(self, state_action)
return self.normalize(state)
Evaluate the dynamics.
Evaluate the dynamics.
Evaluate the dynamics .
def build_evaluation(self, state_action):
        """Evaluate the dynamics."""
        state, _ = tf.split(state_action, [2, 1], axis=1)
        state = self.denormalize(state)
        inner_euler_steps = 10
        dt = self.dt / inner_euler_steps
        for _ in range(inner_euler_steps):
            state_derivative = self.ode(state)
            state = state + dt * state_derivative
        return self.normalize(state)
def build_evaluation ( self , state_action ) : state , _ = tf . split ( state_action , [ 2 , 1 ] , axis = 1 ) state = self . denormalize ( state ) inner_euler_steps = 10 dt = self . dt / inner_euler_steps for _ in range ( inner_euler_steps ) : state_derivative = self . ode ( state ) state = state + dt * state_derivative return self . normalize ( state )