minor fix

pina/label_tensor.py

@@ -107,10 +107,12 @@ class LabelTensor(torch.Tensor):
             raise TypeError(
                 '`label_to_extract` should be a str, or a str iterator')
 
-        try:
-            indeces = [self.labels.index(f) for f in label_to_extract]
-        except ValueError:
-            raise ValueError('`label_to_extract` not in the labels list')
+        indeces = []
+        for f in label_to_extract:
+            try:
+                indeces.append(self.labels.index(f))
+            except ValueError:
+                raise ValueError(f'`{f}` not in the labels list')
 
         new_data = self[:, indeces].float()
         new_labels = [self.labels[idx] for idx in indeces]
@@ -118,11 +120,12 @@ class LabelTensor(torch.Tensor):
 
         return extracted_tensor
 
-    def append(self, lt):
+    def append(self, lt, mode='std'):
         """
         Return a copy of the merged tensors.
 
         :param LabelTensor lt: the tensor to merge.
+        :param str mode: {'std', 'first', 'cross'}
         :return: the merged tensors
         :rtype: LabelTensor
         """
@@ -130,7 +133,23 @@ class LabelTensor(torch.Tensor):
             raise RuntimeError('The tensors to merge have common labels')
 
         new_labels = self.labels + lt.labels
-        new_tensor = torch.cat((self, lt), dim=1)
+        if mode == 'std':
+            new_tensor = torch.cat((self, lt), dim=1)
+        elif mode == 'first':
+            raise NotImplementedError
+        elif mode == 'cross':
+            tensor1 = self
+            tensor2 = lt
+            n1 = tensor1.shape[0]
+            n2 = tensor2.shape[0]
+
+            tensor1 = LabelTensor(
+                tensor1.repeat(n2, 1),
+                labels=tensor1.labels)
+            tensor2 = LabelTensor(
+                tensor2.repeat_interleave(n1, dim=0),
+                labels=tensor2.labels)
+            new_tensor = torch.cat((tensor1, tensor2), dim=1)
         return LabelTensor(new_tensor, new_labels)
 
     def __str__(self):