INNER CODE UNIT · Python

_build_nn_model

rasbt/machine-learning-book · ch19/cartpole/main.py:52

    def _build_nn_model(self):
        self.model = nn.Sequential(nn.Linear(self.state_size, 256),
                                   nn.ReLU(),
                                   nn.Linear(256, 128),
                                   nn.ReLU(),
                                   nn.Linear(128, 64),
                                   nn.ReLU(),
                                   nn.Linear(64, self.action_size))

        self.loss_fn = nn.MSELoss()
        self.optimizer = torch.optim.Adam(
            self.model.parameters(), self.lr)

    def remember(self, transition):
        self.memory.append(transition)

    def choose_action(self, state):
        if np.random.rand() <= self.epsilon:

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