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 forward(self, inputs):
      return (
          cuda.get_cudnn_dropout_states().backward(
              None, inputs[0], self.dropout_ratio, self.states
          ),
      )
  
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 2 for calling the DropoutGradCuDNN obj's underlying member method code with example usage: obj.forward(inputs) and returns: cuda