code: def call(self, x, training, mask):
      attn_output, _ = self.mha(
          x, x, x, mask
      )  # (batch_size, input_seq_len, embedding_size)
      attn_output = self.dropout1(attn_output, training=training)
      out1 = self.layernorm1(
          x + attn_output
      )  # (batch_size, input_seq_len, embedding_size)
      ffn_output = self.ffn(
          out1
      )  # (batch_size, input_seq_len, embedding_size)
      ffn_output = self.dropout2(ffn_output, training=training)
      out2 = self.layernorm2(
          out1 + ffn_output
      )  # (batch_size, input_seq_len, embedding_size)
      return out2
  
imports: import numpy
  import tensorflow
label_desc: Use image node_id 2 for calling the EncoderLayer obj's underlying member method code with example usage: obj.call(x, training, mask) and returns: out2