class_docstr: Dropout regularization.
class_docstr_tok: ["Dropout","regularization","."]
code: def forward_cpu(self, x):
      if (
          intel64.should_use_ideep(">=auto")
          and intel64.inputs_all_ready(x)
          and self.mask is None
      ):
          return self._forward_ideep(x)
  
      if self.mask is not None:
          y = x[0] * self.mask
      else:
          scale = x[0].dtype.type(1.0 / (1 - self.dropout_ratio))
          flag = numpy.random.rand(*x[0].shape) >= self.dropout_ratio
          self.mask = scale * flag
          y = x[0] * self.mask
      return (y,)
  
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 Dropout obj's underlying member method code with example usage: obj.forward_cpu(x) and returns: y, self