class_docstr: Gradient of generalized eigenvalues of a Hermitian positive definite
  eigensystem.
class_docstr_tok: ["Gradient","of","generalized","eigenvalues","of","a","Hermitian","positive","definite","eigensystem","."]
code: def infer_shape(self, node, shapes):
      return [shapes[0], shapes[1]]
  
imports: from __future__ import absolute_import, print_function, division
  import logging
  import warnings
  from six.moves import xrange
  import numpy
  from theano import tensor
  import theano.tensor
  from theano.tensor import as_tensor_variable
  from theano.gof import Op, Apply
label_desc: Use image node_id 4 for calling the EigvalshGrad obj's underlying member method code with example usage: obj.infer_shape(node, shapes) and returns: list