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