magnitude

Step-by-Step

This document is used to list steps of reproducing Intel® Neural Compressor magnitude pruning feature.

Prerequisite

1. Environment

Install Intel® Neural Compressor

pip install neural-compressor

Install TensorFlow

pip install tensorflow

Run

Run the command to get pretrained baseline model which will be saved to './baseline_model'. Then, the model will be pruned and saved into a given path. The CIFAR10 dataset will be automatically loaded.

python main.py --output_model=/path/to/output_model/ --prune

If you want to accelerate pruning with multi-node distributed training and evaluation, you only need to add two arguments and use horovod to run main.py. Use horovod to run main.py to get pruned model with multi-node distributed training and evaluation.

horovodrun -np <num_of_processes> -H <hosts> python main.py --output_model=/path/to/output_model/  --train_distributed --evaluation_distributed  --prune

Run the command to get pruned model performance.

python main.py --input_model=/path/to/input_model/ --benchmark