code: def _convert_to_spec(
      space: gym.Space, num_agents: int, name: Optional[str] = None
  ) -> types.NestedSpec:
      """Converts multigrid Gym space to an Acme multiagent spec.
  
      Args:
        space: The Gym space to convert.
        num_agents: the number of agents.
        name: Optional name to apply to all return spec(s).
  
      Returns:
        A dm_env spec or nested structure of specs, corresponding to the input
        space.
      """
      # Convert gym specs to acme specs
      spec = _gym_to_spec(space, name)
      # Then change spec indexing from observation-key-first to agent-index-first
      return [_get_single_agent_spec(spec)] * num_agents
  
imports: from typing import Any, Dict, List, Optional
  import warnings
  from acme import specs
  from acme import types
  from acme import wrappers
  from acme.multiagent import types
  from acme.wrappers import multiagent_dict_key_wrapper
  import dm_env
  import gym
  from gym import spaces
  import jax
  import numpy
  import tree
label_desc: Use image node_id 3 for calling a global function with example usage: _convert_to_spec(space, num_agents, name) and returns: unknown