如何使用spacy3.0的nlp.update问题示例

我试图用spacy v3.0来训练我的数据，很明显nlp.update不接受任何元组。下面是一段代码：

import spacy
import random
import json
nlp = spacy.blank("en")
ner = nlp.create_pipe("ner")
nlp.add_pipe('ner')
ner.add_label("label")
# Start the training
nlp.begin_training()
# Loop for 40 iterations
for itn in range(40):
    # Shuffle the training data
    random.shuffle(TRAINING_DATA)
    losses = {}
# Batch the examples and iterate over them
    for batch in spacy.util.minibatch(TRAINING_DATA, size=2):
        texts = [text for text, entities in batch]
        annotations = [entities for text, entities in batch]
# Update the model
        nlp.update(texts, annotations, losses=losses, drop=0.3)
    print(losses)

我收到了一个错误

ValueError                                Traceback (most recent call last)
<ipython-input-79-27d69961629b> in <module>
     18         annotations = [entities for text, entities in batch]
     19 # Update the model
---> 20         nlp.update(texts, annotations, losses=losses, drop=0.3)
     21     print(losses)

~\Anaconda3\lib\site-packages\spacy\language.py in update(self, examples, _, drop, sgd, losses, component_cfg, exclude)
   1086         """
   1087         if _ is not None:
-> 1088             raise ValueError(Errors.E989)
   1089         if losses is None:
   1090             losses = {}

ValueError: [E989] `nlp.update()` was called with two positional arguments. This may be due to a backwards-incompatible change to the format of the training data in spaCy 3.0 onwards. The 'update' function should now be called with a batch of Example objects, instead of `(text, annotation)` tuples. 

我的列车数据如下所示：

[('Part List', {'entities': []}), ('pending', {'entities': []}), ('3D Printing', {'entities': [(0, 11, 'Process')]}), ('Recommended to use a FDM 3D printer with PLA material.', {'entities': [(25, 36, 'Process'), (41, 44, 'Material')]}), ('', {'entities': []}), ('No need supports or rafts.', {'entities': []}), ('Resolution: 0.20mm', {'entities': []}), ('Fill density 20%', {'entities': []}), ('As follows from the analysis, part of the project is devoted to 3D', {'entities': [(64, 66, 'Process')]}), ('printing, as all static components were created using 3D modelling and', {'entities': [(54, 66, 'Process')]}), ('subsequent printing.', {'entities': []}), ('', {'entities': []}), ('In our project, we created several versions of the', {'entities': []}), ('model during modelling, which we will describe and document in the', {'entities': []}), ('following subchapters. As a tool for 3D modelling, we used the Sketchup', {'entities': [(37, 49, 'Process')]}), ('Make tool, version from 2017. The main reason was the high degree of', {'entities': []}), ('intuitiveness and simplicity of the tool, as we had not encountered 3D', {'entities': [(68, 70, 'Process')]}), ('modelling before and needed a relatively flexible and efficient tool to', {'entities': []}), ('guarantee the desired result. with zero previous experience.', {'entities': []}), ('In this version, which is shown in the figures Figure 13 - Version no. 2 side view and Figure 24 - Version no. 2 - front view, for the first time, the specific dimensions of the infuser were clarified and', {'entities': []}), ('modelled. The details of the lower servo attachment, the cable hole in', {'entities': []}), ('the main mast, the winding cylinder mounting, the protrusion on the', {'entities': [(36, 44, 'Process')]}), ('winding cylinder for holding the tea bag, the preparation for fitting', {'entities': []}), ('the wooden and aluminium plate and the shape of the cylinder end that', {'entities': [(15, 25, 'Material')]}), ('exactly fit the servo were also reworked.', {'entities': []}), ('After the creation of this', {'entities': []}), ('version of the model, this model was subsequently officially consulted', {'entities': []}), ('and commented on for the first time.', {'entities': []}), ('In this version, which is shown in the figures Figure 13 - Version no. 2 side view and Figure 24 - Version no. 2 - front view, for the first time, the specific dimensions of the infuser were clarified and', {'entities': []}), ('modelled. The details of the lower servo attachment, the cable hole in', {'entities': []}), ('the main mast, the winding cylinder mounting, the protrusion on the', {'entities': [(36, 44, 'Process')]})]

