notebooks in examples folders, they are getting errors for inferencing

in both get_started.ipynb and inference_and_resource_chaining.ipynb, the cells that have .invoke are failing

invoke_result = endpoint.invoke(body=serializer.serialize(test_data_no_target),
content_type='text/csv',
accept='text/csv')

in :7 │
│ │
│ 4 deserializer = CSVDeserializer() │
│ 5 serializer = CSVSerializer() │
│ 6 │
│ ❱ 7 invoke_result = endpoint.invoke(body=serializer.serialize(test_data_no_target), │
│ 8 │ │ │ │ │ │ │ │ content_type='text/csv', │
│ 9 │ │ │ │ │ │ │ │ accept='text/csv') │
│ 10 │
│ │
│ /opt/conda/lib/python3.11/site-packages/sagemaker_core/main/resources.py:136 in wrapper │
│ │
│ 133 │ │ @functools.wraps(func) │
│ 134 │ │ def wrapper(*args, **kwargs): │
│ 135 │ │ │ config = dict(arbitrary_types_allowed=True) │
│ ❱ 136 │ │ │ return validate_call(config=config)(func)(*args, **kwargs) │
│ 137 │ │ │
│ 138 │ │ return wrapper │
│ 139 │
│ │
│ /opt/conda/lib/python3.11/site-packages/pydantic/_internal/_validate_call.py:38 in │
│ wrapper_function │
│ │
│ 35 │ │ │
│ 36 │ │ @functools.wraps(wrapped) │
│ 37 │ │ def wrapper_function(*args, **kwargs): │
│ ❱ 38 │ │ │ return wrapper(*args, **kwargs) │
│ 39 │ │
│ 40 │ # We need to manually update this because `partial` object has no `__name__` and `__ │
│ 41 │ wrapper_function.__name__ = extract_function_name(wrapped) │
│ │
│ /opt/conda/lib/python3.11/site-packages/pydantic/_internal/_validate_call.py:111 in __call__ │
│ │
│ 108 │ │ │ self.__return_pydantic_validator__ = None │
│ 109 │ │
│ 110 │ def __call__(self, *args: Any, **kwargs: Any) -> Any: │
│ ❱ 111 │ │ res = self.__pydantic_validator__.validate_python(pydantic_core.ArgsKwargs(args, │
│ 112 │ │ if self.__return_pydantic_validator__: │
│ 113 │ │ │ return self.__return_pydantic_validator__(res) │
│ 114 │ │ else: │
│ │
│ /opt/conda/lib/python3.11/site-packages/sagemaker_core/main/resources.py:9441 in invoke │
│ │
│ 9438 │ │ response = client.invoke_endpoint(**operation_input_args) │
│ 9439 │ │ logger.debug(f"Response: {response}") │
│ 9440 │ │ │
│ ❱ 9441 │ │ transformed_response = transform(response, "InvokeEndpointOutput") │
│ 9442 │ │ return InvokeEndpointOutput(**transformed_response) │
│ 9443 │ │
│ 9444 │ @Base.add_validate_call │
│ │
│ /opt/conda/lib/python3.11/site-packages/sagemaker_core/main/code_injection/codec.py:248 in │
│ transform │
│ │
│ 245 │ │ │ _map_type_shape = SHAPE_DAG[_member_shape] │
│ 246 │ │ │ evaluated_value = _evaluate_map_type(data[_member_name], _map_type_shape) │
│ 247 │ │ else: │
│ ❱ 248 │ │ │ raise ValueError(f"Unexpected member type encountered: {_member_type}") │
│ 249 │ │ │
│ 250 │ │ result[attribute_name] = evaluated_value │
│ 251 │ │ if object_instance: │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ValueError: Unexpected member type encountered: blob

I am running notebooks inside sagemaker Jupyter

my sagemaker-core version is this

Name: sagemaker-core
Version: 1.0.21
Summary: An python package for sagemaker core functionalities
Home-page:
Author:
Author-email: AWS
License:
Location: /opt/conda/lib/python3.11/site-packages
Requires: boto3, importlib-metadata, jsonschema, mock, platformdirs, pydantic, PyYAML, rich
Required-by: sagemaker
Metadata-Version: 2.2
Installer: pip
Classifiers:
Development Status :: 3 - Alpha
Intended Audience :: Developers
License :: OSI Approved :: Apache Software License
Programming Language :: Python :: 3.8
Programming Language :: Python :: 3.9
Programming Language :: Python :: 3.10
Programming Language :: Python :: 3.11
Programming Language :: Python :: 3.12
Entry-points:
Project-URLs:
Repository, https://github.com/aws/sagemaker-core.git

Start by opening get_started.ipynb and inference_and_resource_chaining.ipynb in SageMaker Jupyter and rerun the cells containing endpoint.invoke. Compare the failures with the sagemaker-core 1.0.21 traceback, and consider the work complete when both notebooks run those inference cells without the reported ValueError.

Written by the indexing model from the issue text.