Import from the newly cleaned-up prototorch namespace

prototorch/models/glvq.py

@@ -1,18 +1,13 @@
 """Models based on the GLVQ framework."""
 
 import torch
-from prototorch.functions.activations import get_activation
-from prototorch.functions.competitions import wtac
-from prototorch.functions.distances import (
-    lomega_distance,
-    omega_distance,
-    squared_euclidean_distance,
-)
-from prototorch.functions.helper import get_flat
-from prototorch.functions.losses import glvq_loss, lvq1_loss, lvq21_loss
-from prototorch.modules import LambdaLayer, LossLayer
 from torch.nn.parameter import Parameter
 
+from ..core.competitions import wtac
+from ..core.distances import lomega_distance, omega_distance, squared_euclidean_distance
+from ..core.losses import glvq_loss, lvq1_loss, lvq21_loss
+from ..nn.activations import get_activation
+from ..nn.wrappers import LambdaLayer, LossLayer
 from .abstract import ImagePrototypesMixin, SupervisedPrototypeModel
 
 
@@ -137,7 +132,7 @@ class SiameseGLVQ(GLVQ):
 
     def compute_distances(self, x):
         protos, _ = self.proto_layer()
-        x, protos = get_flat(x, protos)
+        x, protos = [arr.view(arr.size(0), -1) for arr in (x, protos)]
         latent_x = self.backbone(x)
         self.backbone.requires_grad_(self.both_path_gradients)
         latent_protos = self.backbone(protos)