code: def convert_tass2020(in_directory, out_directory, dataset_name):
      """
      Read all of the data from in_directory/spanish/tass2020, write it to out_directory/dataset_name...
      """
      in_directory = os.path.join(in_directory, "spanish", "tass2020")
  
      pipe = stanza.Pipeline(
          lang="es", processors="tokenize", tokenize_no_ssplit=True
      )
  
      test_11 = {}
      test_11_labels_zip = os.path.join(
          in_directory, "tass2020-test-gold.zip"
      )
      test_11_sentences_zip = os.path.join(in_directory, "Test1.1.zip")
      for piece in DATASET_PIECES:
          inner_label_filename = piece + ".tsv"
          inner_sentence_filename = os.path.join(
              "Test1.1", piece.upper() + ".tsv"
          )
          test_11[piece] = read_test_set(
              test_11_labels_zip,
              inner_label_filename,
              test_11_sentences_zip,
              inner_sentence_filename,
              pipe,
          )
  
      test_12_label_filename = os.path.join(
          in_directory, "task1.2-test-gold.tsv"
      )
      test_12_sentences_zip = os.path.join(in_directory, "test1.2.zip")
      test_12_sentences_filename = "test1.2/task1.2.tsv"
      test_12 = read_test_set(
          None,
          test_12_label_filename,
          test_12_sentences_zip,
          test_12_sentences_filename,
          pipe,
      )
  
      train_dev_zip = os.path.join(in_directory, "Task1-train-dev.zip")
      dev = {}
      train = {}
      for piece in DATASET_PIECES:
          dev_filename = os.path.join("dev", piece + ".tsv")
          dev[piece] = read_train_file(
              train_dev_zip, dev_filename, pipe
          )
  
      for piece in DATASET_PIECES:
          train_filename = os.path.join("train", piece + ".tsv")
          train[piece] = read_train_file(
              train_dev_zip, train_filename, pipe
          )
  
      all_test = test_12 + [
          item for piece in test_11.values() for item in piece
      ]
      all_dev = [item for piece in dev.values() for item in piece]
      all_train = [item for piece in train.values() for item in piece]
  
      print("Total train items: %8d" % len(all_train))
      print("Total dev items:   %8d" % len(all_dev))
      print("Total test items:  %8d" % len(all_test))
  
      write_dataset(
          (all_train, all_dev, all_test), out_directory, dataset_name
      )
  
      output_file = os.path.join(
          out_directory, "%s.test.p2.json" % dataset_name
      )
      write_list(output_file, test_12)
  
      for piece in DATASET_PIECES:
          output_file = os.path.join(
              out_directory,
              "%s.test.p1.%s.json" % (dataset_name, piece),
          )
          write_list(output_file, test_11[piece])
  
file_path: stanza/stanza/utils/datasets/sentiment/process_es_tass2020.py
imports: import os
  import zipfile
  import stanza
  from stanza.models.classifiers.data import SentimentDatum
  import stanza.utils.default_paths
  from stanza.utils.datasets.sentiment.process_utils import write_dataset, write_list
label_desc: Use image node_id 10 for calling a global function with example usage: convert_tass2020(in_directory, out_directory, dataset_name) without return types