Update tests

tests/unit/dpulearn_tests/test_dpulearn_fit.py

@@ -23,12 +23,14 @@ def create_labels(size):
 
 def check_invalid_conditions(X, labels, min_samples=3, check_unique=True):
     n_samples, n_features = X.shape
+    n_unique_labels = len(set(labels))
     n_unique_samples = len(set(map(tuple, X)))
     conditions = [
         (np.any(np.isinf(X)) or np.any(np.isnan(X)), "X contains NaN or Inf"),
         (n_samples < min_samples, f"n_samples={n_samples} should be >= {min_samples}"),
         (n_features < 2, f"n_features={n_features} should be >= 2"),
         (len(labels) != n_samples, "Length of labels should match n_samples."),
+        (n_unique_labels < 2, f"n_unique_labels={n_unique_samples} should be >= 2")
     ]
     if check_unique:
         conditions.append((n_unique_samples == 1, "Feature matrix 'X' should not have all identical samples."))