I am getting this error and it is preventing my code to run. I try to filter the warning but even so it stops the running of my code. I still after many hours does not figure it out hiw to overcome it.
Traceback (most recent call last):
File "/gpfs7kw/linkhome/rech/genlig01/umg16uw/test/expe_5/substitution/augment.py", line 92, in <module>
gen_eda(args.input, output, alpha_sr=alpha_sr, alpha_ri=alpha_ri, alpha_rs=alpha_rs, alpha_rd=alpha_rd, num_aug=num_aug)
File "/gpfs7kw/linkhome/rech/genlig01/umg16uw/test/expe_5/substitution/augment.py", line 79, in gen_eda
aug_sentences = eda(sentence, alpha_sr=alpha_sr, alpha_ri=alpha_ri, alpha_rs=alpha_rs, p_rd=alpha_rd, num_aug=num_aug)
File "/gpfs7kw/linkhome/rech/genlig01/umg16uw/test/expe_5/substitution/substitution.py", line 225, in eda
sent_doc = nlp(sentence)
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/spacy/language.py", line 998, in __call__
doc = self.make_doc(text)
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/spacy/language.py", line 1081, in make_doc
return self.tokenizer(text)
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/spacy_stanza/tokenizer.py", line 83, in __call__
snlp_doc = self.snlp(text)
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/stanza/pipeline/core.py", line 231, in __call__
doc = self.process(doc)
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/stanza/pipeline/core.py", line 225, in process
doc = process(doc)
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/stanza/pipeline/mwt_processor.py", line 33, in process
preds += self.trainer.predict(b)
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/stanza/models/mwt/trainer.py", line 79, in predict
preds, _ = self.model.predict(src, src_mask, self.args['beam_size'])
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/stanza/models/common/seq2seq_model.py", line 296, in predict
is_done = beam[b].advance(log_probs.data[b])
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/stanza/models/common/beam.py", line 86, in advance
prevK = bestScoresId // numWords
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/torch/_tensor.py", line 29, in wrapped
return f(*args, **kwargs)
File "/linkhome/rech/genlig01/umg16uw/.conda/envs/bert/lib/python3.9/site-packages/torch/_tensor.py", line 575, in __floordiv__
return torch.floor_divide(self, other)
UserWarning: floor_divide is deprecated, and will be removed in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values.
To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). (Triggered internally at /opt/conda/conda-bld/pytorch_1623448238472/work/aten/src/ATen/native/BinaryOps.cpp:467.)
Exception ignored in: <_io.FileIO name='test_augmented.txt' mode='wb' closefd=True>
ResourceWarning: unclosed file <_io.TextIOWrapper name='test_augmented.txt' mode='w' encoding='utf-8'>
this the library I import :
# -*- coding: UTF-8 -*-
# !/usr/bin/env python3
import random, pickle, os, csv
import re, string
import string, stanza
import spacy_stanza
import warnings
warnings.filterwarnings("error")
from random import shuffle
# stanza.download('fr')
nlp = spacy_stanza.load_pipeline('fr', processors='tokenize,mwt,pos,lemma')
random.seed(1)
Seems the problem is linked to stanza but I do not know why, I used pip to install it shoud I unsinstall it ?
