hunk.code_window:     "compress_observations": True,
       # === Optimization ===
       # Learning rate for adam optimizer
       "lr": 5e-4,
       # Adam epsilon hyper parameter
       "adam_epsilon": 1e-8,
       # If not None, clip gradients during optimization at this value
  
hunk.labels: keep keep keep keep add keep keep keep
hunk.after_edit:     # Learning rate schedule
       "lr_schedule": None,
  
hunk.file_path: python/ray/rllib/agents/dqn/dqn.py
hunk.type: add
file: #!/usr/bin/env bash
  
  set -e
  
  ROOT_DIR=$(cd "$(dirname "${BASH_SOURCE:-$0}")"; pwd)
  
  pushd "$ROOT_DIR"
  
  # Kill all of the workloads.
  for workload_file in "$ROOT_DIR"/workloads/*; do
    file_name=$(basename -- $workload_file)
    workload_name="${file_name%.*}"
    ray down -y config.yaml --cluster-name="$workload_name" &
  done
  # Wait for all of the ray down commands to finish.
  wait
  
  popd
  