code: def __init__(self, encoder_layer, num_layers, norm=None):
      super(TransformerEncoder, self).__init__()
      self.layers = _get_clones(encoder_layer, num_layers)
      self.num_layers = num_layers
      self.norm = norm
  
imports: import math
  import copy
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register, serializable
  from ppdet.modeling.layers import DropBlock, MultiHeadAttention
  from ppdet.modeling.ops import get_act_fn
  from ..backbones.cspresnet import ConvBNLayer, BasicBlock
  from ..shape_spec import ShapeSpec
  from ..initializer import linear_init_
label_desc: Use image node_id 1 to create a new TransformerEncoder object from inherited base classes: nn with example: obj = TransformerEncoder(encoder_layer, num_layers, norm)