bar.draw(value=data.get_count()) t = time.time() - now acc, loss = net.get_record() loss_avg = np.array(loss).mean() loss_diff = loss_avg - loss_cache loss_cache = loss_avg print 'Acc: ', np.array(acc).mean() print 'Loss: ', loss_avg print 'Time: ', t f, b = net.get_profile() net.clear_record() bar_t = Bar(max_value=nt) bar_t.cursor.clear_lines(2) # Make some room bar_t.cursor.save() # Mark starting line for _ in xrange(data.batch_run_test()): net.input(data.next_batch_test()) net.forward() bar_t.cursor.restore() # Return cursor to start bar_t.draw(value=data.get_count_test()) acc, loss = net.get_record() print 'Val: ', np.array(acc).mean() print 'Loss: ', np.array(loss).mean() net.clear_record() lr *= gamma print lr, loss_diff print # Profile print 'Forward Time: ', sum(f) print f