遇到了如下的问题

[slccccccc]

PGL和PaddlePaddle版本号：
paddlepaddle 2.6.2
pgl 2.2.4
系统环境：
windows11

Exception in thread Thread-1:
Traceback (most recent call last):
File "C:\Users\10453.conda\envs\g\lib\site-packages\pgl\utils\mp_reader.py", line 157, in pipe_reader
p.start()
File "C:\Users\10453.conda\envs\g\lib\multiprocessing\process.py", line 121, in start
self._popen = self._Popen(self)
File "C:\Users\10453.conda\envs\g\lib\multiprocessing\context.py", line 224, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:\Users\10453.conda\envs\g\lib\multiprocessing\context.py", line 327, in _Popen
return Popen(process_obj)
File "C:\Users\10453.conda\envs\g\lib\multiprocessing\popen_spawn_win32.py", line 93, in init
reduction.dump(process_obj, to_child)
File "C:\Users\10453.conda\envs\g\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
AttributeError: Can't pickle local object 'multiprocess_reader.._read_into_pipe'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\10453.conda\envs\g\lib\threading.py", line 932, in _bootstrap_inner
self.run()
File "C:\Users\10453.conda\envs\g\lib\threading.py", line 870, in run
self._target(*self._args, **self._kwargs)
File "C:\Users\10453.conda\envs\g\lib\site-packages\paddle\reader\decorator.py", line 333, in read_worker
for d in r:
File "C:\Users\10453.conda\envs\g\lib\site-packages\pgl\utils\mp_reader.py", line 159, in pipe_reader
raise RuntimeError(
RuntimeError: The program met some problems. If your system is Mac OS and python >= 3.8, please checkout #305 to fix the problem.
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\10453.conda\envs\g\lib\multiprocessing\spawn.py", line 107, in spawn_main
new_handle = reduction.duplicate(pipe_handle,
File "C:\Users\10453.conda\envs\g\lib\multiprocessing\reduction.py", line 79, in duplicate
return _winapi.DuplicateHandle(
OSError: [WinError 6] 句柄无效。

[slccccccc]

train_loss, train_rmse, train_r2, train_mse = train(model, criterion, optimizer, train_dataloader)
def train(model, criterion, optimizer, dataloader):

model.train()
list_loss = []
train_pred, train_label = [], []
for graphs, proteins_seq, labels in dataloader:
    graphs = graphs.tensor()
    proteins_seq = paddle.to_tensor(proteins_seq)
    labels = paddle.to_tensor(labels)
    
    preds = model(graphs, proteins_seq)
    loss = criterion(preds, labels)
    
    loss.backward()
    optimizer.step()
    optimizer.clear_grad()
    list_loss.append(loss.numpy())
    
    train_pred.append(preds.numpy())
    train_label.append(labels)
    
train_pred = np.concatenate(train_pred, 0).flatten()
train_label = np.concatenate(train_label, 0).flatten()

mse = ((train_label - train_pred) ** 2).mean(axis=0)  
rmse = np.sqrt(mean_squared_error(train_label, train_pred))
r2 = r2_score(train_label, train_pred)
return np.mean(list_loss), rmse, r2, mse 

中间某步导致了这样的报错