,10 @@ def test_huggingface_inference(
 @pytest.mark.skip(
     reason="re-enable when above MODEL_BASED endpoint hugging face inference test enabled",
 )
+@pytest.mark.skipif(
+    tests.integ.test_region() not in tests.integ.INFERENCE_COMPONENT_SUPPORTED_REGIONS,
+    reason="inference component based endpoint is not supported in certain regions",
+)
 def test_huggingface_inference_inference_component_based_endpoint(
     sagemaker_session,
     gpu_pytorch_instance_type,

tests/integ/test_inference_component_based_endpoint.py

@@ -15,6 +15,7 @@
 import os
 import sagemaker.predictor
 import sagemaker.utils
+import tests.integ
 import pytest
 
 from sagemaker import image_uris
@@ -114,6 +115,10 @@ def xgboost_model(sagemaker_session, resources, model_update_to_name):
 
 
 @pytest.mark.release
+@pytest.mark.skipif(
+    tests.integ.test_region() not in tests.integ.INFERENCE_COMPONENT_SUPPORTED_REGIONS,
+    reason="inference component based endpoint is not supported in certain regions",
+)
 def test_deploy_single_model_with_endpoint_name(tfs_model, resources):
     endpoint_name = sagemaker.utils.unique_name_from_base("sagemaker-tensorflow-serving")
     predictor = tfs_model.deploy(
@@ -141,6 +146,10 @@ def test_deploy_single_model_with_endpoint_name(tfs_model, resources):
 
 
 @pytest.mark.release
+@pytest.mark.skipif(
+    tests.integ.test_region() not in tests.integ.INFERENCE_COMPONENT_SUPPORTED_REGIONS,
+    reason="inference component based endpoint is not supported in certain regions",
+)
 def test_deploy_update_predictor_with_other_model(
     tfs_model,
     resources,
@@ -198,6 +207,10 @@ def test_deploy_update_predictor_with_other_model(
 
 
 @pytest.mark.release
+@pytest.mark.skipif(
+    tests.integ.test_region() not in tests.integ.INFERENCE_COMPONENT_SUPPORTED_REGIONS,
+    reason="inference component based endpoint is not supported in certain regions",
+)
 def test_deploy_multi_models_without_endpoint_name(tfs_model, resources):
     input_data = {"instances": [1.0, 2.0, 5.0]}
     expected_result = {"predictions": [3.5, 4.0, 5.5]}