code: def norm_layer(norm_type, nc):
      # normalization layer 1d
      norm = norm_type.lower()
      if norm == "batch":
          layer = batch_norm_1d(nc)
      elif norm == "layer":
          layer = nn.LayerNorm(nc)
      else:
          raise NotImplementedError(
              "normalization layer [%s] is not found" % norm
          )
      return layer
  
imports: import numpy
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import paddle.distributed
  import pgl
  import pgl.nn
  from pgl.nn import functional
  from pgl.utils.logger import log
  import models.mol_encoder
label_desc: Use image node_id 3 for calling a global function with example usage: norm_layer(norm_type, nc) and returns: layer