fix model

model.py

@@ -12,7 +12,11 @@ try:
 except ImportError:
     HAS_TRITON = False
 
+
 def pytorch_clifford_product(a, b):
+    # DÜZELTME BURADA: a ve b matrislerini çarpmadan önce ortak boyuta genişlet (Broadcast)
+    a, b = torch.broadcast_tensors(a, b)
+
     res = torch.zeros_like(a)
     res[..., 0] = a[...,0]*b[...,0] + a[...,1]*b[...,1] + a[...,2]*b[...,2] + a[...,3]*b[...,3] - a[...,4]*b[...,4] - a[...,5]*b[...,5] - a[...,6]*b[...,6] - a[...,7]*b[...,7]
     res[..., 1] = a[...,0]*b[...,1] + a[...,1]*b[...,0] - a[...,2]*b[...,4] + a[...,3]*b[...,6] + a[...,4]*b[...,2] - a[...,5]*b[...,7] - a[...,6]*b[...,3] - a[...,7]*b[...,5]
@@ -24,11 +28,13 @@ def pytorch_clifford_product(a, b):
     res[..., 7] = a[...,0]*b[...,7] + a[...,1]*b[...,5] + a[...,2]*b[...,6] + a[...,3]*b[...,4] + a[...,4]*b[...,3] + a[...,5]*b[...,1] + a[...,6]*b[...,2] + a[...,7]*b[...,0]
     return res
 
+
 def smart_clifford_product(a, b):
     if HAS_TRITON:
         pass 
     return pytorch_clifford_product(a, b)
 
+
 class CliffordDiracLayer(MessagePassing):
     def __init__(self, channels: int):
         super().__init__(aggr="add", node_dim=0)