class_docstr: Multi-head attention over encoder output with Fixup initialization.
class_docstr_tok: ["Multi-head","attention","over","encoder","output","with","Fixup","initialization","."]
docstr: Call the layer.
docstr_tok: ["Call","the","layer","."]
code: def call(self, context, x, losses=None):
      """Call the layer."""
      return transformer_layers.enc_dec_attention(
          self, self._get_memory_antecedent(context), context, x, losses
      )
  
imports: import math
  import gin
  import mesh_tensorflow
  from mesh_tensorflow.transformer import attention
  from mesh_tensorflow.transformer import transformer
  from mesh_tensorflow.transformer import transformer_layers
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the EncDecAttentionFixup obj's underlying member method code with example usage: obj.call(context, x, losses) and returns: transformer_layers