skip hf_pt-inference-latest-dlc-sagemaker-local-test temporarily

Author: malavhs

dlc_developer_config.toml

@@ -37,10 +37,10 @@ deep_canary_mode = false
 [build]
 # Add in frameworks you would like to build. By default, builds are disabled unless you specify building an image.
 # available frameworks - ["autogluon", "huggingface_tensorflow", "huggingface_pytorch", "huggingface_tensorflow_trcomp", "huggingface_pytorch_trcomp", "pytorch_trcomp", "tensorflow", "mxnet", "pytorch", "stabilityai_pytorch"]
-build_frameworks = []
+build_frameworks = ["huggingface_pytorch"]
 
 # By default we build both training and inference containers. Set true/false values to determine which to build.
-build_training = true
+build_training = false
 build_inference = true
 
 # Set do_build to "false" to skip builds and test the latest image built by this PR
@@ -146,7 +146,7 @@ dlc-pr-tensorflow-2-neuron-inference = ""
 
 # HuggingFace Inference
 dlc-pr-huggingface-tensorflow-inference = ""
-dlc-pr-huggingface-pytorch-inference = ""
+dlc-pr-huggingface-pytorch-inference = "huggingface/pytorch/inference/buildspec.yml"
 dlc-pr-huggingface-pytorch-neuron-inference = ""
 
 # Stability AI Inference

test/sagemaker_tests/huggingface/inference/integration/local/test_serving.py

@@ -19,6 +19,7 @@
 from sagemaker.predictor import Predictor
 from sagemaker.serializers import JSONSerializer
 from sagemaker.deserializers import JSONDeserializer
+from packaging.version import Version
 
 from ...integration import model_dir, ROLE, pt_model, tf_model
 from ...utils import local_mode_utils
@@ -60,6 +61,8 @@ def _assert_prediction(predictor):
 @pytest.mark.model("tiny-distilbert")
 @pytest.mark.team("sagemaker-1p-algorithms")
 def test_serve_json(docker_image, framework_version, sagemaker_local_session, instance_type):
+    if "pytorch" in docker_image and Version(framework_version) < Version("2.4"):
+        pytest.skip("Skipping distilbert SM local tests for PT")
     with _predictor(
         model_dir, docker_image, framework_version, sagemaker_local_session, instance_type
     ) as predictor: