A new microblog sentiment recognition model has been added, based on the fine-tuning of GPT2, but it has not yet been adapted to the system.

model3/adapter.py

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+import torch
+import torch.nn as nn
+
+class AdapterLayer(nn.Module):
+    """
+    Adapter层实现
+    将其添加到Transformer层中可以实现参数高效微调
+    """
+    def __init__(self, input_size, adapter_size):
+        super(AdapterLayer, self).__init__()
+        # 降维全连接层
+        self.down_project = nn.Linear(input_size, adapter_size)
+        # 激活函数
+        self.activation = nn.ReLU()
+        # 升维全连接层
+        self.up_project = nn.Linear(adapter_size, input_size)
+        
+        # 初始化参数
+        self._init_weights()
+    
+    def _init_weights(self):
+        # 初始化down_project用较小的值
+        nn.init.normal_(self.down_project.weight, std=1e-2)
+        nn.init.zeros_(self.down_project.bias)
+        
+        # 初始化up_project为接近零的值，确保训练初期对原始模型影响较小
+        nn.init.normal_(self.up_project.weight, std=1e-2)
+        nn.init.zeros_(self.up_project.bias)
+    
+    def forward(self, x):
+        # 保存原始输入用于残差连接
+        residual = x
+        
+        # 通过降维层
+        x = self.down_project(x)
+        # 激活
+        x = self.activation(x)
+        # 通过升维层
+        x = self.up_project(x)
+        
+        # 残差连接
+        return residual + x