Method forward

chp4/mlp.py:17–22

(self, inputs)

        self.linear2 = nn.Linear(hidden_dim, num_class)

    def forward(self, inputs):
        hidden = self.linear1(inputs)
        activation = self.activate(hidden)
        outputs = self.linear2(activation)
        probs = F.softmax(outputs, dim=1) # 获得每个输入属于某一类别的概率
        return probs

mlp = MLP(input_dim=4, hidden_dim=5, num_class=2)
inputs = torch.rand(3, 4) # 输入形状为(3, 4)的张量，其中3表示有3个输入，4表示每个输入的维度