code: def make_multiagent_environment_spec(
      agent_indices: List[str],
  ) -> specs.EnvironmentSpec:
      """Returns dummy multiagent environment spec.
  
      Args:
        agent_indices: a list of agent indices.
      """
      action_spec = _make_multiagent_spec(agent_indices)
      discount_spec = specs.BoundedArray((), np.float32, 0.0, 1.0)
      observation_spec = _make_multiagent_spec(agent_indices)
      reward_spec = _make_multiagent_spec(agent_indices)
      return specs.EnvironmentSpec(
          actions=action_spec,
          discounts=discount_spec,
          observations=observation_spec,
          rewards=reward_spec,
      )
  
imports: from typing import Dict, List
  from acme import specs
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: make_multiagent_environment_spec(agent_indices) and returns: specs