fix(total-3mm): match M297 architecture

M297.pt contains five encoder stages with channels 1,32,64,128,256,320. The published model.py reused the extra 320 stage from the full-resolution model, causing strict checkpoint loading to fail. Validated with KonfAI 5195b79: strict load succeeds (16,550,518 parameters).

total-3mm/model.py

@@ -47,7 +47,7 @@ class ClipAndNormalize(torch.nn.Module):
 class Unet_TS_CT(network.Network):
 
     # Intrinsic to the pretrained weights (network architecture), not a tunable — fixed here.
-    CHANNELS = [1, 32, 64, 128, 256, 320, 320]
+    CHANNELS = [1, 32, 64, 128, 256, 320]
 
 
     def __init__(self,
@@ -76,4 +76,4 @@ class Unet_TS_CT(network.Network):
     ):
         nb_class, in_channels = state_dict["Model"]["Unet_TS_CT"]["Head.Conv.weight"].shape[:2]
         self["Head"].add_module("Conv", torch.nn.Conv3d(in_channels = in_channels, out_channels = nb_class, kernel_size = 1, stride = 1, padding = 0))
-        super().load(state_dict, init, ema)
+        super().load(state_dict, init, ema)