Credit Model with Sagemaker Linear Model expects 16 arguments, but got 15

[AGrosserHH]

I am running the notebook "Credit Model with Sagemaker Linear Model" at IBM cloud witch Python 3.11 and I am getting an error when running the field
"from sagemaker.amazon.amazon_estimator import get_image_uri

sm_client = session.client('sagemaker')"

then the err occurs:

sagemaker.config INFO - Not applying SDK defaults from location: /etc/xdg/sagemaker/config.yaml
sagemaker.config INFO - Not applying SDK defaults from location: /home/wsuser/.config/sagemaker/config.yaml

---

TypeError Traceback (most recent call last)
Cell In[22], line 1
----> 1 from sagemaker.amazon.amazon_estimator import get_image_uri
3 sm_client = session.client('sagemaker')

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/sagemaker/init.py:18
14 from future import absolute_import
16 import importlib_metadata
---> 18 from sagemaker import estimator, parameter, tuner # noqa: F401
19 from sagemaker.amazon.kmeans import KMeans, KMeansModel, KMeansPredictor # noqa: F401
20 from sagemaker.amazon.pca import PCA, PCAModel, PCAPredictor # noqa: F401

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/sagemaker/estimator.py:110
107 from sagemaker.workflow.parameters import ParameterString
108 from sagemaker.workflow.pipeline_context import PipelineSession, runnable_by_pipeline
--> 110 from sagemaker.mlflow.forward_sagemaker_metrics import log_sagemaker_job_to_mlflow
112 logger = logging.getLogger(name)
115 class EstimatorBase(with_metaclass(ABCMeta, object)): # pylint: disable=too-many-public-methods

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/sagemaker/mlflow/forward_sagemaker_metrics.py:23
21 from typing import Set, Tuple, List, Dict, Generator
22 import boto3
---> 23 import mlflow
24 from mlflow import MlflowClient
25 from mlflow.entities import Metric, Param, RunTag

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/mlflow/init.py:34
31 from mlflow.version import VERSION
33 version = VERSION
---> 34 from mlflow import (
35 artifacts, # noqa: F401
36 client, # noqa: F401
37 config, # noqa: F401
38 data, # noqa: F401
39 exceptions, # noqa: F401
40 models, # noqa: F401
41 projects, # noqa: F401
42 tracking, # noqa: F401
43 )
44 from mlflow.environment_variables import MLFLOW_CONFIGURE_LOGGING
45 from mlflow.utils.lazy_load import LazyLoader

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/mlflow/data/init.py:5
2 from contextlib import suppress
3 from typing import Union
----> 5 from mlflow.data import dataset_registry
6 from mlflow.data import sources as mlflow_data_sources
7 from mlflow.data.dataset import Dataset

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/mlflow/data/dataset_registry.py:137
135 # use contextlib suppress to ignore import errors
136 with suppress(ImportError):
--> 137 from mlflow.data.pandas_dataset import from_pandas
139 _dataset_registry.register_constructor(from_pandas)
140 with suppress(ImportError):

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/mlflow/data/pandas_dataset.py:12
10 from mlflow.data.digest_utils import compute_pandas_digest
11 from mlflow.data.evaluation_dataset import EvaluationDataset
---> 12 from mlflow.data.pyfunc_dataset_mixin import PyFuncConvertibleDatasetMixin, PyFuncInputsOutputs
13 from mlflow.exceptions import MlflowException
14 from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/mlflow/data/pyfunc_dataset_mixin.py:6
3 from typing import List
5 from mlflow.data.evaluation_dataset import EvaluationDataset
----> 6 from mlflow.models.utils import PyFuncInput, PyFuncOutput
9 @DataClass
10 class PyFuncInputsOutputs:
11 inputs: List[PyFuncInput]

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/mlflow/models/init.py:75
73 try:
74 from mlflow.models.python_api import predict
---> 75 from mlflow.models.signature import ModelSignature, infer_signature, set_signature
76 from mlflow.models.utils import (
77 ModelInputExample,
78 add_libraries_to_model,
(...)
81 validate_serving_input,
82 )
84 all += [
85 "ModelSignature",
86 "ModelInputExample",
(...)
93 "validate_serving_input",
94 ]

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/mlflow/models/signature.py:21
19 from mlflow.models import Model
20 from mlflow.models.model import MLMODEL_FILE_NAME
---> 21 from mlflow.models.utils import _contains_params, _Example
22 from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE, RESOURCE_DOES_NOT_EXIST
23 from mlflow.store.artifact.models_artifact_repo import ModelsArtifactRepository

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/mlflow/models/utils.py:50
47 HAS_SCIPY = False
49 try:
---> 50 from pyspark.sql import DataFrame as SparkDataFrame
51 from pyspark.sql import Row
52 from pyspark.sql.types import (
53 ArrayType,
54 BinaryType,
(...)
60 TimestampType,
61 )

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/pyspark/init.py:46
43 import types
45 from pyspark.conf import SparkConf
---> 46 from pyspark.context import SparkContext
47 from pyspark.rdd import RDD
48 from pyspark.files import SparkFiles

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/pyspark/context.py:31
27 from tempfile import NamedTemporaryFile
29 from py4j.protocol import Py4JError
---> 31 from pyspark import accumulators
32 from pyspark.accumulators import Accumulator
33 from pyspark.broadcast import Broadcast, BroadcastPickleRegistry

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/pyspark/accumulators.py:97
95 import socketserver as SocketServer
96 import threading
---> 97 from pyspark.cloudpickle import CloudPickler
98 from pyspark.serializers import read_int, PickleSerializer
101 all = ['Accumulator', 'AccumulatorParam']

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/pyspark/cloudpickle.py:146
126 else:
127 return types.CodeType(
128 co.co_argcount,
129 co.co_kwonlyargcount,
(...)
142 (),
143 )
--> 146 _cell_set_template_code = _make_cell_set_template_code()
149 def cell_set(cell, value):
150 """Set the value of a closure cell.
151 """

File /opt/conda/envs/Python-RT24.1-Premium/lib/python3.11/site-packages/pyspark/cloudpickle.py:127, in _make_cell_set_template_code()
110 return types.CodeType(
111 co.co_argcount,
112 co.co_nlocals,
(...)
124 (),
125 )
126 else:
--> 127 return types.CodeType(
128 co.co_argcount,
129 co.co_kwonlyargcount,
130 co.co_nlocals,
131 co.co_stacksize,
132 co.co_flags,
133 co.co_code,
134 co.co_consts,
135 co.co_names,
136 co.co_varnames,
137 co.co_filename,
138 co.co_name,
139 co.co_firstlineno,
140 co.co_lnotab,
141 co.co_cellvars, # this is the trickery
142 (),
143 )

TypeError: code expected at least 16 arguments, got 15