class_docstr: Takes a batch of tokens and returns the masks of corresponding length
code: def __call__(tokens_batch, **kwargs):
      batch_size = len(tokens_batch)
      max_len = max(len(utt) for utt in tokens_batch)
      mask = np.zeros([batch_size, max_len], dtype=np.float32)
      for n, utterance in enumerate(tokens_batch):
          mask[n, : len(utterance)] = 1
  
      return mask
  
imports: import numpy
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.models.component import Component
label_desc: Use image node_id 2 for calling the Mask obj's underlying member method code with example usage: obj.__call__(tokens_batch) and returns: mask