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A library for training and deploying machine learning models on Amazon SageMaker

Results 337 sagemaker-python-sdk issues
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I tried to implement model monitoring but I do not understand how to implement it for Image dataset. Specially I am not sure how the 4 dimensional data for the...

component:model monitor

**Description** The feature_definitions attribute of an existing FeatureGroup is empty, although you can get the list of the real feature definitions associated with that FeatureGroup when you do `feature_group.describe().get("FeatureDefinitions")` **Expected...

bug
component: feature store

**Describe the bug** I'm currently using Sagemaker to host a custom ML model deployed to two accounts, homolog, and production. Both endpoints have the same entry point code and were...

bug
component: hosting

*Issue #, if available:* N/A *Description of changes:* Processing Step may evaluate its `arguments` properties more than once, causing unwanted side-effects: the same code is uploaded many times, but only...

**What did you find confusing? Please describe.** I was trying to run the Processing Job in the script mode with a custom dependencies provided through `requirements.txt` file. To do that...

In the [official document](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AthenaDatasetDefinition.html), there are several parameters that are required. However, in this [SDK](https://github.com/aws/sagemaker-python-sdk/blob/b4f05b86a90f4ae202ad7f9b048922ab490731fe/src/sagemaker/dataset_definition/inputs.py#L75), default values for those are set as 'None' Is there any reason not for marking...

**Describe the bug** Trying to use any Processor derived from FrameworkProcessor is bugged with SageMaker Pipelines. There is a problem with the `command` and `entrypoint` parameter, where `command` does not...

bug
component: processing
component: pipelines

**Describe the bug** Inference of PyTorch Model when mapped to Elastic Inference Accelarator is 15 times slow as compared to the CPU inference **To reproduce** I am loading CLIP model...

bug
component: hosting

**Describe the bug** The sagemaker.sklearn.processing SKLearnProcessor object throws a value error when sagemaker.workflow.parameters.ParameterString is passed as instance_type. I have been running the exact same script, and I never had an...

bug
component: pipelines

**Describe the bug** Calling `get_pipeline` when one of the parameters is using a variable or f-string fails. If replace with hard-coded string - everything fine. This was working before and...

component: pipelines