class_docstr: Parametric Rectified Linear Unit gradient function.
code: def check_type_forward(self, in_types):
      type_check._argname(in_types, ("x", "W", "gy"))
      x_type, W_type, gy_type = in_types
      type_check.expect(
          x_type.dtype.kind == "f",
          W_type.dtype == x_type.dtype,
          gy_type.dtype == x_type.dtype,
          x_type.ndim >= W_type.ndim + 1,
          x_type.shape[1 : 1 + type_check.eval(W_type.ndim)]
          == W_type.shape,
          gy_type.shape == x_type.shape,
      )
  
imports: import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 2 for calling the PReLUFunctionGrad obj's underlying member method code with example usage: obj.check_type_forward(in_types) without return types