src/transformers/models/t5/modeling_tf_t5.py/TFT5LayerCrossAttention/call
class TFT5LayerCrossAttention:    def call(
        self,
        hidden_states,
        key_value_states,
        attention_mask=None,
        position_bias=None,
        layer_head_mask=None,
        past_key_value=None,
        query_length=None,
        use_cache=False,
        output_attentions=False,
        training=False,
    ):
        normed_hidden_states = self.layer_norm(hidden_states)
        attention_output = self.EncDecAttention(
            normed_hidden_states,
            mask=attention_mask,
            key_value_states=key_value_states,
            position_bias=position_bias,
            layer_head_mask=layer_head_mask,
            past_key_value=past_key_value,
            query_length=query_length,
            use_cache=use_cache,
            output_attentions=output_attentions,
            training=training,
        )
        hidden_states = hidden_states + self.dropout(attention_output[0], training=training)
        outputs = (hidden_states,) + attention_output[1:]  # add attentions if we output them
        return outputs