class_docstr: Simple Tensorizer that splits a sentence on spaces and create tensors
  from the vocabulary index built on the training data.
code: def tensorize(self, batch):
      tokens, seq_lens = zip(*batch)
      return (
          pad_and_tensorize(tokens, self.vocab.get_pad_index()),
          pad_and_tensorize(seq_lens),
      )
  
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 7 for calling the MyWordTensorizer obj's underlying member method code with example usage: obj.tensorize(batch) and returns: pad_and_tensorize,  pad_and_tensorize