code: def clbn_self_folding_resblock(
      x,
      i,
      maps,
      kernel=(3, 3),
      pad=(1, 1),
      stride=(1, 1),
      name="convblock",
  ):
      h = x
      with nn.parameter_scope(name):
          h = PF.convolution(
              h,
              maps,
              kernel=kernel,
              pad=pad,
              stride=stride,
              channel_last=True,
              with_bias=False,
          )
          a, b = create_scale_bias(i, h.shape[3], axes=[3])
          h = a * h + b
      return F.relu(h + x)
  
imports: from __future__ import absolute_import
  import nnabla
  import nnabla.functions
  import nnabla.parametric_functions
  from .helper import create_scale_bias, create_conv_weight_bias, create_affine_weight_bias, get_channel_axes
label_desc: Use image node_id 29 for calling a global function with example usage: clbn_self_folding_resblock(x, i, maps, kernel, pad, stride, name) and returns: F