code: def __init__(
      self, path, fields, encoding="utf-8", separator="\t", **kwargs
  ):
      examples = []
      with open(path, encoding=encoding) as input_file:
          for line in input_file:
              a, b = line.split("\t")
              label = a
              words = [w for w in b.split() if w not in "()"]
  
              cur = 0
              spans = []
              stack = []
              for w in b.split():
                  if w == "(":
                      stack.append(cur)
                  elif w == ")":
                      spans.append((stack[-1], cur - 1, w))
                      stack = stack[:-1]
                  else:
                      spans.append((cur, cur, w))
                      cur += 1
              examples.append(
                  data.Example.fromlist((words, label, spans), fields)
              )
      super(ListOpsDataset, self).__init__(examples, fields, **kwargs)
  
file_path: pytorch-struct/examples/data/trees.py
imports: import torchtext.data
  import torch
label_desc: Use image node_id 2 to create a new ListOpsDataset object from inherited base classes: data with example: obj = ListOpsDataset(path, fields, encoding, separator)