Compression¶
The following tutorials will help you learn how to use compression techniques with MXNet.
Compression: float16https://mxnet.apache.org/api/faq/float16
How to use float16 in your model to boost training speed.
Gradient Compressionhttps://mxnet.apache.org/api/faq/gradient_compression
How to use gradient compression to reduce communication bandwidth and increase speed.
Inference with Quantized Modelshttps://gluon-cv.mxnet.io/build/examples_deployment/int8_inference.html
How to use quantized GluonCV models for inference on Intel Xeon Processors to gain higher performance.
Compression: int8int8.html
How to use int8 in your model to boost training speed.
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