Error in `spacy.lang` when training large language model

I’m trying to train a language model on a corpus of ~64 GB of domain specific text. My machine isn’t beefy enough to do it so I spun up an instance on Google Compute Engine that has 356 GB of RAM and left it to work overnight. When I went to bed, it was estimating about 19 more hours to finish creating the databunch:

data_lm = (TextList.from_df(df, path=path)

But I woke up this morning and it had stalled out with this error:

_RemoteTraceback                          Traceback (most recent call last)
Traceback (most recent call last):
  File "/opt/anaconda3/lib/python3.7/site-packages/spacy/", line 50, in get_lang_class
    module = importlib.import_module('.lang.%s' % lang, 'spacy')
  File "/opt/anaconda3/lib/python3.7/importlib/", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
  File "<frozen importlib._bootstrap>", line 983, in _find_and_load
  File "<frozen importlib._bootstrap>", line 967, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 677, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 728, in exec_module
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "/opt/anaconda3/lib/python3.7/site-packages/spacy/lang/en/", line 15, in <module>
    from ...language import Language
  File "/opt/anaconda3/lib/python3.7/site-packages/spacy/", line 15, in <module>
    from .tokenizer import Tokenizer
ImportError: /opt/anaconda3/lib/python3.7/site-packages/spacy/ failed to map segment from shared object

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/opt/anaconda3/lib/python3.7/concurrent/futures/", line 232, in _process_worker
    r = call_item.fn(*call_item.args, **call_item.kwargs)
  File "/opt/anaconda3/lib/python3.7/concurrent/futures/", line 191, in _process_chunk
    return [fn(*args) for args in chunk]
  File "/opt/anaconda3/lib/python3.7/concurrent/futures/", line 191, in <listcomp>
    return [fn(*args) for args in chunk]
  File "/opt/anaconda3/lib/python3.7/site-packages/fastai/text/", line 112, in _process_all_1
    tok = self.tok_func(self.lang)
  File "/opt/anaconda3/lib/python3.7/site-packages/fastai/text/", line 25, in __init__
    self.tok = spacy.blank(lang)
  File "/opt/anaconda3/lib/python3.7/site-packages/spacy/", line 25, in blank
    LangClass = util.get_lang_class(name)
  File "/opt/anaconda3/lib/python3.7/site-packages/spacy/", line 52, in get_lang_class
    raise ImportError(Errors.E048.format(lang=lang))
ImportError: [E048] Can't import language en from spacy.lang.

The above exception was the direct cause of the following exception:

ImportError                               Traceback (most recent call last)
<ipython-input-5-eea942f12256> in <module>
      1 data_lm = (TextList.from_df(df, path=path)
----> 2       .random_split_by_pct(0.1)
      3       .label_for_lm()
      4       .databunch(bs=80))

/opt/anaconda3/lib/python3.7/site-packages/fastai/ in _inner(*args, **kwargs)
    439             self.valid = fv(*args, from_item_lists=True, **kwargs)
    440             self.__class__ = LabelLists
--> 441             self.process()
    442             return self
    443         return _inner

/opt/anaconda3/lib/python3.7/site-packages/fastai/ in process(self)
    493         "Process the inner datasets."
    494         xp,yp = self.get_processors()
--> 495         for ds,n in zip(self.lists, ['train','valid','test']): ds.process(xp, yp, name=n)
    496         #progress_bar clear the outputs so in some case warnings issued during processing disappear.
    497         for ds in self.lists:

/opt/anaconda3/lib/python3.7/site-packages/fastai/ in process(self, xp, yp, name)
    665                     p.warns = []
    666                 self.x,self.y = self.x[~filt],self.y[~filt]
--> 667         self.x.process(xp)
    668         return self

/opt/anaconda3/lib/python3.7/site-packages/fastai/ in process(self, processor)
     72         if processor is not None: self.processor = processor
     73         self.processor = listify(self.processor)
---> 74         for p in self.processor: p.process(self)
     75         return self

/opt/anaconda3/lib/python3.7/site-packages/fastai/text/ in process(self, ds)
    286         tokens = []
    287         for i in progress_bar(range(0,len(ds),self.chunksize), leave=False):
--> 288             tokens += self.tokenizer.process_all(ds.items[i:i+self.chunksize])
    289         ds.items = tokens

/opt/anaconda3/lib/python3.7/site-packages/fastai/text/ 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(, partition_by_cores(texts, self.n_cpus)), [])
    122 class Vocab():

/opt/anaconda3/lib/python3.7/concurrent/futures/ in _chain_from_iterable_of_lists(iterable)
    474     careful not to keep references to yielded objects.
    475     """
--> 476     for element in iterable:
    477         element.reverse()
    478         while element:

/opt/anaconda3/lib/python3.7/concurrent/futures/ 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())

/opt/anaconda3/lib/python3.7/concurrent/futures/ in result(self, timeout)
    423                 raise CancelledError()
    424             elif self._state == FINISHED:
--> 425                 return self.__get_result()
    427             self._condition.wait(timeout)

/opt/anaconda3/lib/python3.7/concurrent/futures/ in __get_result(self)
    382     def __get_result(self):
    383         if self._exception:
--> 384             raise self._exception
    385         else:
    386             return self._result

ImportError: [E048] Can't import language en from spacy.lang.

I’m wondering if I might have still run out of memory. free says I have 135GB still available but I’m not sure if it evicted anything huge after that exception was raised.

jupyter@my-fastai-instance:~$ free -mh
              total        used        free      shared  buff/cache   available
Mem:           307G        171G        135G         11M         91M        133G
Swap:            0B          0B          0B

Any ideas for whether there’s something else to look into before trying to double the memory size and let it run again? The other weird thing I encountered was when rebooting/resizing the instance the conda install seemed to get a bit messed up – I had to reinstall fastai and it complained about pytorch being missing for a bit before fixing itself… maybe it missed reinstalling another dependency?

Working through debugging this, I tried to call the line causing the exception in a fresh notebook and it seems to work so I’m leaning towards memory exhaustion. Going to try again with an ultramem n1-highmem-96 instance with twice the memory and see if it helps any… (edit: apparently ultramem instances can’t have a GPU attached)

I’ve observed random “unexplainable” traces when the code gets low on memory, so I vote for OOM.

Try logging the amount of free memory during your script run.

1 Like

Argh. I think there’s something going wrong here. It’s been running for 4 hours and the estimated time to completion is going up rather than down. It is making progress… just slowly. But if it’s slowing down as the size grows I’m not confident it’s ever going to finish.

Going to try to profile things and dig down to see if I can find what the bottleneck is.

I have been logging memory though and it’s been sticking right at 160 GB used (fluctuating just a bit as it grows then garbage collects I think).