def act()

in run_exp.py [0:0]

• 41 lines of code
• 11 McCabe index (conditional complexity)

def act(i: int, free_queue: mp.SimpleQueue, full_queue: mp.SimpleQueue,
        model: torch.nn.Module, buffers: Buffers, flags):
    try:
        logging.info('Actor %i started.', i)
        timings = prof.Timings()  # Keep track of how fast things are.

        gym_env = Net.create_env(flags)
        seed = i ^ int.from_bytes(os.urandom(4), byteorder='little')
        gym_env.seed(seed)
        env = environment.Environment(gym_env)
        env_output = env.initial()
        agent_output = model(env_output)
        while True:
            index = free_queue.get()
            if index is None:
                break

            # Write old rollout end.
            for key in env_output:
                buffers[key][index][0, ...] = env_output[key]
            for key in agent_output:
                buffers[key][index][0, ...] = agent_output[key]

            # Do new rollout
            for t in range(flags.unroll_length):
                timings.reset()

                with torch.no_grad():
                    agent_output = model(env_output)

                timings.time('model')

                env_output = env.step(agent_output['action'])

                timings.time('step')

                for key in env_output:
                    buffers[key][index][t + 1, ...] = env_output[key]
                for key in agent_output:
                    buffers[key][index][t + 1, ...] = agent_output[key]

                timings.time('write')
            full_queue.put(index)

        if i == 0:
            logging.info('Actor %i: %s', i, timings.summary())

    except KeyboardInterrupt:
        pass  # Return silently.
    except Exception as e:
        logging.error('Exception in worker process %i', i)
        traceback.print_exc()
        print()
        raise e