class_docstr: Preparer for sequence labeling.
docstr: Load a raw file. Return text and label.
  For single text input, text: [sentence1, ...]
  For multiple text inputs, text: [[sentence1_1, ...], [sentence1_2, ...]]
  For single output, label: [label1, label2, ...]
  For multiple outputs, label: [[label1_1, ...], [label1_2, ...]]
docstr_tok: ["Load","a","raw","file",".","Return","text","and","label",".","For","single","text","input",",","text",":","[","sentence1",",","...","]","For","multiple","text","inputs",",","text",":","[","[","sentence1_1",",","...","]",",","[","sentence1_2",",","...","]","]","For","single","output",",","label",":","[","label1",",","label2",",","...","]","For","multiple","outputs",",","label",":","[","[","label1_1",",","...","]",",","[","label1_2",",","...","]","]"]
code: def load_a_raw_file(self, one_path, infer_without_label):
      """
      Load a raw file. Return text and label.
      For single text input, text: [sentence1, ...]
      For multiple text inputs, text: [[sentence1_1, ...], [sentence1_2, ...]]
      For single output, label: [label1, label2, ...]
      For multiple outputs, label: [[label1_1, ...], [label1_2, ...]]
      """
      if infer_without_label:
          column_num = 1
      else:
          column_num = 2
      ds_list = load_textline_dataset(one_path, column_num)
      if infer_without_label:
          text = ds_list
          label = []
      else:
          text = ds_list[1:]
          label = ds_list[:1]
      return (text, label)
  
file_path: delta/delta/data/preprocess/text_seq_label_preparer.py
imports: from delta.data.preprocess.base_preparer import TextPreparer
  from delta.data.preprocess.text_ops import load_textline_dataset
  from delta.data import utils
  from delta.utils.register import registers
label_desc: Use image node_id 1 for calling the TextSeqLabelPreparer obj's underlying member method code with example usage: obj.load_a_raw_file(one_path, infer_without_label) and returns: text,  label