---

作为一名新的贡献者，我将非常感谢您的帮助。非常感谢

您没有提供您的

列车数据，因此我无法复制它。但是，您应该尝试以下方法：

[('Part List', {'entities': []}), ('pending', {'entities': []}), ('3D Printing', {'entities': [(0, 11, 'Process')]}), ('Recommended to use a FDM 3D printer with PLA material.', {'entities': [(25, 36, 'Process'), (41, 44, 'Material')]}), ('', {'entities': []}), ('No need supports or rafts.', {'entities': []}), ('Resolution: 0.20mm', {'entities': []}), ('Fill density 20%', {'entities': []}), ('As follows from the analysis, part of the project is devoted to 3D', {'entities': [(64, 66, 'Process')]}), ('printing, as all static components were created using 3D modelling and', {'entities': [(54, 66, 'Process')]}), ('subsequent printing.', {'entities': []}), ('', {'entities': []}), ('In our project, we created several versions of the', {'entities': []}), ('model during modelling, which we will describe and document in the', {'entities': []}), ('following subchapters. As a tool for 3D modelling, we used the Sketchup', {'entities': [(37, 49, 'Process')]}), ('Make tool, version from 2017. The main reason was the high degree of', {'entities': []}), ('intuitiveness and simplicity of the tool, as we had not encountered 3D', {'entities': [(68, 70, 'Process')]}), ('modelling before and needed a relatively flexible and efficient tool to', {'entities': []}), ('guarantee the desired result. with zero previous experience.', {'entities': []}), ('In this version, which is shown in the figures Figure 13 - Version no. 2 side view and Figure 24 - Version no. 2 - front view, for the first time, the specific dimensions of the infuser were clarified and', {'entities': []}), ('modelled. The details of the lower servo attachment, the cable hole in', {'entities': []}), ('the main mast, the winding cylinder mounting, the protrusion on the', {'entities': [(36, 44, 'Process')]}), ('winding cylinder for holding the tea bag, the preparation for fitting', {'entities': []}), ('the wooden and aluminium plate and the shape of the cylinder end that', {'entities': [(15, 25, 'Material')]}), ('exactly fit the servo were also reworked.', {'entities': []}), ('After the creation of this', {'entities': []}), ('version of the model, this model was subsequently officially consulted', {'entities': []}), ('and commented on for the first time.', {'entities': []}), ('In this version, which is shown in the figures Figure 13 - Version no. 2 side view and Figure 24 - Version no. 2 - front view, for the first time, the specific dimensions of the infuser were clarified and', {'entities': []}), ('modelled. The details of the lower servo attachment, the cable hole in', {'entities': []}), ('the main mast, the winding cylinder mounting, the protrusion on the', {'entities': [(36, 44, 'Process')]})]

来自spacy.training.example导入示例
对于spacy.util.minibatch中的批（训练数据，大小=2）：
对于文本，批注释：
#创建示例
文档=nlp.make_文档（文本）
示例=示例。来自目录（文档、注释）
#更新模型
nlp.update（[示例]，损失=损失，下降=0.3）
如果阅读错误并查看spacy3.0（）的文档，您将看到在spacy3.0中，
nlp.update
的输入已更改，您需要构造
示例
对象并发送它。这个页面有一些你可以遵循的例子。嘿，非常感谢你的建议，我在我的问题中添加了我的火车数据，我也尝试创建了一个例子，但是我得到了一个错误，doc=nlp.make_doc（text）的输入应该是字符串，但是我已经编辑了答案。现在它传递一个字符串给示例非常感谢！现在可以了。我真的很感谢你的帮助