code: def test_backwards_compatibility():
      # Tests that legacy level-based metadata keys are supported.
      metadata = {
          "SibSp": {
              "char_idx2str": [
                  "<EOS>",
                  "<SOS>",
                  "<PAD>",
                  "<UNK>",
                  "0",
                  "1",
                  "2",
                  "4",
                  "3",
                  "8",
                  "5",
              ],
              "char_max_sequence_length": 3,
              "char_pad_idx": 2,
              "char_pad_symbol": "<PAD>",
              "char_str2freq": {
                  "0": 608,
                  "1": 209,
                  "2": 28,
                  "3": 16,
                  "4": 18,
                  "5": 5,
                  "8": 7,
                  "<EOS>": 0,
                  "<PAD>": 0,
                  "<SOS>": 0,
                  "<UNK>": 0,
              },
              "char_str2idx": {
                  "0": 4,
                  "1": 5,
                  "2": 6,
                  "3": 8,
                  "4": 7,
                  "5": 10,
                  "8": 9,
                  "<EOS>": 0,
                  "<PAD>": 2,
                  "<SOS>": 1,
                  "<UNK>": 3,
              },
              "char_unk_symbol": "<UNK>",
              "char_vocab_size": 11,
              "preprocessing": {
                  "char_most_common": 70,
                  "char_sequence_length_limit": 1024,
                  "char_tokenizer": "characters",
                  "char_vocab_file": None,
                  "computed_fill_value": "<UNK>",
                  "fill_value": "<UNK>",
                  "lowercase": True,
                  "missing_value_strategy": "fill_with_const",
                  "padding": "right",
                  "padding_symbol": "<PAD>",
                  "pretrained_model_name_or_path": None,
                  "unknown_symbol": "<UNK>",
                  "word_most_common": 20000,
                  "word_sequence_length_limit": 256,
                  "word_tokenizer": "space_punct",
                  "word_vocab_file": None,
              },
              "word_idx2str": [
                  "<EOS>",
                  "<SOS>",
                  "<PAD>",
                  "<UNK>",
                  "0",
                  "1",
                  "2",
                  "4",
                  "3",
                  "8",
                  "5",
              ],
              "word_max_sequence_length": 3,
              "word_pad_idx": 2,
              "word_pad_symbol": "<PAD>",
              "word_str2freq": {
                  "0": 608,
                  "1": 209,
                  "2": 28,
                  "3": 16,
                  "4": 18,
                  "5": 5,
                  "8": 7,
                  "<EOS>": 0,
                  "<PAD>": 0,
                  "<SOS>": 0,
                  "<UNK>": 0,
              },
              "word_str2idx": {
                  "0": 4,
                  "1": 5,
                  "2": 6,
                  "3": 8,
                  "4": 7,
                  "5": 10,
                  "8": 9,
                  "<EOS>": 0,
                  "<PAD>": 2,
                  "<SOS>": 1,
                  "<UNK>": 3,
              },
              "word_unk_symbol": "<UNK>",
              "word_vocab_size": 11,
          }
      }
  
      column = pd.core.series.Series(["hello world", "hello world"])
  
      feature_data = text_feature.TextInputFeature.feature_data(
          column,
          metadata["SibSp"],
          metadata["SibSp"]["preprocessing"],
          LocalBackend(),
      )
  
      assert list(feature_data[0]) == [1, 3, 3]
      assert list(feature_data[1]) == [1, 3, 3]
  
file_path: ludwig/tests/ludwig/features/test_text_feature.py
imports: import pandas
  import torch
  from transformers import AutoTokenizer
  from ludwig.backend import LocalBackend
  from ludwig.constants import LOGITS, PREDICTIONS, PROBABILITIES
  from ludwig.features import text_feature
label_desc: Use image node_id 1 for calling a global function with example usage: test_backwards_compatibility() without return types