hunk.code_window:     active_envs = set()
       to_eval = defaultdict(list)
       outputs = []
       # For each environment
       for env_id, agent_obs in unfiltered_obs.items():
           new_episode = env_id not in active_episodes
  
hunk.labels: keep keep add keep keep keep keep
hunk.after_edit:     large_batch_threshold = max(1000, unroll_length * 10) if \
           unroll_length != float("inf") else 5000
  
hunk.file_path: rllib/evaluation/sampler.py
hunk.type: add
file: # This file is generated by `ray project create`
  
  # An unique identifier for the head node and workers of this cluster.
  cluster_name: pytorch-transformers
  
  # The maximum number of workers nodes to launch in addition to the head
  # node. This takes precedence over min_workers. min_workers default to 0.
  max_workers: 1
  
  # Cloud-provider specific configuration.
  provider:
      type: aws
      region: us-west-2
      availability_zone: us-west-2a
  
  # How Ray will authenticate with newly launched nodes.
  auth:
      ssh_user: ubuntu
  