sagemaker-python-sdk
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aws
A library for training and deploying machine learning models on Amazon SageMaker
**Describe the feature you'd like** A clear and concise description of the functionality you want. Allow to pass arguments to ContainerEntrypoint for sagemaker.estimator.Estimator as ContainerArguments similar to ScriptProcessor ContainerEntrypoint should...
**Describe the bug** Passing a ParameterString parameter in the arguments for Processor throws an error when defining it as part of a pipeline. Getting `TypeError: Object of type ParameterString is...
### Describe the bug HI, I am not sure it is right place to ask, but need a help. I am a beginner of this field and I am struggling...
**Describe the bug** When running a sagemaker pytorch pipeline with two separate pytorch training steps with hyperparameters passed to pytorch estimators, if one sets a hyperparam named "modeA" to e.g....
*Issue #, if available:* *Description of changes:* support kms key in processor pack local code *Testing done:* ## Merge Checklist _Put an `x` in the boxes that apply. You can...
**Describe the bug** My default credentials do not have write access to S3 for a feature, so I need to assume a role using boto/STS. I create all the relevant...
Currently, SageMaker local mode for model training does not allow for adjusting `smh-size`. Defaults to 64MB which is not enough for most use cases. Does not allow for model to...
Hi, The entrypoint script of my training job fails when using the Huggingface estimator with Pytorch because it tries to import Tensorflow, which is not installed in the image. The...
**Describe the bug** Currently, the docker major version is restricted to `docker~=5.0.0` in the [local extras](https://github.com/aws/sagemaker-python-sdk/blob/master/requirements/extras/local_requirements.txt). This makes installing sagemaker into a windows python 3.10 environment quite difficult, or not...
**Describe the bug** When creating a PyTorchModel and deploying to endpoint, using a specified `image_uri`, the model object is has attribute `self.framework_version=None`. In the check for `_is_mms_version` this will cause...
