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Amazon SageMaker Debugger is an offering from AWS which helps you automate the debugging of machine learning training jobs.
This library powers Amazon SageMaker Debugger, and helps you develop better, faster and cheaper models by catching common errors quickly. It allows you to save tensors from training jobs and makes these tensors available for analysis, all through a flexible and powerful API. It supports TensorFlow, PyTorch, MXNet, and XGBoost on Python 3.6+.
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Amazon SageMaker Debugger is an offering from AWS which helps you automate the debugging of machine learning training jobs.
We found that smdebug demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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