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src/heads/mlp_head.py

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+"""
+MLP classification head — shared across all backbones.
+
+LayerNorm → Linear → GELU → Dropout → Linear → num_classes
+"""
+
+import torch.nn as nn
+
+
+class MLPHead(nn.Module):
+    def __init__(self, embed_dim: int, num_classes: int, hidden_dim: int = 512, dropout: float = 0.3):
+        super().__init__()
+        self.head = nn.Sequential(
+            nn.LayerNorm(embed_dim),
+            nn.Linear(embed_dim, hidden_dim),
+            nn.GELU(),
+            nn.Dropout(dropout),
+            nn.Linear(hidden_dim, num_classes),
+        )
+
+    def forward(self, x):
+        return self.head(x)