我试图使用贝叶斯优化来优化LSTM的超参数。但是当我运行代码时，收到了错误消息 TypeError: only integer scalar arrays can be converted to a scalar index。我找到的一个解决方案是将训练数据和验证数据转换为数组，但在我的代码中它们已经是数组而不是列表。或者将它们转换为元组，但我不知道如何操作
X_train 形状: (946, 60, 1)
y_train 形状: (946,)
X_val 形状: (192, 60, 1)
y_val 形状: (192,)
def build(hp): activation = hp.Choice('activation', [ 'relu', 'tanh', 'linear', 'selu', 'elu' ]) num_rnn_layers = hp.Int( 'num_rnn_layers', min_value=0, max_value=12, default=3) recurrent_dropout = hp.Float( 'recurrent_dropout', min_value=0.0, max_value=0.99, default=0.2) num_units = hp.Int( 'num_units', min_value=0, max_value=64, default=32) model = Sequential() model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train[1], 1))) model.add(Dense(1)) model.compile(loss='mse', metrics=['mse'], optimizer=keras.optimizers.Adam( hp.Choice('learning_rate', values=[1e-2, 1e-3, 1e-4]))) model.compile( optimizer=keras.optimizers.Adam( hp.Float( 'learning_rate', min_value=1e-10, max_value=1e-2, sampling='LOG', default=1e-6 ), ), loss=tf.losses.MeanSquaredError(), metrics=[tf.metrics.MeanAbsoluteError()] ) return modelbayesian_opt_tuner = BayesianOptimization( build, objective='mse', max_trials=3, executions_per_trial=1, directory=os.path.normpath('C:/keras_tuning'), project_name='kerastuner_bayesian_poc', overwrite=True)n_epochs=100bayesian_opt_tuner.search(X_train, y_train,epochs=n_epochs, validation_data=(X_val, y_val), validation_split=0.2,verbose=1)bayes_opt_model_best_model = bayesian_opt_tuner.get_best_models(num_models=1)model = bayes_opt_model_best_model[0]错误日志:
Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build model = self.hypermodel.build(hp) File "<ipython-input-80-00452994e0d6>", line 33, in build model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train[1], 1))) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/training/tracking/base.py", line 517, in _method_wrapper result = method(self, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/sequential.py", line 204, in add batch_shape=batch_shape, dtype=dtype, name=layer.name + '_input') File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 309, in Input input_layer = InputLayer(**input_layer_config) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 160, in __init__ ragged=ragged) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/backend.py", line 1247, in placeholder shape=shape, dtype=dtype, name=name) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_spec.py", line 51, in __init__ self._shape = tensor_shape.TensorShape(shape) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in __init__ self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in <listcomp> self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 201, in __init__ self._value = int(value.__index__())TypeError: only integer scalar arrays can be converted to a scalar index[Warning] Invalid model 0/5Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build model = self.hypermodel.build(hp) File "<ipython-input-80-00452994e0d6>", line 33, in build model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train[1], 1))) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/training/tracking/base.py", line 517, in _method_wrapper result = method(self, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/sequential.py", line 204, in add batch_shape=batch_shape, dtype=dtype, name=layer.name + '_input') File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 309, in Input input_layer = InputLayer(**input_layer_config) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 160, in __init__ ragged=ragged) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/backend.py", line 1247, in placeholder shape=shape, dtype=dtype, name=name) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_spec.py", line 51, in __init__ self._shape = tensor_shape.TensorShape(shape) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in __init__ self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in <listcomp> self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 201, in __init__ self._value = int(value.__index__())TypeError: only integer scalar arrays can be converted to a scalar index[Warning] Invalid model 1/5Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build model = self.hypermodel.build(hp) File "<ipython-input-80-00452994e0d6>", line 33, in build model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train[1], 1))) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/training/tracking/base.py", line 517, in _method_wrapper result = method(self, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/sequential.py", line 204, in add batch_shape=batch_shape, dtype=dtype, name=layer.name + '_input') File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 309, in Input input_layer = InputLayer(**input_layer_config) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 160, in __init__ ragged=ragged) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/backend.py", line 1247, in placeholder shape=shape, dtype=dtype, name=name) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_spec.py", line 51, in __init__ self._shape = tensor_shape.TensorShape(shape) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in __init__ self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in <listcomp> self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 201, in __init__ self._value = int(value.