class_docstr: Tangent space of M for discrete distributions.
  
  In this special case the tangent space is 0-dimensional, and the
  basis is represented by a 0x0 matrix, which gives 0 as the density
  correction term.
class_docstr_tok: ["Tangent","space","of","M","for","discrete","distributions",".","In","this","special","case","the","tangent","space","is","0-dimensional",",","and","the","basis","is","represented","by","a","0x0","matrix",",","which","gives","0","as","the","density","correction","term","."]
code: def _transform_general(self, x, f, **kwargs):
      del x, f
      return 0, ZeroSpace()
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 1 for calling the ZeroSpace obj's underlying member method code with example usage: obj._transform_general(x, f) and returns: int,  ZeroSpace