src/transformers/models/cvt/modeling_tf_cvt.py/TFCvtLayer/call
class TFCvtLayer:    def call(self, hidden_state: tf.Tensor, height: int, width: int, training: bool = False) -> tf.Tensor:
        # in Cvt, layernorm is applied before self-attention
        attention_output = self.attention(self.layernorm_before(hidden_state), height, width, training=training)
        attention_output = self.drop_path(attention_output, training=training)

        # first residual connection
        hidden_state = attention_output + hidden_state

        # in Cvt, layernorm is also applied after self-attention
        layer_output = self.layernorm_after(hidden_state)
        layer_output = self.intermediate(layer_output)

        # second residual connection is done here
        layer_output = self.dense_output(layer_output, hidden_state)
        layer_output = self.drop_path(layer_output, training=training)
        return layer_output