src/transformers/models/ctrl/modeling_tf_ctrl.py/TFEncoderLayer/call
class TFEncoderLayer:    def call(self, x, mask, layer_past, attention_mask, head_mask, use_cache, output_attentions, training=False):
        normed = self.layernorm1(x)
        attn_outputs = self.multi_head_attention(
            normed,
            normed,
            normed,
            mask,
            layer_past,
            attention_mask,
            head_mask,
            use_cache,
            output_attentions,
            training=training,
        )
        attn_output = attn_outputs[0]
        attn_output = self.dropout1(attn_output, training=training)
        out1 = x + attn_output

        out2 = self.layernorm2(out1)
        ffn_output = self.ffn(out2)
        ffn_output = self.dropout2(ffn_output, training=training)
        out2 = out1 + ffn_output

        outputs = (out2,) + attn_outputs[1:]
        return outputs