code: def get_data(self, path, batch_size=20):
      # Add words to the dictionary
      with open(path, "r") as f:
          tokens = 0
          for line in f:
              words = line.split() + ["<eos>"]
              tokens += len(words)
              for word in words:
                  self.dictionary.add_word(word)
  
      # Tokenize the file content
      ids = torch.LongTensor(tokens)
      token = 0
      with open(path, "r") as f:
          for line in f:
              words = line.split() + ["<eos>"]
              for word in words:
                  ids[token] = self.dictionary.word2idx[word]
                  token += 1
      num_batches = ids.size(0) // batch_size
      ids = ids[: num_batches * batch_size]
      return ids.view(batch_size, -1)
  
file_path: pytorch-tutorial/tutorials/02-intermediate/language_model/data_utils.py
imports: import torch
  import os
label_desc: Use image node_id 2 for calling the Corpus obj's underlying member method code with example usage: obj.get_data(path, batch_size) and returns: ids