x_batch = xp.asarray(x_test[i: i + batch_size])
y_batch = xp.asarray(y_test[i: i + batch_size])
acc = forward(x_batch, y_batch, train=False)
sum_acc += float(acc.data) * len(y_batch)
epoch_acc = sum_acc / N_test
log.info("test accuracy: {0}".format(epoch_acc))
fp_acc.write("{0}\t{1}\n".format(epoch, epoch_acc))
fp_acc.flush()
# モデルパラメータの途中保存
if check_interval > 0 and (epoch % check_interval) == 0:
check_file = "result/{0:0>3}_".format(epoch) + args.model
log.info("Checkpoint : {0}".format(check_file))
param = model.to_cpu().parameters
np.save(check_file, param)
end_time = time.clock()
log.info("Trainging time: {0} [s]".format(end_time - start_time))
fp_acc.close()
fp_loss.close()
# モデルのパラメータを保存
if n_epoch > 0:
log.info("Save model parameters : {0}".format(param_file))
param = model.to_cpu().parameters
np.save(param_file, param)
if plot_model == 1:
# 重みを表示
plot_mlp_weight(model, "l1", shape=(28, 28))
plot_mlp_weight(model, "l2", shape=(16, 16))
