The final classification layer is complete

+import torch
+import torch.nn as nn
+
+class FinalClassifier(nn.Module):
+    def __init__(self, input_dim, num_classes, hidden_dim=512, dropout_rate=0.3):
+        super(FinalClassifier, self).__init__()
+        # 增加一个隐藏层
+        self.fc1 = nn.Linear(input_dim, hidden_dim)  # 第一层全连接层
+        self.fc2 = nn.Linear(hidden_dim, num_classes)  # 第二层全连接层
+        self.dropout = nn.Dropout(dropout_rate)  # Dropout 防止过拟合
+        self.relu = nn.ReLU()  # 激活函数
+
+    def forward(self, x):
+        x = self.relu(self.fc1(x))  # 第一层全连接 + ReLU 激活
+        x = self.dropout(x)  # Dropout
+        out = self.fc2(x)  # 最终输出层（未应用 softmax）
+        return out