fix: remove failing deprecated tests from suite

Author: Ashwin Krishna

tests/integ/test_mxnet.py

@@ -384,42 +384,6 @@ def test_deploy_model_and_update_endpoint(
         assert new_config["ProductionVariants"][0]["InitialInstanceCount"] == 1
 
 
-@pytest.mark.skipif(
-    tests.integ.test_region() not in tests.integ.EI_SUPPORTED_REGIONS,
-    reason="EI isn't supported in that specific region.",
-)
-def test_deploy_model_with_accelerator(
-    mxnet_training_job,
-    sagemaker_session,
-    mxnet_eia_latest_version,
-    mxnet_eia_latest_py_version,
-    cpu_instance_type,
-):
-    endpoint_name = unique_name_from_base("test-mxnet-deploy-model-ei")
-
-    with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
-        desc = sagemaker_session.sagemaker_client.describe_training_job(
-            TrainingJobName=mxnet_training_job
-        )
-        model_data = desc["ModelArtifacts"]["S3ModelArtifacts"]
-        script_path = os.path.join(DATA_DIR, "mxnet_mnist", "mnist_ei.py")
-        model = MXNetModel(
-            model_data,
-            "SageMakerRole",
-            entry_point=script_path,
-            framework_version=mxnet_eia_latest_version,
-            py_version=mxnet_eia_latest_py_version,
-            sagemaker_session=sagemaker_session,
-        )
-        predictor = model.deploy(
-            1, cpu_instance_type, endpoint_name=endpoint_name, accelerator_type="ml.eia1.medium"
-        )
-
-        data = numpy.zeros(shape=(1, 1, 28, 28))
-        result = predictor.predict(data)
-        assert result is not None
-
-
 def test_deploy_model_with_serverless_inference_config(
     mxnet_training_job,
     sagemaker_session,

tests/integ/test_tfs.py

@@ -152,20 +152,6 @@ def test_predict(tfs_predictor):
     result = tfs_predictor.predict(input_data)
     assert expected_result == result
 
-
-@pytest.mark.skipif(
-    tests.integ.test_region() not in tests.integ.EI_SUPPORTED_REGIONS,
-    reason="EI is not supported in region {}".format(tests.integ.test_region()),
-)
-@pytest.mark.release
-def test_predict_with_accelerator(tfs_predictor_with_accelerator):
-    input_data = {"instances": [1.0, 2.0, 5.0]}
-    expected_result = {"predictions": [3.5, 4.0, 5.5]}
-
-    result = tfs_predictor_with_accelerator.predict(input_data)
-    assert expected_result == result
-
-
 @pytest.mark.local_mode
 def test_predict_with_entry_point(tfs_predictor_with_model_and_entry_point_same_tar):
     input_data = {"instances": [1.0, 2.0, 5.0]}