class_docstr: Efficient and numerically stable implementation of a dot product followed
  by a modulo operation. This performs the same function as matVecModM.
  
  We do this 2 times on 2 triple inputs and concatenating the output.
code: def c_code_cache_version(self):
      return (6,)
  
imports: from __future__ import absolute_import, print_function, division
  import warnings
  import numpy
  from six import integer_types, string_types
  from six.moves import xrange
  import theano
  from theano import Op, Apply, shared, config, Variable
  from theano import gradient, function
  from theano.gradient import undefined_grad
  from theano import tensor
  from theano.tensor import TensorType, as_tensor_variable, get_vector_length, cast, opt, scal
  from theano.compile import optdb
  from theano.gof import local_optimizer, ParamsType
  from theano.scalar import bool, int32
  from .None import multinomial
label_desc: Use image node_id 3 for calling the DotModulo obj's underlying member method code with example usage: obj.c_code_cache_version() and returns: int