Question

我正在尝试使用Stanfordnlp获取单词的依赖关系。我已经下载了英语模型，并能够加载模型以获得文本中单词的依赖关系。但是，它还将打印整个加载过程消息。

示例代码：

import stanfordnlp

config = {
    'processors': 'tokenize,pos,lemma,depparse', # Comma-separated list of processors to use
    'lang': 'en', # Language code for the language to build the Pipeline in
    'tokenize_model_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt_tokenizer.pt', 
    'pos_model_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt_tagger.pt',
    'pos_pretrain_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt.pretrain.pt',
    'lemma_model_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt_lemmatizer.pt',
    'depparse_model_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt_parser.pt',
    'depparse_pretrain_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt.pretrain.pt'
}

text = 'The weather is nice today.'

# This downloads the English models for the neural pipeline
nlp = stanfordnlp.Pipeline(**config) # This sets up a default neural pipeline in English
doc = nlp(text)
doc.sentences[0].print_dependencies()

>>>

Use device: cpu
---
Loading: tokenize
With settings: 
{'model_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt_tokenizer.pt', 'lang': 'en', 'shorthand': 'en_ewt', 'mode': 'predict'}
---
Loading: pos
With settings: 
{'model_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt_tagger.pt', 'pretrain_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt.pretrain.pt', 'lang': 'en', 'shorthand': 'en_ewt', 'mode': 'predict'}
---
Loading: lemma
With settings: 
{'model_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt_lemmatizer.pt', 'lang': 'en', 'shorthand': 'en_ewt', 'mode': 'predict'}
Building an attentional Seq2Seq model...
Using a Bi-LSTM encoder
Using soft attention for LSTM.
Finetune all embeddings.
[Running seq2seq lemmatizer with edit classifier]
---
Loading: depparse
With settings: 
{'model_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt_parser.pt', 'pretrain_path': 'C:\\path\\stanfordnlp_resources\\en_ewt_models\\en_ewt.pretrain.pt', 'lang': 'en', 'shorthand': 'en_ewt', 'mode': 'predict'}
Done loading processors!
---
('The', '2', 'det')
('weather', '4', 'nsubj')
('is', '4', 'cop')
('nice', '0', 'root')
('today', '4', 'obl:tmod')
('.', '4', 'punct')

我使用Anaconda安装了Stanfordnlp，并使用Jupyter笔记本电脑。有没有一种方法可以跳过消息，因为我只需要依赖项。

Answer 1

如果您只想摆脱Jupyter笔记本中的这些行，则可以在调用管道之后立即清除输出；

from IPython.display import clear_output

...

nlp = stanfordnlp.Pipeline(**config)
clear_output()

如何在不打印加载处理器消息的情况下加载Stanfordnlp管道

1 个答案: