TypeError: blank() got an unexpected keyword argument 'disable'

helenas · February 8, 2021, 4:57pm

I am running a text classification model in production that has been using fastai 1.0.60. I chose not to update to fastai v2 because there were bugs around using load_learner() and loading a pretrained model. Up until early January, this method was working perfectly, but now I am getting this error when running learn.predict(). The input is a string, so no idea why this error is popping up. Has anyone else faced this issue? Thanks!

torch == 1.4.0
fastai == 1.0.60

path = ‘files/modelsavelocation’
learn = load_learner(path, ‘final_whole’)
learn.predict(‘How can I find bios?’)

TypeError Traceback (most recent call last)
in
----> 1 learn.predict(‘How can I find bios?’)

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/basic_train.py in predict(self, item, return_x, batch_first, with_dropout, **kwargs)
370 def predict(self, item:ItemBase, return_x:bool=False, batch_first:bool=True, with_dropout:bool=False, **kwargs):
371 “Return predicted class, label and probabilities for item.”
→ 372 batch = self.data.one_item(item)
373 res = self.pred_batch(batch=batch, with_dropout=with_dropout)
374 raw_pred,x = grab_idx(res,0,batch_first=batch_first),batch[0]

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/basic_data.py in one_item(self, item, detach, denorm, cpu)
179 “Get item into a batch. Optionally detach and denorm.”
180 ds = self.single_ds
→ 181 with ds.set_item(item):
182 return self.one_batch(ds_type=DatasetType.Single, detach=detach, denorm=denorm, cpu=cpu)
183

/usr/lib/python3.7/contextlib.py in enter(self)
110 del self.args, self.kwds, self.func
111 try:
→ 112 return next(self.gen)
113 except StopIteration:
114 raise RuntimeError(“generator didn’t yield”) from None

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/data_block.py in set_item(self, item)
613 def set_item(self,item):
614 “For inference, will briefly replace the dataset with one that only contains item.”
→ 615 self.item = self.x.process_one(item)
616 yield None
617 self.item = None

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/data_block.py in process_one(self, item, processor)
89 if processor is not None: self.processor = processor
90 self.processor = listify(self.processor)
—> 91 for p in self.processor: item = p.process_one(item)
92 return item
93

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/text/data.py in process_one(self, item)
289
290 def process_one(self, item):
→ 291 return self.tokenizer._process_all_1(_join_texts([item], self.mark_fields, self.include_bos, self.include_eos))[0]
292
293 def process(self, ds):

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/text/transform.py in _process_all_1(self, texts)
110 def _process_all_1(self, texts:Collection[str]) → List[List[str]]:
111 “Process a list of texts in one process.”
→ 112 tok = self.tok_func(self.lang)
113 if self.special_cases: tok.add_special_cases(self.special_cases)
114 return [self.process_text(str(t), tok) for t in texts]

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/text/transform.py in init(self, lang)
23 “Wrapper around a spacy tokenizer to make it a BaseTokenizer.”
24 def init(self, lang:str):
—> 25 self.tok = spacy.blank(lang, disable=[“parser”,“tagger”,“ner”])
26
27 def tokenizer(self, t:str) → List[str]:

TypeError: blank() got an unexpected keyword argument ‘disable’

muellerzr · February 8, 2021, 5:41pm

What’s your version of spacy?

helenas · February 8, 2021, 5:57pm

spacy is version 3.0.1

muellerzr · February 8, 2021, 6:11pm

Can you try again? Jeremy pinned the spacy version to 3.0.0

(You’ll need to install with pip install git+https://github.com/fastai/fastai @helenas)

helenas · February 8, 2021, 6:37pm

Unfortunately, doing this gives me this error:

ImportError                               Traceback (most recent call last)
<command-600356928450651> in <module>
      1 import pandas as pd
      2 import fastai
----> 3 from fastai.text import load_learner
      4 print(fastai.__version__)

ImportError: cannot import name 'load_learner' from 'fastai.text' (/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/text/__init__.py)

I am running this model in Databricks, so I load fastai and torch locally in the notebook to make sure the load_learner error doesn’t happen. .

