code: def vectorize(self, input_string: str) -> np.array:
      encoding = np.zeros(shape=len(self.data_vocab), dtype=np.float32)
      tokens = self.tokenizer.tokenize(text=input_string)
      for character in tokens:
          encoding[self.data_vocab.lookup_token(token=character)] = 1
  
      return encoding
  
imports: import numpy
  import pandas
  import torch
  from transfer_nlp.common.tokenizers import CharacterTokenizer
  from transfer_nlp.loaders.loaders import DatasetSplits, DataFrameDataset
  from transfer_nlp.loaders.vectorizers import Vectorizer
  from transfer_nlp.loaders.vocabulary import Vocabulary
  from transfer_nlp.plugins.config import register_plugin
  from transfer_nlp.plugins.helpers import ObjectHyperParams
label_desc: Use image node_id 2 for calling the TestVectorizer obj's underlying member method code with example usage: obj.vectorize(input_string) and returns: encoding