python - AttributeError：“NoneType”对象没有属性“_global_run_stack”

Question

描述

我正在使用带有 A3C 模型的 PTAN 库，我正在尝试使用wandb 扫描，但我遇到了一些奇怪的问题，我不确定这是否是关于扫描的错误（因为如果我只想使用一个简单的模型没有任何涉及的线程将正常工作）或者我做错了什么。

如何重现

训练功能：

def train(conf):
    batch = []
    step_idx = 0
    epoch = conf['epochs']
    try:
        with commune.RewardTracker(writer, stop_reward=conf['reward_bound']) as tracker:
            with ptan.common.utils.TBMeanTracker(writer, batch_size=100) as tb_tracker:
                while True:
                    if step_idx == epoch:
                        break
                    train_entry = train_queue.get()
                    if isinstance(train_entry, TotalReward):
                        if tracker.reward(train_entry.reward, step_idx):
                            break
                        continue
                    if isinstance(train_entry, TotalProfit):
                        tracker.profits(train_entry.total_profit, train_entry.curr_profit, step_idx)
                        continue
                    step_idx += 1
                    if step_idx % 100 == 0:
                        torch.save(net.state_dict(), os.path.join(SAVING_FOLDER, PROJECT_NAME))

                    batch.append(train_entry)
                    if len(batch) < conf['batch_size']:
                        continue

                    states_v, actions_t, vals_ref_v = commune.unpack_batch(batch, net,
                                                                           last_val_gamma=conf['gamma'] ** conf['reward_steps'],
                                                                           device=device)
                    batch.clear()

                    optimizer.zero_grad()
                    logits_v, value_v = net(states_v)

                    loss_value_v = F.mse_loss(value_v.squeeze(-1), vals_ref_v)

                    log_prob_v = F.log_softmax(logits_v, dim=1)
                    adv_v = vals_ref_v - value_v.detach()
                    log_prob_actions_v = adv_v * log_prob_v[range(conf['batch_size']), actions_t]
                    loss_policy_v = -log_prob_actions_v.mean()

                    prob_v = F.softmax(logits_v, dim=1)
                    entropy_loss_v = conf['entropy_beta'] * (prob_v * log_prob_v).sum(dim=1).mean()

                    loss_v = entropy_loss_v + loss_value_v + loss_policy_v
                    loss_v.backward()
                    nn_utils.clip_grad_norm_(net.parameters(), conf['clip_grad'])
                    optimizer.step()

                    tb_tracker.track("advantage", adv_v, step_idx)
                    tb_tracker.track("values", value_v, step_idx)
                    tb_tracker.track("batch_rewards", vals_ref_v, step_idx)
                    tb_tracker.track("loss_entropy", entropy_loss_v, step_idx)
                    tb_tracker.track("loss_policy", loss_policy_v, step_idx)
                    tb_tracker.track("loss_value", loss_value_v, step_idx)
                    tb_tracker.track("loss_total", loss_v, step_idx)
    finally:
        for p in data_proc_list:
            p.terminate()
            p.join()

主功能：

if __name__ == "__main__":
    mp.set_start_method('fork')
    device = torch.device("cuda:0" if use_cuda else "cpu")

    with open(r'sweep_config.yaml') as file:
        sweep_config = yaml.load(file, Loader=yaml.FullLoader)

    logs_dir_name = "a3c_stock"
    wandb.tensorboard.patch(root_logdir=logs_dir_name)

    sweep_id = wandb.sweep(sweep_config, project="sweep_project", entity="vildnex")
    wandb.init(config=config_default)

    config = wandb.config

    writer = SummaryWriter(comment=logs_dir_name)

    env = make_env(config)
    net = commune.AtariA2C(env.observation_space.shape, env.action_space.n).to(device)
    net.share_memory()

    if not os.path.isdir(SAVING_FOLDER):
        os.mkdir(SAVING_FOLDER)

    if os.path.isfile(os.path.join(SAVING_FOLDER, PROJECT_NAME)):
        net.load_state_dict(torch.load(os.path.join(SAVING_FOLDER, PROJECT_NAME), map_location=device))

    optimizer = optim.RMSprop(net.parameters(), lr=config.learning_rate, eps=1e-3)

    train_queue = mp.Queue(maxsize=config.processes_count)
    data_proc_list = []
    dict_conf = dict(config)
    for _ in range(config.processes_count):
        data_proc = mp.Process(target=data_func, args=(net, device, train_queue, dict_conf))
        data_proc.start()
        data_proc_list.append(data_proc)

    wandb.agent(sweep_id, lambda: train(dict_conf))

错误信息：

Exception in thread Thread-6:
Traceback (most recent call last):
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/agents/pyagent.py", line 303, in _run_job
    self._function()
  File "<PATH>/RL_TraningBot/EXPERIMENTS/A3C_TEST.py", line 191, in <lambda>
    wandb.agent(sweep_id, lambda: train(dict_conf))
  File "<PATH>/RL_TraningBot/EXPERIMENTS/A3C_TEST.py", line 105, in train
    tracker.profits(train_entry.total_profit, train_entry.curr_profit, step_idx)
  File "<PATH>/RL_TraningBot/EXPERIMENTS/commune.py", line 118, in profits
    self.writer.add_scalar("total_profit", total_profit, frame)
  File "<PATH>/venv/lib/python3.9/site-packages/torch/utils/tensorboard/writer.py", line 344, in add_scalar
    self._get_file_writer().add_summary(
  File "<PATH>/venv/lib/python3.9/site-packages/torch/utils/tensorboard/writer.py", line 250, in _get_file_writer
    self.file_writer = FileWriter(self.log_dir, self.max_queue,
  File "<PATH>/venv/lib/python3.9/site-packages/torch/utils/tensorboard/writer.py", line 60, in __init__
    self.event_writer = EventFileWriter(
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/integration/tensorboard/monkeypatch.py", line 157, in __init__
    _notify_tensorboard_logdir(logdir, save=save, root_logdir=root_logdir_arg)
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/integration/tensorboard/monkeypatch.py", line 167, in _notify_tensorboard_logdir
    wandb.run._tensorboard_callback(logdir, save=save, root_logdir=root_logdir)
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 804, in _tensorboard_callback
    self._backend.interface.publish_tbdata(logdir, save, root_logdir)
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/sdk/interface/interface.py", line 202, in publish_tbdata
    self._publish(rec)
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/sdk/interface/interface.py", line 518, in _publish
    raise Exception("The wandb backend process has shutdown")
Exception: The wandb backend process has shutdown

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/lib/python3.9/threading.py", line 954, in _bootstrap_inner
    self.run()
  File "/usr/lib/python3.9/threading.py", line 892, in run
    self._target(*self._args, **self._kwargs)
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/agents/pyagent.py", line 308, in _run_job
    wandb.finish(exit_code=1)
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 2374, in finish
    wandb.run.finish(exit_code=exit_code)
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 1144, in finish
    if self._wl and len(self._wl._global_run_stack) > 0:
  File "<PATH>/venv/lib/python3.9/site-packages/wandb/sdk/wandb_setup.py", line 234, in __getattr__
    return getattr(self._instance, name)
AttributeError: 'NoneType' object has no attribute '_global_run_stack'

环境

• 操作系统：Manjaro 5.21.5
• 环境：PyCharm 本地
• Python版本：3.9

标签： pythonpytorchsweeperwandb