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
      self.embed_dims = encoder_layer.embed_dims
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from ppdet.core.workspace import register
  from ..layers import MultiHeadAttention, _convert_attention_mask
  from .utils import _get_clones
  from ..initializer import linear_init_, normal_, constant_, xavier_uniform_
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)