Sagemaker core is unimportable in warnings as error mode due to `SyntaxError: invalid escape sequence: '\|'`

[jmahlik]

Describe the bug
A clear and concise description of what the bug is.

Sagemaker core cannot be imported when running python in warnings as error mode. This comes up a lot in test suites when running pytest in warnings as error mode.

I believe most of this is codegen, so likely will need a fix to the generator to remove invalid escape sequences. Potentially a CI check could be added down the road to ensure the files are importable. There shouldn't be warnings on import either.

To reproduce
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The provided code need to be complete and runnable, if additional data is needed, please include them in the issue.

# In case the venv creation matters
python -m pip install uv
uv venv venv
. venv/Scripts/active

python --version
Python 3.13.1

 python ./src/sagemaker_core/main/shapes.py
C:\sagemaker-core\src\sagemaker_core\main\shapes.py:5799: SyntaxWarning: invalid escape sequence '\|'
  """
C:\sagemaker-core\src\sagemaker_core\main\shapes.py:6604: SyntaxWarning: invalid escape sequence '\*'
  """
C:\sagemaker-core\src\sagemaker_core\main\shapes.py:8812: SyntaxWarning: invalid escape sequence '\*'
  """
C:\sagemaker-core\venv\Lib\site-packages\pydantic\_internal\_fields.py:192: UserWarning: Field name "json" in "MonitoringDatasetFormat" shadows an attribute in parent "Base"
  warnings.warn(


python -W error ./src/sagemaker_core/main/shapes.py
  File "C:\sagemaker-core\src\sagemaker_core\main\shapes.py", line 5799
    """
    ^^^
SyntaxError: invalid escape sequence '\|'

There's multiple files with this issue. I'm not sure how these are passing tests.

git grep -e '\\|'
src/sagemaker_core/main/resources.py:            task: The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION" \| "OBJECT_DETECTION" \| "TEXT_GENERATION" \|"IMAGE_SEGMENTATION" \| "FILL_MASK" \| "CLASSIFICATION" \| "REGRESSION" \| "OTHER". Specify "OTHER" if none of the tasks listed fit your use case.
src/sagemaker_core/main/shapes.py:    domain: The machine learning domain of the model and its components. Valid Values: COMPUTER_VISION \| NATURAL_LANGUAGE_PROCESSING \| MACHINE_LEARNING
src/sagemaker_core/main/shapes.py:    task: The machine learning task that the model accomplishes. Valid Values: IMAGE_CLASSIFICATION \| OBJECT_DETECTION \| TEXT_GENERATION \| IMAGE_SEGMENTATION \| FILL_MASK \| CLASSIFICATION \| REGRESSION \| OTHER
src/sagemaker_core/main/shapes.py:    framework: The machine learning framework of the container image. Valid Values: TENSORFLOW \| PYTORCH \| XGBOOST \| SAGEMAKER-SCIKIT-LEARN
src/sagemaker_core/main/shapes.py:    nearest_model_name: The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model. Valid Values: efficientnetb7 \| unet \| xgboost \| faster-rcnn-resnet101 \| nasnetlarge \| vgg16 \| inception-v3 \| mask-rcnn \| sagemaker-scikit-learn \| densenet201-gluon \| resnet18v2-gluon \| xception \| densenet201 \| yolov4 \| resnet152 \| bert-base-cased \| xceptionV1-keras \| resnet50 \| retinanet

Expected behavior
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No errors nor warnings on import.

Screenshots or logs
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Bug information
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• SageMaker Core version: main
• Python version: 3.13, 3.12, 3.11
• Is the issue with autogen code or with generate code ?: yes

Additional context
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[jmahlik]

One idea to stop codegen generating python files with warnings or invalid code all together.

Somewhere after reformat with black runs and the files are about to be written:

sagemaker-core/src/sagemaker_core/main/utils.py

Line 79 in 1918e57

def reformat_file_with_black(filename):

. Simulate a run of the import to make sure no warnings happen on import.

Something like this.

with warnings.filterwarnings("error"):
    runpy.run_path(file)

[jmahlik]

Related issue in sm_debug_rulesconfig awslabs/sagemaker-debugger-rulesconfig#45 that also prevents the sagemaker python sdk from being imported.