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SageMaker MXNet Inference Toolkit is an open-source library for serving MXNet models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain MXNet model types and utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well.
Features
- SageMaker MXNet Containers is licensed under the Apache 2.0 License
- For training, see SageMaker MXNet Training Toolkit
- Inference and serving with MXNet in SageMaker
- Provides default pre-processing, predict and postprocessing for certain MXNet model types
- Utilizes the SageMaker Inference Toolkit for starting up the model server
- For information on using MXNet on Amazon SageMaker, please refer to the SageMaker Python SDK documentation
Project Samples
