src/transformers/models/swin/modeling_tf_swin.py/AdaptiveAveragePooling1D/compute_output_shape
class AdaptiveAveragePooling1D:    def compute_output_shape(self, input_shape: Iterable[int]) -> tf.TensorShape:
        input_shape = tf.TensorShape(input_shape).as_list()
        if self.data_format == "channels_last":
            shape = tf.TensorShape([input_shape[0], self.output_size[0], input_shape[2]])
        else:
            shape = tf.TensorShape([input_shape[0], input_shape[1], self.output_size[0]])
        return shape