keras LSTM 上的超频带调优：目标问题

Question

我有一个 keras LSTM 模型（回归器）：

def model_builder(hp):
  model = Sequential()
 
  hp_units = hp.Int('units', min_value=32, max_value=512, step=32)

  model.add(LSTM(units=hp_units, input_shape=(trainX.shape[1], trainX.shape[2])))
  model.add(Dropout(0.2))
  model.add(Dense(1))

  hp_learning_rate = hp.Choice('learning_rate', values=[1e-2, 1e-3, 1e-4])

  model.compile(loss='mean_squared_error', optimizer='adam')

  return model

我按如下方式设置调谐器：

tuner = kt.Hyperband(model_builder,
                     objective='val_mean_squared_error',
                     max_epochs=10,
                     factor=3)

跑步时

    tuner.search(X_train, y_train, epochs=50, validation_split=0.2, callbacks=[stop_early])

我收到此错误：

Search: Running Trial #3

Value             |Best Value So Far |Hyperparameter
64                |352               |units
0.0001            |0.01              |learning_rate
2                 |2                 |tuner/epochs
0                 |0                 |tuner/initial_epoch
2                 |2                 |tuner/bracket
0                 |0                 |tuner/round

Epoch 1/2
104/104 ━━━━━━━━━━━━━━━━━━━━ 6s 29ms/step - loss: 0.0641 - val_loss: 0.0042
Epoch 2/2
104/104 ━━━━━━━━━━━━━━━━━━━━ 2s 24ms/step - loss: 0.0074 - val_loss: 0.0043
Traceback (most recent call last):
  File "/home/tillys/python/usr/local/lib/python3.10/site-packages/keras_tuner/src/engine/base_tuner.py", line 274, in _try_run_and_update_trial
    self._run_and_update_trial(trial, *fit_args, **fit_kwargs)
  File "/home/tillys/python/usr/local/lib/python3.10/site-packages/keras_tuner/src/engine/base_tuner.py", line 265, in _run_and_update_trial
    tuner_utils.convert_to_metrics_dict(
  File "/home/tillys/python/usr/local/lib/python3.10/site-packages/keras_tuner/src/engine/tuner_utils.py", line 132, in convert_to_metrics_dict
    [convert_to_metrics_dict(elem, objective) for elem in results]
  File "/home/tillys/python/usr/local/lib/python3.10/site-packages/keras_tuner/src/engine/tuner_utils.py", line 132, in <listcomp>
    [convert_to_metrics_dict(elem, objective) for elem in results]
  File "/home/tillys/python/usr/local/lib/python3.10/site-packages/keras_tuner/src/engine/tuner_utils.py", line 145, in convert_to_metrics_dict
    best_value, _ = _get_best_value_and_best_epoch_from_history(
  File "/home/tillys/python/usr/local/lib/python3.10/site-packages/keras_tuner/src/engine/tuner_utils.py", line 116, in _get_best_value_and_best_epoch_from_history
    objective_value = objective.get_value(metrics)
  File "/home/tillys/python/usr/local/lib/python3.10/site-packages/keras_tuner/src/engine/objective.py", line 59, in get_value
    return logs[self.name]
KeyError: 'val_mean_squared_error'

该模型在没有 keras hyperband 的情况下运行良好。 我对这个 KeyError 有点困惑：

'val_mean_squared_error'

任何想法将不胜感激。

Answer 1

在

Hyperband

中，目标函数评估定义在

metrics

。我在构建时添加了

compile function

指标 模型，进行这些更改后，代码将按预期工作。请 请参阅此

gist

进行实施。