class_docstr: Fundamental way to create a sparse node.
  
  Parameters
  ----------
  dtype : numpy dtype string such as 'int64' or 'float64' (among others)
      Type of numbers in the matrix.
  format: str
      The sparse storage strategy.
  
  Returns
  -------
  An empty SparseVariable instance.
  
  Notes
  -----
  As far as I can tell, L{scipy.sparse} objects must be matrices, i.e.
  have dimension 2.
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code: def __hash__(self):
      return hash(self.dtype) ^ hash(self.format)
  
imports: from __future__ import absolute_import, print_function, division
  import numpy
  import theano
  from theano import gof
  from six import string_types
label_desc: Use image node_id 6 for calling the SparseType obj's underlying member method code with example usage: obj.__hash__() and returns: unknown