AttributeError: 'function' object has no attribute 'predict'. Keras

Question

I am working on an RL problem and I created a class to initialize the model and other parameters. The code is as follows:

class Agent:
    def __init__(self, state_size, is_eval=False, model_name=""):
        self.state_size = state_size
        self.action_size = 20 # measurement, CNOT, bit-flip
        self.memory = deque(maxlen=1000)
        self.inventory = []
        self.model_name = model_name
        self.is_eval = is_eval
        self.done = False

        self.gamma = 0.95
        self.epsilon = 1.0
        self.epsilon_min = 0.01
        self.epsilon_decay = 0.995


    def model(self):
        model = Sequential()
        model.add(Dense(units=16, input_dim=self.state_size, activation="relu"))
        model.add(Dense(units=32, activation="relu"))
        model.add(Dense(units=8, activation="relu"))
        model.add(Dense(self.action_size, activation="softmax"))
        model.compile(loss="categorical_crossentropy", optimizer=Adam(lr=0.003))
        return model

    def act(self, state):
        options = self.model.predict(state)
        return np.argmax(options[0]), options

I want to run it for only one iteration, hence I create an object and I pass a vector of length 16 like this:

agent = Agent(density.flatten().shape)
state = density.flatten()
action, probs = agent.act(state)

However, I get the following error:

AttributeError                       Traceback (most recent call last) <ipython-input-14-4f0ff0c40f49> in <module>
----> 1 action, probs = agent.act(state)

<ipython-input-10-562aaf040521> in act(self, state)
     39 #             return random.randrange(self.action_size)
     40 #         model = self.model()
---> 41         options = self.model.predict(state)
     42         return np.argmax(options[0]), options
     43 

AttributeError: 'function' object has no attribute 'predict'

What's the issue? I checked some other people's codes as well, like this and I think mine is also very similar.

Let me know.

EDIT:

I changed the argument in Dense from input_dim to input_shape and self.model.predict(state) to self.model().predict(state).

Now when I run the NN for one input data of shape (16,1), I get the following error:

ValueError: Error when checking input: expected dense_1_input to have 3 dimensions, but got array with shape (16, 1)

And when I run it with shape (1,16), I get the following error:

ValueError: Error when checking input: expected dense_1_input to have 3 dimensions, but got array with shape (1, 16)

What should I do in this case?

Answer 1

in last code block,

def act(self, state):
        options = self.model.predict(state)
        return np.argmax(options[0]), options

self.model is a function which is returning a model, it should be self.model().predict(state)