MobileViT的伪代码

MobileViT是一种基于Transformer的视觉模型，用于图像分类任务。以下是MobileViT的伪代码：

class MobileViT(nn.Module):
    def __init__(self, num_classes, patch_size, num_layers, hidden_dim, num_heads, mlp_dim):
        super(MobileViT, self).__init__()
        
        self.patch_embedding = nn.Conv2d(in_channels=3, out_channels=hidden_dim, kernel_size=patch_size, stride=patch_size)
        self.positional_encoding = PositionalEncoding(hidden_dim)
        
        self.transformer_encoder = nn.TransformerEncoder(
            nn.TransformerEncoderLayer(d_model=hidden_dim, nhead=num_heads, dim_feedforward=mlp_dim),
            num_layers=num_layers
        )
        
        self.classifier = nn.Linear(hidden_dim, num_classes)
    
    def forward(self, x):
        x = self.patch_embedding(x)
        x = x.flatten(2).transpose(1, 2)
        x = self.positional_encoding(x)
        x = self.transformer_encoder(x)
        x = x.mean(dim=1)
        x = self.classifier(x)
        
        return x

其中，MobileViT的核心是Transformer编码器部分，它由多个TransformerEncoderLayer组成。输入图像经过patch embedding和位置编码后，进入Transformer编码器进行特征提取和建模。最后，通过全局平均池化和线性分类器得到最终的分类结果。