8dcbf002d0058939802920c11f74791708838791,ml/rl/training/ddpg_predictor.py,CriticNet,forward,#CriticNet#Any#Any#,98

Before Change

        :param state state as list of state features
        :param state action as list of action features
        
        x = torch.cat(
            (Variable(torch.from_numpy(state).float()),
            Variable(torch.from_numpy(action).float())), dim=0
        )
        for i, activation in enumerate(self.activations):
            activation_func = getattr(F, activation)
            fc_func = getattr(self, self.layer_names[i])
            x = fc_func(x) if activation == "linear" else activation_func(fc_func(x))

After Change

        :param state state as list of state features
        :param state action as list of action features
        
        x = torch.cat((state, action), dim=1)
        for i, activation in enumerate(self.activations):
            activation_func = getattr(F, activation)
            fc_func = getattr(self, self.layer_names[i])
            x = fc_func(x) if activation == "linear" else activation_func(fc_func(x))

Instances