我正在尝试在我的模型中实现嘈杂的网络。我在 GitHub 上找到了一个代码，它是NoisyDense Class的一个实现。我在我的模型中使用了这个类。这里的代码： -
class Agent:
def __init__(self, state_size, strategy="t-dqn", reset_every=1000, pretrained=False, model_name=None):
self.strategy = strategy
# agent config
self.state_size = state_size
self.action_size = 3
self.model_name = model_name
self.inventory = []
self.buffer = []
self.first_iter = True
self.nstep = 5
self.n_step_buffer = deque(maxlen = self.nstep)
self.cnt = count()
self.alpha = 0.6
self.model_name = model_name
self.gamma = 0.95 # affinity for long term reward
self.epsilon = 1.0
self.epsilon_min = 0.01
self.epsilon_decay = 0.995
self.learning_rate = 0.001
self.loss = huber_loss
self.custom_objects = {"huber_loss": huber_loss} # important for loading the model from memory
self.optimizer = Adam(lr=self.learning_rate)
if pretrained and self.model_name is not None:
self.model = self.load()
else:
self.model = self._model()
# strategy config
if self.strategy in ["t-dqn", "double-dqn"]:
self.n_iter = 1
self.reset_every = reset_every
# target network
self.target_model = clone_model(self.model)
self.target_model.set_weights(self.model.get_weights())
def _model(self):
model = Sequential()
model.add(Dense(units=128, activation="relu", input_dim=self.state_size))
model.add(Dense(units=256, activation="relu"))
model.add(Dense(units=256, activation="relu"))
model.add(NoisyDense(128, activation="relu"))
model.add(NoisyDense(self.action_size + 1, activation='linear'))
model.compile(loss=self.loss, optimizer=self.optimizer)
return model
但是遇到了一个错误，我似乎不知道如何解决它，也检查了 NoisyDense 的实现。我在 StackOverflow 上寻找了类似的问题，但没有得到任何适用于我的代码的解决方案。此外，当我不调用 NoisyDense 类而是使用 Dense 层时，相同的模型也有效。回溯中的 Train.py 文件调用了代理类，我猜没有什么比这更重要的了。使用的模型是 Keras 模型，它的版本是 2.3.1
Traceback (most recent call last):
File "train.py", line 85, in <module>
pretrained=pretrained, debug=debug)
File "train.py", line 52, in main
agent = Agent(window_size, strategy=strategy, pretrained=pretrained, model_name=model_name)
File "C:\Users\Desktop\agent.py", line 158, in __init__
self.target_model = clone_model(self.model)
File "D:\anaconda\lib\site-packages\keras\models.py", line 255, in clone_model
return _clone_sequential_model(model, input_tensors=input_tensors)
File "D:\anaconda\lib\site-packages\keras\models.py", line 207, in _clone_sequential_model
layers = [clone(layer) for layer in model.layers]
File "D:\anaconda\lib\site-packages\keras\models.py", line 207, in <listcomp>
layers = [clone(layer) for layer in model.layers]
File "D:\anaconda\lib\site-packages\keras\models.py", line 205, in clone
return layer.__class__.from_config(layer.get_config())
File "D:\anaconda\lib\site-packages\keras\engine\base_layer.py", line 1179, in from_config
return cls(**config)
TypeError: __init__() missing 1 required positional argument: 'units'