class_docstr: Computes the gradient of the Dropout function.
class_docstr_tok: ["Computes","the","gradient","of","the","Dropout","function","."]
code: def _forward_ideep(self, inputs):
      return (
          intel64.ideep.dropout.Backward(
              intel64.ideep.array(self.mask),
              intel64.ideep.array(inputs[0]),
          ),
      )
  
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 DropoutGrad obj's underlying member method code with example usage: obj._forward_ideep(inputs) and returns: intel64