v4 update

v4/classes/vehicles-deprecated/htmono.py

@@ -0,0 +1,44 @@
+"""htmono — HTMono: single tower + ClassificationHead, no bridge."""
+from __future__ import annotations
+
+import torch
+import torch.nn as nn
+
+from v4.classes.heads.classifier import ClassificationHead
+from v4.classes.vehicles.htbase import HTBase
+
+
+class HTMono(HTBase):
+    """Single-tower vehicle: tower embedding fed directly into a ClassificationHead.
+
+    No bridge or projection — the tower's output goes straight to
+    ReLU → Dropout → Linear.  Returns ``(logits, {})`` from ``forward``
+    to match the HTFusion / HTLateral interface.
+
+    Parameters
+    ----------
+    tower       : encoder module with ``.out_dim``
+    num_classes : output classes
+    dropout     : dropout before the output linear layer
+    """
+
+    def __init__(
+        self,
+        tower:       nn.Module,
+        num_classes: int,
+        dropout:     float = 0.5,
+    ):
+        super().__init__()
+        self.tower = tower
+        self.head  = ClassificationHead(tower.out_dim, num_classes, dropout)  # type: ignore[arg-type]
+
+    def encode(self, inputs) -> torch.Tensor:
+        """Return tower embedding (pre-classifier)."""
+        if isinstance(inputs, dict):
+            # single-entry dict from HTDataset eye-level pass
+            (z,) = inputs.values()
+            return self.tower(z) if torch.is_tensor(z) else self.tower(*z.values())
+        return self.tower(inputs)
+
+    def forward(self, inputs) -> tuple[torch.Tensor, dict]:
+        return self.head(self.encode(inputs)), {}