#model print("Building model ...") sys.stdout.flush() model = Scorer() scores_pred = model(inp=im_pl, training=training_pl, zero_centered=ZERO_CENTER) # print(scores_pred.shape) # sys.exit(0) # losses print("Losses ...") sys.stdout.flush() loss = model.compute_loss(scores_pl, scores_pred) # sys.exit(0) # define trainer print("Train_op ...") sys.stdout.flush() train_op, global_step = model.train_op(loss, LR, beta1=BETA1, beta2=BETA2) # sys.exit(0) # define summaries print("Summaries ...") sys.stdout.flush() train_loss_summary = tf.summary.scalar("train_loss", loss) valid_loss_pl = tf.placeholder( dtype=tf.float32, shape=[]) # placeholder for mean validation loss