我想使用Keras来调优模型的超参数,使用下面的代码,这些代码首先创建类来进行优化,如下面的所示
model = keras.Sequential()
model.add(layers.Conv2D(filter=hp.Int('conv_1_filter',min_value=32,max_value=128,step=16),
kernel_size=hp.Choice('conv_1_kernel',values = [3,5]),
activation='relu',
input_shape=(28,28,1)
))
model.add(layers.Conv2D(filter=hp.Int('conv_2_filter',min_value=32,max_value=128,step=16),
kernel_size=hp.Choice('conv_2_kernel',values = [3,5]),
activation='relu'))
model.add(layers.Flatten())
model.add(layers.Dense(
units=hp.Int('dense_1_units',min_value=32,max_value=128, step=16),
activation='relu'
))
model.add(layers.Dense(10,activation='softmax'))
model.compile(
optimizer=keras.optimizers.Adam(
hp.Choice('learning_rate',
values=[1e-2, 1e-3])),
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
return model
from kerastuner import RandomSearch
from tensorflow.keras import layers
from kerastuner.engine.hyperparameters import HyperParameters
tuner_search=RandomSearch(build_model,
objective='val_accuracy',
max_trials=5,
executions_per_trial=3,
directory='output',project_name='MNIST') **我运行这个类,但是当我尝试使用任意搜索、超带等调谐器时,我得到了以下错误**
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
model = self.hypermodel.build(hp)
File "<ipython-input-37-8db271052e01>", line 6, in build_model
input_shape=(28,28,1)
TypeError: __init__() missing 1 required positional argument: 'filters'
[Warning] Invalid model 0/5
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
model = self.hypermodel.build(hp)
File "<ipython-input-37-8db271052e01>", line 6, in build_model
input_shape=(28,28,1)
TypeError: __init__() missing 1 required positional argument: 'filters'
[Warning] Invalid model 1/5
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
model = self.hypermodel.build(hp)
File "<ipython-input-37-8db271052e01>", line 6, in build_model
input_shape=(28,28,1)
TypeError: __init__() missing 1 required positional argument: 'filters'
[Warning] Invalid model 2/5
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
model = self.hypermodel.build(hp)
File "<ipython-input-37-8db271052e01>", line 6, in build_model
input_shape=(28,28,1)
TypeError: __init__() missing 1 required positional argument: 'filters'
[Warning] Invalid model 3/5
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
model = self.hypermodel.build(hp)
File "<ipython-input-37-8db271052e01>", line 6, in build_model
input_shape=(28,28,1)
TypeError: __init__() missing 1 required positional argument: 'filters'
[Warning] Invalid model 4/5
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
model = self.hypermodel.build(hp)
File "<ipython-input-37-8db271052e01>", line 6, in build_model
input_shape=(28,28,1)
TypeError: __init__() missing 1 required positional argument: 'filters'
[Warning] Invalid model 5/5
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/usr/local/lib/python3.6/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:
8 frames
TypeError: __init__() missing 1 required positional argument: 'filters'
During handling of the above exception, another exception occurred:
RuntimeError Traceback (most recent call last)
/usr/local/lib/python3.6/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.**有人能帮我解决这个问题吗?**
发布于 2020-07-16 18:00:38
所以您已经完成了大多数正确的事情,您只是在您的代码中输入了错误。
您必须使用filters,也可以使用filter。
为了更清楚地说明,它应该以以下方式进行。
model.add(layers.Conv2D(filters=hp.Int('conv_1_filter',min_value=32,max_value=128,step=16),
kernel_size=hp.Choice('conv_1_kernel',values = [3,5]),
activation='relu',
input_shape=(28,28,1)
))改变这一点应该能解决这个问题。我希望你的问题能解决。
https://stackoverflow.com/questions/62928797
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