You can try AIO by either running jupyter notebook examples or python scripts on CLI level.
Note: Before running the examples, please run download_models.sh script to pull down all models.
Use AIO_NUM_THREADS to specify the number of cores the AIO compute kernels will run on
export AIO_NUM_THREADS=16
cd /aio-examples/
bash start_notebook.sh
If you run it on a cloud instance, make sure your machine has port 8080 open and on your local device run:
ssh -N -L 8080:localhost:8080 -i <ssh key> your_user@xxx.xxx.xxx.xxx
Use a browser to point to the URL printed out by the Jupyter notebook launcher. You will find Jupyter Notebook examples, examples.ipynb, under /classification and /object_detection folders. The examples run through several inference models, visualize results and present the performance numbers.
To use CLI-level scripts:
Use AIO_NUM_THREADS to specify the number of cores the AIO compute kernels will run on
cd /aio-examples/
Go to the directory of choice, eg.
cd classification/resnet_50_v1
Evaluate the model with run.py script
Optional arguments:
-h, --help show this help message and exit
-p {fp32}, --precision {fp32}
-b BATCH_SIZE, --batch_size BATCH_SIZE
AIO_NUM_THREADS=16 numactl --physcpubind=0-15 python run.py -p fp32