AttributeError: 'NoneType' object has no attribute 'tokenize'

[junwei-h]

Hello, Hit an error while running python .\train.py --config .\config\doc_ner_best.yaml --batch_size 1 --parse --target_dir .\datasets\mytest --keep_order on Windows 10, Python 3.7, no GPU.

Here is the error message: 2022-07-28 14:35:50,789 Reading data from datasets\mytest 2022-07-28 14:35:50,789 Train: datasets\mytest\doc_train.txt 2022-07-28 14:35:50,789 Dev: None 2022-07-28 14:35:50,791 Test: None Traceback (most recent call last): File ".\train.py", line 345, in train_eval_result, train_loss = student.evaluate(loader,out_path=Path('outputs/train.'+config.config['model_name']+'.'+tar_file_name+'.conllu'),embeddings_storage_mode="none",prediction_mode=True) File "C:\Users\ebb\ACE\flair\models\sequence_tagger_model.py", line 2218, in evaluate features = self.forward(batch,prediction_mode=prediction_mode) File "C:\Users\ebb\ACE\flair\models\sequence_tagger_model.py", line 818, in forward self.embeddings.embed(sentences,embedding_mask=self.selection) File "C:\Users\ebb\ACE\flair\embeddings.py", line 184, in embed embedding.embed(sentences) File "C:\Users\ebb\ACE\flair\embeddings.py", line 97, in embed self._add_embeddings_internal(sentences) File "C:\Users\ebb\ACE\flair\embeddings.py", line 2962, in _add_embeddings_internal self._add_embeddings_to_sentences(sentences) File "C:\Users\ebb\ACE\flair\embeddings.py", line 3051, in _add_embeddings_to_sentences subtokenized_sentence = self.tokenizer.tokenize(tokenized_string) AttributeError: 'NoneType' object has no attribute 'tokenize'

The error is trigged by this line: https://github.com/Alibaba-NLP/ACE/blob/main/flair/embeddings.py#L3041 because self.tokenizer is None.

Any suggestions how to debug this issue? Thanks.

btw, the content of doc_train.txt is the following gibberish: -DOCSTART- O

Amazon O predict O Paypal O and O do O 7-11 O for O Canada O and O Hongkong O

[wangxinyu0922]

Sometimes the embeddings cannot read the saved tokenizer correctly. I add some lines in train.py to fix this issue.

[junwei-h]

Still have error using the updated train.py. Here is the error message:

[2022-07-29 21:50:39,054 INFO] loading file https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-large-cased-spiece.model from cache at C:\Users\ebb/.cache\torch\transformers\5b125ba222ff82664771f63cd8fac9696c24b403fc1ab720d537fe2ceaaf0576.8b10bd978b5d01c21303cc761fc9ecd464419b3bf921864a355ba807cfbfafa8
Traceback (most recent call last):
  File ".\train.py", line 206, in <module>
    embedding.add_special_tokens
  File "C:\Users\ebb\.conda\envs\ace_py37\lib\site-packages\torch\nn\modules\module.py", line 585, in __getattr__
    type(self).__name__, name))
AttributeError: 'TransformerWordEmbeddings' object has no attribute 'add_special_tokens'

I had if '/' in name: name = name.split('/')[-1], otherwise I have the error in issue https://github.com/Alibaba-NLP/ACE/issues/42

[wangxinyu0922]

Oops, this line is not needed in the code, fixed it.

[junwei-h]

Another error:

2022-08-01 17:33:40,842 Reading data from datasets\mytest
2022-08-01 17:33:40,843 Train: datasets\mytest\doc_train.txt
2022-08-01 17:33:40,844 Dev: None
2022-08-01 17:33:40,844 Test: None
Traceback (most recent call last):
  File ".\train.py", line 368, in <module>
    train_eval_result, train_loss = student.evaluate(loader,out_path=Path('outputs/train.'+config.config['model_name']+'.'+tar_file_name+'.conllu'),embeddings_storage_mode="none",prediction_mode=True)
  File "C:\Users\ebb\ACE\flair\models\sequence_tagger_model.py", line 2212, in evaluate
    features = self.forward(batch,prediction_mode=prediction_mode)
  File "C:\Users\ebb\ACE\flair\models\sequence_tagger_model.py", line 818, in forward
    self.embeddings.embed(sentences,embedding_mask=self.selection)
  File "C:\Users\ebb\ACE\flair\embeddings.py", line 184, in embed
    embedding.embed(sentences)
  File "C:\Users\ebb\ACE\flair\embeddings.py", line 97, in embed
    self._add_embeddings_internal(sentences)
  File "C:\Users\ebb\ACE\flair\embeddings.py", line 2943, in _add_embeddings_internal
    self.add_document_embeddings_v2(sentences, max_sequence_length = model_max_length, batch_size = 32 if not hasattr(self,'doc_batch_size') else self.doc_batch_size)
  File "C:\Users\ebb\ACE\flair\embeddings.py", line 3570, in add_document_embeddings_v2
    for doc_pos, doc_sent in enumerate(sentence.doc):
AttributeError: 'Sentence' object has no attribute 'doc'

EDIT (debug info): self.name='/home/yongjiang.jy/.flair/embeddings/en-xlmr-first-docv2_10epoch_1batch_4accumulate_0.000005lr_10000lrrate_eng_monolingual_nocrf_fast_norelearn_sentbatch_sentloss_finetune_nodev_saving_ner5/roberta-large' and sentence.batch_pos={}, thus runs the else branch and sentence= Sentence: "-DOCSTART-" - 1 Tokens, has no doc attribute.

[wangxinyu0922]

I didn't consider the scenario for document-level ACE for prediction. I add some tricks in train.py to fix it, you may try it. Moreover, you can also change the test file in the conll 03 dataset to your own testing file (doc_train.txt) and use the --test command for prediction. Note: --test command works if you want to predict only thousands of sentences. If you want to predict millions of sentences, I still suggest using --parse command since it is more CPU memory friendly.

[junwei-h]

Sorry, I still have the same error as before AttributeError: 'Sentence' object has no attribute 'doc'. See the debug info in the previous post.

[junwei-h]

Using the latest code and running python .\train.py --config .\config\doc_ner_best.yaml --batch_size 1 --parse --target_dir .\datasets\mytest --keep_order on Windows 10, Python 3.7, no GPU, I have another error:

Setting embedding mask to the best action: tensor([1., 1., 0., 1., 0., 0., 1., 0., 0., 1., 1., 1.])
2022-08-19 10:56:10,298 Reading data from datasets\mytest
2022-08-19 10:56:10,298 Train: datasets\mytest\doc_train.txt
2022-08-19 10:56:10,298 Dev: None
2022-08-19 10:56:10,299 Test: None
Traceback (most recent call last):
  File ".\train.py", line 379, in <module>
    corpus_data = trainer.assign_corpus(corpus = corpus.train, set_name= args.set_name, corpus_name = args.corpus_name, train_with_doc = True, pretrained_file_dict = config.config['ReinforcementTrainer']['pretrained_file_dict'])
  File "C:\Users\ACE\flair\trainers\reinforcement_trainer.py", line 1402, in assign_corpus
    corpus.reset_sentence_count
AttributeError: 'Subset' object has no attribute 'reset_sentence_count