feat: raise error in case cat_dims and cat_idxs are incoherent

pytorch_tabnet/tab_network.py

@@ -794,10 +794,19 @@ def __init__(self, input_dim, cat_dims, cat_idxs, cat_emb_dim):
             If int, the same embedding dimension will be used for all categorical features
         """
         super(EmbeddingGenerator, self).__init__()
-        if cat_dims == [] or cat_idxs == []:
+        if cat_dims == [] and cat_idxs == []:
             self.skip_embedding = True
             self.post_embed_dim = input_dim
             return
+        elif (cat_dims == []) ^ (cat_idxs == []):
+            if cat_dims == []:
+                msg = "If cat_idxs is non-empty, cat_dims must be defined as a list of same length."
+            else:
+                msg = "If cat_dims is non-empty, cat_idxs must be defined as a list of same length."
+            raise ValueError(msg)
+        elif len(cat_dims) != len(cat_idxs):
+            msg = "The lists cat_dims and cat_idxs must have the same length."
+            raise ValueError(msg)
 
         self.skip_embedding = False
         if isinstance(cat_emb_dim, int):