Error:DQN expects a model that has one dimension for each action, in this case (1, 2, 1, 0)

I am building an RL agent for which the model is defined:

def build_model(states, actions):
    azioni = list(actions)
    model = Sequential()
    model.add(Dense(4, activation='relu', input_shape=[len(azioni)]))
    model.add(Dense(4, activation='relu'))
return model

The action.space is:

self.action_space=gym.spaces.Tuple(tuple([gym.spaces.Discrete(3)]*4))

My action space consists of 4 actions for 4 agents, where agents is a list of 4 object agents.

Then define Agent:

def build_agent(model, actions):
    policy = BoltzmannQPolicy()
    memory = SequentialMemory(limit=50000, window_length=1)
    dqn = DQNAgent(model=model, memory=memory, policy=policy,
                   nb_actions=actions, nb_steps_warmup=10, target_model_update=1e-2)
return dqn

When I try to build the agent:

dqn = build_agent(model, actions)

I get this error:

---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

ipython-input-98-512746ffa1dc in module
11     return dqn
12 
--- 13 dqn = build_agent(model, actions)
14 dqn.compile(Adam(lr=1e-3), metrics=['mae'])
15 dqn.fit(env, nb_steps=50000, visualize=False, verbose=1)

ipython-input-98-512746ffa1dc in build_agent(model, actions)
8     memory = SequentialMemory(limit=50000, window_length=1)
9     dqn = DQNAgent(model=model, memory=memory, policy=policy,
--- 10                   nb_actions=actions, nb_steps_warmup=10,     target_model_update=1e-2)
11     return dqn
12 

~/PycharmProjects/pythonProject6/venv/lib/python3.6/site-packages/rl/agents/dqn.py   in __init__(self, model, policy, test_policy, enable_double_dqn, enable_dueling_network,  dueling_type, *args, **kwargs)
109             raise ValueError('Model {} has more than one output. DQN expects a model that has a single output.'.format(model))
110         if tuple(model.output.shape) != list((None, self.nb_actions)):
-- 111             raise ValueError('Model output {} has invalid shape. DQN expects a model that has one dimension for each action, in this case  {}.'.format(model.output, self.nb_actions))
112 
113         # Parameters.

ValueError: Model output Tensor(dense_16/Relu:0, shape=(?, 4), dtype=float32) has invalid shape. DQN expects a model that has one dimension for each action, in this case (1, 2, 1, 0).

I checked the value of model.output.shape and action:

print(model.output_shape)
#(None, 4)

print(actions)
#(1, 2, 1, 0)

I don't know how to adapt the action list to pass to my agents with the model.output_shape. Since my space_action is given by a list where space_action[0] is the action of agent[0], action[1] is the action of agent[1] etc.