code: def check_backward(self, inputs, grad_outputs, backend_config):
      if backend_config.use_cuda:
          inputs = cuda.to_gpu(inputs)
          grad_outputs = cuda.to_gpu(grad_outputs)
  
      # Instantiate the function class directly in order to reuse the mask,
      # because f will be called repeatedly.
      dropout = functions.noise.dropout.Dropout(self.ratio)
  
      def f(*inputs):
          return dropout.apply(inputs)
  
      with backend_config:
          gradient_check.check_backward(
              f, inputs, grad_outputs, **self.check_backward_options
          )
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import functions
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
label_desc: Use image node_id 5 for calling the TestDropout obj's underlying member method code with example usage: obj.check_backward(inputs, grad_outputs, backend_config) and returns: dropout