How to run a distributed training job with the SageMaker distributed data parallelism library
The SageMaker distributed data parallelism (SMDDP) library is designed for ease of use and to provide seamless integration with PyTorch.
When training a deep learning model with the SMDDP library on SageMaker, you can focus on writing your training script and model training.
To get started, import the SMDDP library to use its collective operations optimized for AWS. The following topics provide instructions on what to add to your training script depending on which collective operation you want to optimize.
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