def start(self,x=None):
		if x is None:
			x=Tensor.context


		obs_array = x.content.data
		#print "sum",obs_array.sum()

		# Initialize State
		self.state = np.zeros((self.func.hist_size, self.image_feature_dim), dtype=np.uint8)
		self.state[0] = obs_array
		state_ = np.asanyarray(self.state.reshape(1, self.func.hist_size, self.image_feature_dim), dtype=np.float32)
		if 0 >= Deel.gpu:
			state_ = cuda.to_gpu(state_)

		# Generate an Action e-greedy
		action, Q_now = self.func.e_greedy(state_, self.epsilon)
		returnAction = action

		# Update for next step
		self.lastAction = copy.deepcopy(returnAction)
		self.last_state = self.state.copy()
		self.last_observation = obs_array

		return returnAction
dataset/ETHPy150Open uei/deel/deel/network/dqn.py/DQN.start/swapped operands of `>=`