我一直在从Wikipedia训练语言模型，以便在FastAi中创建文本分类器。 我一直在使用Google colab。 但是经过几分钟的培训，该过程因以下错误而停止：
get_wiki(path,lang)
dest = split_wiki(path,lang)
bs=64
data = (TextList.from_folder(dest)
.split_by_rand_pct(0.1, seed=42)
.label_for_lm()
.databunch(bs=bs, num_workers=1))
data.save('tmp_lm')
BrokenProcessPool Traceback (most recent call last)
<ipython-input-4-60a9d06cb522> in <module>()
1 bs=64
2 data = (TextList.from_folder(dest)
----> 3 .split_by_rand_pct(0.1, seed=42)
4 .label_for_lm()
5 .databunch(bs=bs, num_workers=1))
9 frames
/usr/local/lib/python3.6/dist-packages/fastai/data_block.py in _inner(*args, **kwargs)
478 self.valid = fv(*args, from_item_lists=True, **kwargs)
479 self.__class__ = LabelLists
--> 480 self.process()
481 return self
482 return _inner
/usr/local/lib/python3.6/dist-packages/fastai/data_block.py in process(self)
532 "Process the inner datasets."
533 xp,yp = self.get_processors()
--> 534 for ds,n in zip(self.lists, ['train','valid','test']): ds.process(xp, yp, name=n)
535 #progress_bar clear the outputs so in some case warnings issued during processing disappear.
536 for ds in self.lists:
/usr/local/lib/python3.6/dist-packages/fastai/data_block.py in process(self, xp, yp, name, max_warn_items)
712 p.warns = []
713 self.x,self.y = self.x[~filt],self.y[~filt]
--> 714 self.x.process(xp)
715 return self
716
/usr/local/lib/python3.6/dist-packages/fastai/data_block.py in process(self, processor)
82 if processor is not None: self.processor = processor
83 self.processor = listify(self.processor)
---> 84 for p in self.processor: p.process(self)
85 return self
86
/usr/local/lib/python3.6/dist-packages/fastai/text/data.py in process(self, ds)
295 tokens = []
296 for i in progress_bar(range(0,len(ds),self.chunksize), leave=False):
--> 297 tokens += self.tokenizer.process_all(ds.items[i:i+self.chunksize])
298 ds.items = tokens
299
/usr/local/lib/python3.6/dist-packages/fastai/text/transform.py in process_all(self, texts)
118 if self.n_cpus <= 1: return self._process_all_1(texts)
119 with ProcessPoolExecutor(self.n_cpus) as e:
--> 120 return sum(e.map(self._process_all_1, partition_by_cores(texts, self.n_cpus)), [])
121
122 class Vocab():
/usr/lib/python3.6/concurrent/futures/process.py in _chain_from_iterable_of_lists(iterable)
364 careful not to keep references to yielded objects.
365 """
--> 366 for element in iterable:
367 element.reverse()
368 while element:
/usr/lib/python3.6/concurrent/futures/_base.py in result_iterator()
584 # Careful not to keep a reference to the popped future
585 if timeout is None:
--> 586 yield fs.pop().result()
587 else:
588 yield fs.pop().result(end_time - time.monotonic())
/usr/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
430 raise CancelledError()
431 elif self._state == FINISHED:
--> 432 return self.__get_result()
433 else:
434 raise TimeoutError()
/usr/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
382 def __get_result(self):
383 if self._exception:
--> 384 raise self._exception
385 else:
386 return self._result
BrokenProcessPool: A process in the process pool was terminated abruptly while the future was running or pending.
我试图通过将bs的值更改为64、32、16来解决此问题。同样更改了num_workers的值，但仍然失败。
该过程如下，ram内存开始填充，大约在过程的一半已满，并停止脚本的执行。
Google Colab Machine的详细信息：
GPU机，RAM：25.51 GB，磁盘：358.27 GB。
最好的问候！