code: def forward(self, src, src_mask=None, pos_embed=None):
      output = src
      for layer in self.layers:
          output = layer(output, src_mask=src_mask, pos_embed=pos_embed)
  
      if self.norm is not None:
          output = self.norm(output)
  
      return output
  
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 2 for calling the TransformerEncoder obj's underlying member method code with example usage: obj.forward(src, src_mask, pos_embed) and returns: output