fix: update broken integ tests

And refactor some others to use SimpleBaseSerializer

Author: athewsey

doc/frameworks/xgboost/using_xgboost.rst

@@ -192,8 +192,7 @@ inference against your model.
 
 .. code::
 
-    serializer = StringSerializer()
-    serializer.CONTENT_TYPE = "text/libsvm"
+    serializer = StringSerializer(content_type="text/libsvm")
 
     predictor = estimator.deploy(
         initial_instance_count=1,

tests/integ/test_byo_estimator.py

@@ -20,7 +20,7 @@
 import sagemaker
 from sagemaker import image_uris
 from sagemaker.estimator import Estimator
-from sagemaker.serializers import BaseSerializer
+from sagemaker.serializers import SimpleBaseSerializer
 from sagemaker.utils import unique_name_from_base
 from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, datasets
 from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
@@ -36,9 +36,8 @@ def training_set():
     return datasets.one_p_mnist()
 
 
-class _FactorizationMachineSerializer(BaseSerializer):
-
-    CONTENT_TYPE = "application/json"
+class _FactorizationMachineSerializer(SimpleBaseSerializer):
+    # SimpleBaseSerializer already uses "application/json" CONTENT_TYPE by default
 
     def serialize(self, data):
         js = {"instances": []}

tests/integ/test_neo_mxnet.py

@@ -72,8 +72,7 @@ def test_attach_deploy(
             output_path=estimator.output_path,
         )
 
-        serializer = JSONSerializer()
-        serializer.CONTENT_TYPE = "application/vnd+python.numpy+binary"
+        serializer = JSONSerializer(content_type="application/vnd+python.numpy+binary")
 
         predictor = estimator.deploy(
             1,
@@ -112,8 +111,7 @@ def test_deploy_model(
             sagemaker_session=sagemaker_session,
         )
 
-        serializer = JSONSerializer()
-        serializer.CONTENT_TYPE = "application/vnd+python.numpy+binary"
+        serializer = JSONSerializer(content_type="application/vnd+python.numpy+binary")
 
         model.compile(
             target_instance_family=cpu_instance_family,
@@ -165,8 +163,7 @@ def test_inferentia_deploy_model(
             output_path="/".join(model_data.split("/")[:-1]),
         )
 
-        serializer = JSONSerializer()
-        serializer.CONTENT_TYPE = "application/vnd+python.numpy+binary"
+        serializer = JSONSerializer(content_type="application/vnd+python.numpy+binary")
 
         predictor = model.deploy(
             1, inf_instance_type, serializer=serializer, endpoint_name=endpoint_name

tests/integ/test_tuner.py

@@ -28,7 +28,7 @@
 from sagemaker.estimator import Estimator
 from sagemaker.mxnet.estimator import MXNet
 from sagemaker.pytorch import PyTorch
-from sagemaker.serializers import BaseSerializer
+from sagemaker.serializers import SimpleBaseSerializer
 from sagemaker.tensorflow import TensorFlow
 from sagemaker.tuner import (
     IntegerParameter,
@@ -884,9 +884,8 @@ def test_tuning_byo_estimator(sagemaker_session, cpu_instance_type):
 
 
 # Serializer for the Factorization Machines predictor (for BYO example)
-class _FactorizationMachineSerializer(BaseSerializer):
-
-    CONTENT_TYPE = "application/json"
+class _FactorizationMachineSerializer(SimpleBaseSerializer):
+    # SimpleBaseSerializer already uses "application/json" CONTENT_TYPE by default
 
     def serialize(self, data):
         js = {"instances": []}

tests/integ/test_tuner_multi_algo.py

@@ -21,7 +21,7 @@
 from sagemaker.analytics import HyperparameterTuningJobAnalytics
 from sagemaker.deserializers import JSONDeserializer
 from sagemaker.estimator import Estimator
-from sagemaker.serializers import BaseSerializer
+from sagemaker.serializers import SimpleBaseSerializer
 from sagemaker.tuner import ContinuousParameter, IntegerParameter, HyperparameterTuner
 from tests.integ import datasets, DATA_DIR, TUNING_DEFAULT_TIMEOUT_MINUTES
 from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
@@ -219,9 +219,8 @@ def _create_training_inputs(sagemaker_session):
     return {"train": s3_train_data, "test": s3_train_data}
 
 
-class PredictionDataSerializer(BaseSerializer):
-
-    CONTENT_TYPE = "application/json"
+class PredictionDataSerializer(SimpleBaseSerializer):
+    # SimpleBaseSerializer already uses "application/json" CONTENT_TYPE by default
 
     def serialize(self, data):
         js = {"instances": []}