docstr: Generates random state and reward
  Args:
      action (int): Int received from agent representing action to take on state
code: def step(self, action):
      r"""
      Generates random state and reward
      Args:
          action (int): Int received from agent representing action to take on state
      """
      state = torch.rand(self.state_size)
      reward = random.randint(0, 1)
  
      return state, reward
  
file_path: pytorch/benchmarks/distributed/rpc/rl/observer.py
imports: import random
  import time
  import torch
  import torch.distributed.rpc
  from agent import AgentBase
  from torch.distributed.rpc import rpc_sync
label_desc: Use image node_id 4 for calling the ObserverBase obj's underlying member method code with example usage: obj.step(action) and returns: state,  reward