class_docstr: Computes the gradient of the Dropout function with cuDNN support.
class_docstr_tok: ["Computes","the","gradient","of","the","Dropout","function","with","cuDNN","support","."]
code: def backward(self, indexes, gy):
      return DropoutGradCuDNN(self.states, self.dropout_ratio).apply(gy)
  
imports: import numpy
  import chainer
  from chainer.backends import cuda
  from chainer.backends import intel64
  from chainer import configuration
  from chainer import function_node
  from chainer.utils import argument
  from chainer.utils import type_check
label_desc: Use image node_id 3 for calling the DropoutGradCuDNN obj's underlying member method code with example usage: obj.backward(indexes, gy) and returns: DropoutGradCuDNN