New Model running

modules/geometric_blocks.py

@@ -6,6 +6,7 @@ from torch_geometric.nn import PointConv, fps, radius, global_max_pool, knn_inte
 
 
 class SAModule(torch.nn.Module):
+
     def __init__(self, ratio, r, nn):
         super(SAModule, self).__init__()
         self.ratio = ratio

modules/util.py

@@ -84,12 +84,21 @@ class ShapeMixin:
     @property
     def shape(self):
         assert isinstance(self, (LightningBaseModule, nn.Module))
+
+        def get_out_shape(output):
+            return output.shape[1:] if len(output.shape[1:]) > 1 else output.shape[-1]
+
         if self.in_shape is not None:
             x = torch.randn(self.in_shape)
             # This is needed for BatchNorm shape checking
             x = torch.stack((x, x))
-            output = self(x)
-            return output.shape[1:] if len(output.shape[1:]) > 1 else output.shape[-1]
+
+            y = self(x)
+            if isinstance(y, tuple):
+                shape = tuple([get_out_shape(y[i]) for i in range(len(y))])
+            else:
+                shape = get_out_shape(y)
+            return shape
         else:
             return -1