class_docstr: Partial triple source adding graph nodes for constructing and keeping track
  of triples and their use. Subclasses must implement `_build_queues`.
class_docstr_tok: ["Partial","triple","source","adding","graph","nodes","for","constructing","and","keeping","track","of","triples","and","their","use",".","Subclasses","must","implement","`","_build_queues","`","."]
code: def mask(self, backing_dtype, shape):
      with tf.name_scope("triple-generation"):
          with tf.device(self.producer.device_name):
              a0 = backing_dtype.sample_uniform(shape)
              a1 = backing_dtype.sample_uniform(shape)
              a = a0 + a1
  
      d0, d1 = self._build_queues(a0, a1)
      return a, d0, d1
  
imports: import abc
  import logging
  import random
  import tensorflow
  from ...config import get_config
label_desc: Use image node_id 2 for calling the BaseTripleSource obj's underlying member method code with example usage: obj.mask(backing_dtype, shape) and returns: a,  d0,  d1