diff --git a/dicee/models/clifford.py b/dicee/models/clifford.py
index 570090f7..196aba72 100644
--- a/dicee/models/clifford.py
+++ b/dicee/models/clifford.py
@@ -1,7 +1,5 @@
 from .base_model import BaseKGE
 import torch
-from torch.nn import functional as F
-from torch import nn
 
 
 class CMult(BaseKGE):
diff --git a/dicee/models/function_space.py b/dicee/models/function_space.py
index fc991ac1..57bfa6f1 100644
--- a/dicee/models/function_space.py
+++ b/dicee/models/function_space.py
@@ -18,7 +18,6 @@ def __init__(self, args):
         self.gamma = torch.randn(self.k, self.num_sample)  # N(0,1)
         # Lazy import
         from scipy.special import roots_legendre
-        from scipy.special import roots_legendre
         roots, weights = roots_legendre(self.num_sample)
         self.roots = torch.from_numpy(roots).repeat(self.k, 1).float()  # shape self.k by self.n
         self.weights = torch.from_numpy(weights).reshape(1, -1).float()  # shape 1 by self.n
@@ -81,6 +80,8 @@ def __init__(self, args):
         self.param_init(self.entity_embeddings.weight.data), self.param_init(self.relation_embeddings.weight.data)
         self.k = int(np.sqrt(self.embedding_dim // 2))
         self.num_sample = 250
+        # Lazy import
+        from scipy.special import roots_legendre
         roots, weights = roots_legendre(self.num_sample)
         self.roots = torch.from_numpy(roots).repeat(self.k, 1).float()  # shape self.k by self.n
         self.weights = torch.from_numpy(weights).reshape(1, -1).float()  # shape 1 by self.n
diff --git a/dicee/models/pykeen_models.py b/dicee/models/pykeen_models.py
index e2aeacdb..7c218691 100644
--- a/dicee/models/pykeen_models.py
+++ b/dicee/models/pykeen_models.py
@@ -57,7 +57,7 @@ def __init__(self, args: dict):
         try:
             # lazy import
             from pykeen.models import model_resolver
-        except:
+        except ImportError:
             print(traceback.format_exc())
             print("Pykeen does not work with pytorch>2.0.0. Current pytorch version:",torch.__version__)
             exit(1)