code: def forward(self, query, key, value, sources_mask):
      sources = self.self_attention_layer(
          query, key, value, sources_mask
      )
      sources = self.dropout(sources)
      sources = self.pointwise_feedforward_layer(sources)
      return sources
  
imports: from collections import OrderedDict
  import os
  import numpy
  import torch
  from torch import nn
  from gluoncv.torch.utils.coot_utils import truncated_normal_fill
label_desc: Use image node_id 2 for calling the TransformerEncoderLayer obj's underlying member method code with example usage: obj.forward(query, key, value, sources_mask) and returns: sources