import tensorflow as tf

      # dimension. These Tensors are implicitly concatenated to
      # [params['batch_size']].
      global_step_t = tf.reshape(global_step, [1])
      total_loss_t = tf.reshape(total_loss, [1])
      total_rpn_loss_t = tf.reshape(total_rpn_loss, [1])
      rpn_score_loss_t = tf.reshape(rpn_score_loss, [1])
      rpn_box_loss_t = tf.reshape(rpn_box_loss, [1])
      total_fast_rcnn_loss_t = tf.reshape(total_fast_rcnn_loss, [1])
      fast_rcnn_class_loss_t = tf.reshape(fast_rcnn_class_loss, [1])
      fast_rcnn_box_loss_t = tf.reshape(fast_rcnn_box_loss, [1])
      mask_loss_t = tf.reshape(mask_loss, [1])
      learning_rate_t = tf.reshape(learning_rate, [1])
      host_call = (host_call_fn,
                   [global_step_t, total_loss_t, total_rpn_loss_t,
