sagemaker-python-sdk
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aws
A library for training and deploying machine learning models on Amazon SageMaker
*Issue #, if available:* *Description of changes:* *Testing done:* ## Merge Checklist _Put an `x` in the boxes that apply. You can also fill these out after creating the PR....
*Issue #, if available:* *Description of changes:* *Testing done:* ## Merge Checklist _Put an `x` in the boxes that apply. You can also fill these out after creating the PR....
**Describe the bug** When running sagemaker python sdk (latest version) on macos, it takes around 25-30 mins to submit the job. No logging or debugging is shown to help tracking...
**Describe the bug** If I try to use modelbuilder to create a deployable model using a pytorch then try to save it I get the following error:- sagemaker.config INFO -...
Describe the bug When creating a model card using model package details, the model card is created and visible from the CLI but is not visible in the Model Cards...
**Describe the bug** The logic to repack model artifact (notably used in MXnet) uses a temp dir under `/tmp`. However, on SageMaker notebook instance classic, this partition is limited in...
**What did you find confusing? Please describe.** In AWS EMR, it's explicitly stated in documentation what .jar files are built in. For example, optimized connector to Amazon Redshift is built...
**Describe the feature you'd like** Currently only training instances are allowed when using @remote (from the sagemaker.remote_function module). This module can be used for processing tasks as well, so it...
**Describe the bug** Trition version is old and affected by this https://github.com/pytorch/pytorch/issues/96937 **To reproduce** See attached issue. **Expected behavior** No leaks. **System information** A description of your system. Please provide:...
**Describe the bug** SageMaker Experiments console, showing not data to create charts for metrics defined in job. I'm currently running a HPO jobs, created by using the HyperparameterTuner object and...
