code: def check_forward(self, x_data, W_data, b_data):
      # Check only data type, y is tested by SimplifiedDropconnect link test.
      x = chainer.Variable(x_data)
      W = chainer.Variable(W_data)
      if b_data is None:
          y = functions.simplified_dropconnect(
              x,
              W,
              None,
              self.ratio,
              self.train,
              None,
              self.use_batchwise_mask,
          )
      else:
          b = chainer.Variable(b_data)
          y = functions.simplified_dropconnect(
              x,
              W,
              b,
              self.ratio,
              self.train,
              None,
              self.use_batchwise_mask,
          )
      self.assertEqual(y.data.dtype, self.x_dtype)
      mask = y.creator.mask
      mask = cuda.to_cpu(mask)
      if self.use_batchwise_mask:
          self.assertEqual(mask.shape, (x.shape[0],) + W.shape)
      else:
          self.assertEqual(mask.shape, W.shape)
  
imports: import unittest
  import numpy
  import chainer
  from chainer import backend
  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 2 for calling the TestSimplifiedDropconnect obj's underlying member method code with example usage: obj.check_forward(x_data, W_data, b_data) without return types