diff --git a/pina/label_tensor.py b/pina/label_tensor.py
index f40c36d..3669272 100644
--- a/pina/label_tensor.py
+++ b/pina/label_tensor.py
@@ -114,6 +114,13 @@ class LabelTensor(torch.Tensor):
         """
         Stack a list of tensors. For example, given a tensor `a` of shape `(n,m,dof)` and a tensor `b` of dimension `(n',m,dof)`
         the resulting tensor is of shape `(n+n',m,dof)`
+
+        :param tensors: tensors to concatenate
+        :type tensors: list(LabelTensor)
+        :param dim: dimensions on which you want to perform the operation (default 0)
+        :type dim: int
+        :rtype: LabelTensor
+        :raises ValueError: either number dof or dimensions names differ
         """
         if len(tensors) == 0:
             return []
@@ -177,6 +184,13 @@ class LabelTensor(torch.Tensor):
         return out
 
     def update_labels(self, labels):
+        '''
+        Update the internal label representation according to the values passed as input.
+
+        :param labels: The label(s) to update.
+        :type labels: dict
+        :raises ValueError: dof list contain duplicates or number of dof does not match with tensor shape
+        '''
         self.labels = {
             idx_: {
                 'dof': range(self.tensor.shape[idx_]),
@@ -192,5 +206,11 @@ class LabelTensor(torch.Tensor):
         self.labels.update(labels)
 
     def init_labels_from_list(self, labels):
+        '''
+        Given a list of dof, this method update the internal label representation
+
+        :param labels: The label(s) to update.
+        :type labels: list
+        '''
         last_dim_labels = {self.tensor.ndim - 1: {'dof': labels, 'name': self.tensor.ndim - 1}}
         self.update_labels(last_dim_labels)
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