__index__())TypeError: only integer scalar arrays can be converted to a scalar index[Warning] Invalid model 2/5Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build model = self.hypermodel.build(hp) File "<ipython-input-80-00452994e0d6>", line 33, in build model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train[1], 1))) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/training/tracking/base.py", line 517, in _method_wrapper result = method(self, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/sequential.py", line 204, in add batch_shape=batch_shape, dtype=dtype, name=layer.name + '_input') File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 309, in Input input_layer = InputLayer(**input_layer_config) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 160, in __init__ ragged=ragged) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/backend.py", line 1247, in placeholder shape=shape, dtype=dtype, name=name) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_spec.py", line 51, in __init__ self._shape = tensor_shape.TensorShape(shape) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in __init__ self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in <listcomp> self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 201, in __init__ self._value = int(value.__index__())TypeError: only integer scalar arrays can be converted to a scalar index[Warning] Invalid model 3/5Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build model = self.hypermodel.build(hp) File "<ipython-input-80-00452994e0d6>", line 33, in build model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train[1], 1))) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/training/tracking/base.py", line 517, in _method_wrapper result = method(self, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/sequential.py", line 204, in add batch_shape=batch_shape, dtype=dtype, name=layer.name + '_input') File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 309, in Input input_layer = InputLayer(**input_layer_config) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 160, in __init__ ragged=ragged) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/backend.py", line 1247, in placeholder shape=shape, dtype=dtype, name=name) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_spec.py", line 51, in __init__ self._shape = tensor_shape.TensorShape(shape) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in __init__ self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in <listcomp> self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 201, in __init__ self._value = int(value.__index__())TypeError: only integer scalar arrays can be converted to a scalar index[Warning] Invalid model 4/5Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build model = self.hypermodel.build(hp) File "<ipython-input-80-00452994e0d6>", line 33, in build model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train[1], 1))) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/training/tracking/base.py", line 517, in _method_wrapper result = method(self, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/sequential.py", line 204, in add batch_shape=batch_shape, dtype=dtype, name=layer.name + '_input') File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 309, in Input input_layer = InputLayer(**input_layer_config) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/input_layer.py", line 160, in __init__ ragged=ragged) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/backend.py", line 1247, in placeholder shape=shape, dtype=dtype, name=name) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_spec.py", line 51, in __init__ self._shape = tensor_shape.TensorShape(shape) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in __init__ self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 758, in <listcomp> self._dims = [Dimension(d) for d in dims] File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 201, in __init__ self._value = int(value.__index__())TypeError: only integer scalar arrays can be converted to a scalar index[Warning] Invalid model 5/5---------------------------------------------------------------------------TypeError Traceback (most recent call last)/usr/local/lib/python3.7/dist-packages/kerastuner/engine/hypermodel.py in build(self, hp) 104 with maybe_distribute(self.distribution_strategy):--> 105 model = self.hypermodel.build(hp) 106 except:17 framesTypeError: only integer scalar arrays can be converted to a scalar indexDuring handling of the above exception, another exception occurred:RuntimeError Traceback (most recent call last)/usr/local/lib/python3.7/dist-packages/kerastuner/engine/hypermodel.py in build(self, hp) 113 if i == self._max_fail_streak: 114 raise RuntimeError(--> 115 'Too many failed attempts to build model.') 116 continue 117 RuntimeError: Too many failed attempts to build model.回答：
您的代码应如下所示:
def build(hp): activation = hp.Choice('activation', [ 'relu', 'tanh', 'linear', 'selu', 'elu' ]) num_rnn_layers = hp.Int( 'num_rnn_layers', min_value=0, max_value=12, default=3) recurrent_dropout = hp.Float( 'recurrent_dropout', min_value=0.0, max_value=0.99, default=0.2) num_units = hp.Int( 'num_units', min_value=0, max_value=64, default=32) model = Sequential() model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train.shape[1], 1))) model.add(Dense(1)) model.compile(loss='mse', metrics=['mse'], optimizer=keras.optimizers.Adam( hp.Choice('learning_rate', values=[1e-2, 1e-3, 1e-4]))) model.compile( optimizer=keras.optimizers.Adam( hp.Float( 'learning_rate', min_value=1e-10, max_value=1e-2, sampling='LOG', default=1e-6 ), ), loss=tf.losses.MeanSquaredError(), metrics=[tf.metrics.MeanAbsoluteError()] ) return modelbayesian_opt_tuner = BayesianOptimization( build, objective='mse', max_trials=3, executions_per_trial=1, directory=os.path.normpath('C:/keras_tuning'), project_name='kerastuner_bayesian_poc', overwrite=True)n_epochs=100bayesian_opt_tuner.search(X_train, y_train,epochs=n_epochs, validation_data=(X_val, y_val), validation_split=0.2,verbose=1)bayes_opt_model_best_model = bayesian_opt_tuner.get_best_models(num_models=1)model = bayes_opt_model_best_model[0]我认为导致问题的这一行:
model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train[1], 1)))将其更改为:
model.add(LSTM(units=num_units, activation=activation, recurrent_dropout = recurrent_dropout,input_shape=(X_train.shape[1], 1)))