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 conv2d_triple(self, a, b, strides, padding):
      with tf.device(self.producer.device_name):
          with tf.name_scope("triple"):
              ab = a.conv2d(b, strides, padding)
              ab0, ab1 = self._share(ab)
  
      return self._build_queues(ab0, ab1)
  
imports: import abc
  import logging
  import random
  import tensorflow
  from ...config import get_config
label_desc: Use image node_id 6 for calling the BaseTripleSource obj's underlying member method code with example usage: obj.conv2d_triple(a, b, strides, padding) and returns: self