class_docstr: Simple Tensorizer that splits a sentence on spaces and create tensors
  from the vocabulary index built on the training data.
docstr: Build vocabulary based on training corpus.
code: def initialize(self):
      """Build vocabulary based on training corpus."""
      vocab_builder = VocabBuilder()
  
      try:
          while True:
              row = yield
              words = self._tokenize(row)
              vocab_builder.add_all(words)
      except GeneratorExit:
          self.vocab = vocab_builder.make_vocab()
  
file_path: pytext/demo/examples/tensorizer.py
imports: from pytext.data.tensorizers import Tensorizer
  from pytext.data.utils import pad_and_tensorize, VocabBuilder
label_desc: Use image node_id 5 for calling the MyWordTensorizer obj's underlying member method code with example usage: obj.initialize() without return types