%pip install torch==1.4.0
%pip install fastai==1.0.60

muellerzr · February 8, 2021, 6:45pm

Pretty sure you need to do:

from fastai.learner import load_learner

helenas · February 8, 2021, 7:41pm

Hi Zachary,

Thank you for the help. I had trained and saved my model using fastai v1 as ‘final_whole’ into the path location listed. Now when I run the following to load the model back, there is this error:

path = '/dbfs/mnt/sdslake/sds/lake/workspaces/eservices/' 
learn = load_learner(path, 'final_whole')

IsADirectoryError Traceback (most recent call last)
in
1 path = ‘/dbfs/mnt/sdslake/sds/lake/workspaces/eservices/’ #/mnt/sdslake/sds/lake/workspaces/eservices/CSAT_data
----> 2 learn = load_learner(path, ‘final_whole’)

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/learner.py in load_learner(fname, cpu, pickle_module)
372 “Load a Learner object in fname, optionally putting it on the cpu”
373 distrib_barrier()
→ 374 res = torch.load(fname, map_location=‘cpu’ if cpu else None, pickle_module=pickle_module)
375 if hasattr(res, ‘to_fp32’): res = res.to_fp32()
376 if cpu: res.dls.cpu()

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/torch/serialization.py in load(f, map_location, pickle_module, **pickle_load_args)
579 pickle_load_args[‘encoding’] = ‘utf-8’
580
→ 581 with _open_file_like(f, ‘rb’) as opened_file:
582 if _is_zipfile(opened_file):
583 # The zipfile reader is going to advance the current file position.

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/torch/serialization.py in _open_file_like(name_or_buffer, mode)
228 def _open_file_like(name_or_buffer, mode):
229 if _is_path(name_or_buffer):
→ 230 return _open_file(name_or_buffer, mode)
231 else:
232 if ‘w’ in mode:

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/torch/serialization.py in init(self, name, mode)
209 class _open_file(_opener):
210 def init(self, name, mode):
→ 211 super(_open_file, self).init(open(name, mode))
212
213 def exit(self, *args):

IsADirectoryError: [Errno 21] Is a directory: ‘/dbfs/mnt/sdslake/sds/lake/workspaces/eservices/’

Alternatively, running this code instead gives the following error:
learn = load_learner(‘/dbfs/mnt/sdslake/sds/lake/workspaces/eservices/final_whole’)

AttributeError: Can’t get attribute ‘FlattenedLoss’ on <module ‘fastai.layers’ from ‘/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/layers.py’>

AttributeError Traceback (most recent call last)
in
1 path = ‘/dbfs/mnt/sdslake/sds/lake/workspaces/eservices/’ #/mnt/sdslake/sds/lake/workspaces/eservices/CSAT_data
----> 2 learn = load_learner(‘/dbfs/mnt/sdslake/sds/lake/workspaces/eservices/final_whole’)

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/learner.py in load_learner(fname, cpu, pickle_module)
372 “Load a Learner object in fname, optionally putting it on the cpu”
373 distrib_barrier()
→ 374 res = torch.load(fname, map_location=‘cpu’ if cpu else None, pickle_module=pickle_module)
375 if hasattr(res, ‘to_fp32’): res = res.to_fp32()
376 if cpu: res.dls.cpu()

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/torch/serialization.py in load(f, map_location, pickle_module, **pickle_load_args)
593 return torch.jit.load(opened_file)
594 return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
→ 595 return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
596
597

/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/torch/serialization.py in _legacy_load(f, map_location, pickle_module, **pickle_load_args)
772 unpickler = pickle_module.Unpickler(f, **pickle_load_args)
773 unpickler.persistent_load = persistent_load
→ 774 result = unpickler.load()
775
776 deserialized_storage_keys = pickle_module.load(f, **pickle_load_args)

AttributeError: Can’t get attribute ‘FlattenedLoss’ on <module ‘fastai.layers’ from ‘/local_disk0/.ephemeral_nfs/envs/pythonEnv-5caaef5d-ec1e-4e25-80d3-38d7a857d092/lib/python3.7/site-packages/fastai/layers.py’>

I think I was facing this issue previously in dealing with the update from fastai v1 to v2, and reverting to fastai==1.0.60 fixed the issue, as the model I’m loading was trained with v1. Do you know what is causing this and how to fix? Thanks!

muellerzr · February 8, 2021, 7:45pm

Yeah, fastai isn’t backwards compatible. So you must use and train fastai and deploy it in whatever version it was, you can’t use a learner trained in v2 with v1 and vice versa

helenas · February 8, 2021, 8:03pm

Thanks Zachary for your help I think that brings me back to my original error:

