TypeError: slice indices must be integers or None or have an __index__ method

[xtuyaowu]

Building prefix dict from the default dictionary ... Loading model from cache /tmp/jieba.cache Loading model cost 1.034 seconds. Prefix dict has been built succesfully. Found 4313 unique words (979180 in total) Loading pretrained embeddings from data/vec.txt... Found 13 unique named entity tags 20864 / 2318 / 4636 sentences in train / dev / test. Traceback (most recent call last): File "main.py", line 228, in tf.app.run(main) File "/data/app/Anaconda/envs/resume/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 124, in run _sys.exit(main(argv)) File "main.py", line 222, in main train() File "main.py", line 153, in train train_manager = BatchManager(train_data, FLAGS.batch_size) File "/data/app/resumeSpider/Information-Extraction-Chinese/NER_IDCNN_CRF/data_utils.py", line 285, in init self.batch_data = self.sort_and_pad(data, batch_size) File "/data/app/resumeSpider/Information-Extraction-Chinese/NER_IDCNN_CRF/data_utils.py", line 293, in sort_and_pad batch_data.append(self.pad_data(sorted_data[i*batch_size : (i+1)*batch_size])) TypeError: slice indices must be integers or None or have an index method

[LitTianXin]

我也有一样的错误，你解决了吗？

[doubaojun]

我在Linux系统下运行，也是报出这个错误，请教怎么解决呀？

[logye]

应该修改main.py中的数据类型定义 flags.DEFINE_float("batch_size", 20, "batch size") 改为 flags.DEFINE_integer("batch_size", 20, "batch size")

[LitTianXin]

在发生错误的函数里，转换一下数据类型就可以了。 def sort_and_pad(self, data, batch_size): num_batch = int(math.ceil(len(data) //batch_size)) sorted_data = sorted(data, key=lambda x: len(x[0])) batch_data = list() for i in range(num_batch): i=int(i) batch_data.append(self.pad_data(sorted_data[i*batch_size : (i+1)*batch_size])) return batch_data

[doubaojun]

提供的解决方式更改后可以正确运行了，谢谢

[liutianling]

@logye 谢谢，你说的方法很管用。