Animated Drawings Performance Tuning
To use the Torchserve benchmark suite, first we need to have an archived file, “.mar” file as discussed above, that contains the model, handler and all other artifacts to load and run inference. Animated Drawings uses Detectron2’s implementation of Mask-RCNN for an object detection model. 
How to run benchmark suite
The Automated benchmark suite in Torchserve let you benchmark multiple models with different setting including batch size and number of worker and finally generate a report for you. To get started:
git clone https://github.com/pytorch/serve.git

cd serve/benchmarks

pip install -r requirements-ab.txt

apt-get install apache2-utils

Model level settings can be configured in a yaml file similar to 
```yaml
Model_name:
    eager_mode:
        benchmark_engine: "ab"
        url: "Path to .mar file"
        workers:
            - 1
            - 4