repo_description: Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools, with 10x faster training through evolutionary hyperparameter optimization.
repo_topics: agilerl automl deep-learning deep-reinforcement-learning distributed evolutionary-algorithms gym hpo hyperparameter-optimization hyperparameter-tuning machine-learning mlops multi-agent multi-agent-reinforcement-learning pettingzoo python pytorch reinforcement-learning rlops training
code: """Sitecustomize module to enable coverage tracking in subprocesses.
  
  This file is automatically loaded by Python when the repository root is in PYTHONPATH.
  It starts coverage measurement in subprocesses when COVERAGE_PROCESS_START is set.
  """
  
  import os
  
  import coverage
  
  if os.environ.get("COVERAGE_PROCESS_START"):
      coverage.process_startup()
  