code: def _register_all():
      from ray.rllib.algorithms.registry import (
          ALGORITHMS,
          _get_algorithm_class,
      )
  
      for key, get_trainable_class_and_config in ALGORITHMS.items():
          register_trainable(key, get_trainable_class_and_config()[0])
  
      for key in [
          "__fake",
          "__sigmoid_fake_data",
          "__parameter_tuning",
      ]:
          register_trainable(key, _get_algorithm_class(key))
  
file_path: ray/python/ray/rllib/__init__.py
imports: import logging
  from ray._private.usage import usage_lib
  from ray.rllib.env.base_env import BaseEnv
  from ray.rllib.env.external_env import ExternalEnv
  from ray.rllib.env.multi_agent_env import MultiAgentEnv
  from ray.rllib.env.vector_env import VectorEnv
  from ray.rllib.evaluation.rollout_worker import RolloutWorker
  from ray.rllib.policy.policy import Policy
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.tf_policy import TFPolicy
  from ray.rllib.policy.torch_policy import TorchPolicy
  from ray.tune.registry import register_trainable
label_desc: Use image node_id 2 for calling a global function with example usage: _register_all() without return types