code: def check_type_forward(self, in_types):
      type_check.expect(in_types.size() == 3)
      x_type, gamma_type, beta_type = in_types
      M = type_check.eval(gamma_type.ndim)
      type_check.expect(
          x_type.dtype.kind == "f",
          x_type.ndim >= gamma_type.ndim + 1,
          x_type.shape[1 : 1 + M] == gamma_type.shape,
          # TODO(tkerola): Check shape
          gamma_type.dtype.kind == "f",
          gamma_type.dtype == beta_type.dtype,
          gamma_type.shape == beta_type.shape,
      )
  
imports: import warnings
  import numpy
  from chainer import backend
  from chainer.backends import cuda
  from chainer import configuration
  from chainer import function
  from chainer.functions.normalization import batch_normalization
  from chainer.utils import type_check
label_desc: Use image node_id 5 for calling the BatchRenormalizationFunction obj's underlying member method code with example usage: obj.check_type_forward(in_types) without return types