TypeError: blank() got an unexpected keyword argument ‘disable’

It looks like the error is linked to backwards incompatibility with the new spaCy v3.0 release, so pinning to spacy==2.3.5 resolved the issue. Thanks for your help!

gradz · February 22, 2021, 6:19am

Even with spacy==2.3.5 I still get “TypeError: blank() got an unexpected keyword argument ‘disable’” when creating the IMDB model in 01 intro notebook. Any other suggestions to resolve? Thanks.

f2forest · February 25, 2021, 7:55pm

You should restart your notebook.

helloyi · March 11, 2021, 11:25pm

(WordTokenizer Error) this answer works for me

cdaigneault · April 13, 2021, 12:28pm

Hello Zachary,

I have same problem with error message with “spacy = WordTokenizer()” getting the error message

I am using JupiterLab, I also installed “!pip install git+https://github.com/fastai/fastai” to get spacy version to 3.0.0 as you recommended and I still get the same error message.

to be honest, I get this type of incompatibility often with Fastai lessons, makes me waste lots of time figuring out the issue instead of focusing on real machine learning learning, I wonder if there are any ways to make the lessons more user friendly? I understand that this may be part of the learning, but not sure…

Thanks!

Christian

muellerzr · April 13, 2021, 12:38pm

As others have mentioned in the thread (such as the post just before this) you need spacy to be less than 3.0.0 to 2.2.4

cdaigneault · April 13, 2021, 12:44pm

yes, I also tried 2.2.4 before and get the same error message. the following window shows that I have installed spacy 2.2.4:

cdaigneault · April 13, 2021, 12:51pm

sorry, I closed my JupyterLab session and came back, reinstall spacy==2.2.4 and now it works…I do not know why, but since it works I am happy.

Thanks for the help, really appreciate

symeneses · May 1, 2021, 1:50pm

I created a new class similar to SpacyTokenizer and

import spacy

from fastcore.utils import ifnone, defaults
from fastcore.foundation import L
from spacy.symbols import ORTH

UNK, PAD, BOS, EOS, FLD, TK_REP, TK_WREP, TK_UP, TK_MAJ = "xxunk xxpad xxbos xxeos xxfld xxrep xxwrep xxup xxmaj".split()
defaults.text_spec_tok = [UNK, PAD, BOS, EOS, FLD, TK_REP, TK_WREP, TK_UP, TK_MAJ]

class SpacyTokenizerV3():
"Spacy tokenizer for `lang`"
def __init__(self, lang='en', special_toks=None, buf_sz=5000):
    self.special_toks = ifnone(special_toks, defaults.text_spec_tok)
    nlp = spacy.blank(lang)
    for w in self.special_toks: nlp.tokenizer.add_special_case(w, [{ORTH: w}])
    self.pipe, self.buf_sz = nlp.pipe, buf_sz

def __call__(self, items):
    return (L(doc).attrgot('text') for doc in self.pipe(map(str,items), batch_size=self.buf_sz))

Then I could use the new class to create a tokenizer, doing that I could keep a Spacy at a version higher or equal to 3.0.0.

from functools import partial
from fastai.data.all import RandomSplitter

get_corpus = partial(get_text_files)
tokenizer = SpacyTokenizerV3(lang="de")

dls_lm = DataBlock(
    blocks=TextBlock.from_folder(path, tok=tokenizer, is_lm=True),
    get_items=get_corpus, splitter=RandomSplitter(0.1)
).dataloaders(path, path=path, bs=128, seq_len=80)

muellerzr · May 4, 2021, 4:19pm

The latest fastai now supports spacy 3.x

thudth · August 22, 2022, 3:26pm

I just got the same issue when I started learning NLP by Fastai Courses on Youtube. I used Google Colab to do exercises from these courses. I just pasted everything from the Jupyter guidelines to my notebook but it didn’t run as well. It took me a lot of time to make it run in Google Colab. This issue relates to spacy version. But there’s something strange that I could not explain. If I use GPU runtime environment, I need spacy 2.3.5 version, otherwise, I had to change spacy to 2.2.4 version. I hope that my answer could help someone who are in the same situation. Make sure that you are using fastai version 1 when practicing for the first lessons.