To launch an evaluation cycle, you launch the robomaker docker container with docker run --rm --name dr_e --env-file ./robomaker.env --network sagemaker-local -p 8080:5900 -it crr0004/deepracer_robomaker:console -e "METRICS_S3_OBJECT_KEY=custom_files/eval_metrics.json" -e "NUMBER_OF_TRIALS=5" "./run.sh build evaluation.launch"
The reason we use -e "METRICS_S3_OBJECT_KEY=custom_files/eval_metrics.json"
is so the evaluation metrics will be written to an alternate file than the training metric file.
You can change the world by passing -e "WORLD_NAME=<track_name>"
into the container command. E.G docker run --rm --name dr_e --env-file ./robomaker.env --network sagemaker-local -p 8080:5900 -it -e "WORLD_NAME=Tokyo_Training_track" -e "METRICS_S3_OBJECT_KEY=custom_files/eval_metric.json" -e "NUMBER_OF_TRIALS=5" crr0004/deepracer_robomaker:console "./run.sh build evaluation.launch"
.
Look in bucket/custom_files/eval_metrics.json
.