sagemaker-python-sdk
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aws
A library for training and deploying machine learning models on Amazon SageMaker
**Describe the bug** Tensorflow 2.9 inference image is reported as not available by this library, but does exist in registries. **To reproduce** ```python >>> import sagemaker >>> sagemaker.__version__ '2.99.0' >>>...
When registering a pytorch model, using python 3.8, it fails because the requirements.txt includes dependencies (numpy is the one failing in this case, but may be others) that cannot be...
*Description of changes:* Instead of using `print` function use the `logger`. #### General - [x] I have read the [CONTRIBUTING](https://github.com/aws/sagemaker-python-sdk/blob/master/CONTRIBUTING.md) doc - [x] I certify that the changes I am...
**Describe the bug** A SageMaker image classification model is trained using the VMMRdb dataset. While the training job reports 88.5% of validation accuracy, I can't reproduce the same accuracy after...
**Describe the feature you'd like** Python 3.10 is [a currently supported version of Python ](https://devguide.python.org/versions/#versions). The issue is to track Python 3.10 support for the package `sagemaker-python-sdk`. **How would this...
**Describe the feature you'd like** When I register a model created with any of the [Framework Models](https://sagemaker.readthedocs.io/en/stable/api/inference/model.html#sagemaker.model.FrameworkModel) I don't need to repeat the framework and version (necessary to enable inference...
**Describe the bug** Registering a model using SageMaker SDK `model.register()` without specifying `inference_instances` and `transform_instances` fails with the following error: ```python ParamValidationError: Parameter validation failed: Invalid type for parameter InferenceSpecification.SupportedRealtimeInferenceInstanceTypes,...
**Describe the bug** This is the AMI that I am using - I installed docker-compose by setting up the repository as described here - https://docs.docker.com/engine/install/ubuntu/ It is telling me `ImportError:...
**Describe the bug** Environment variables specified at `Estimator` class are not passed to the entry point script when running jobs by `HyperparameterTune` class. **To reproduce** [Dummy entry point script and...
Please add support for `requirements.txt` in [ScriptProcessor](https://sagemaker.readthedocs.io/en/stable/processing.html#sagemaker.processing.ScriptProcessor) similar to other "Script Mode" parts of the SageMaker Python SDK where I can specify [`source_dir`](https://github.com/aws/sagemaker-python-sdk/blob/926690e216dc8a894b564a6716ca3bf2e8dc4568/tests/unit/test_tf_estimator.py#L249)
