Fix type of n_windows in cross_validation (#1378)

Co-authored-by: Marco <marco@nixtla.io>

Author: Riklia

neuralforecast/core.py

@@ -1337,7 +1337,7 @@ def cross_validation(
         self,
         df: Optional[DataFrame] = None,
         static_df: Optional[DataFrame] = None,
-        n_windows: int = 1,
+        n_windows: Optional[int] = 1,
         step_size: int = 1,
         val_size: Optional[int] = 0,
         test_size: Optional[int] = None,
@@ -1362,8 +1362,8 @@ def cross_validation(
             df (pandas or polars DataFrame, optional): DataFrame with columns [`unique_id`, `ds`, `y`] and exogenous variables.
                 If None, a previously stored dataset is required.
             static_df (pandas or polars DataFrame, optional): DataFrame with columns [`unique_id`] and static exogenous. Defaults to None.
-            n_windows (int): Number of windows used for cross validation. 
-            step_size (int): Step size between each window. 
+            n_windows (int, None): Number of windows used for cross validation. If None, define `test_size`.
+            step_size (int): Step size between each window.
             val_size (int, optional): Length of validation size. If passed, set `n_windows=None`. Defaults to 0.
             test_size (int, optional): Length of test size. If passed, set `n_windows=None`. 
             use_init_models (bool, optional): Use initial model passed when object was instantiated. 
@@ -1418,13 +1418,19 @@ def cross_validation(
         if n_windows is None and test_size is None:
             raise Exception("you must define `n_windows` or `test_size`.")
         if test_size is None and h is not None:
+            assert n_windows is not None
             test_size = h + step_size * (n_windows - 1)
         elif n_windows is None:
+            assert test_size is not None
+            assert h is not None
             if (test_size - h) % step_size:
-                raise Exception("`test_size - h` should be module `step_size`")
+                raise Exception("`test_size - h` must be divisible by `step_size`")
             n_windows = int((test_size - h) / step_size) + 1
         else:
             raise Exception("you must define `n_windows` or `test_size` but not both")
+    
+        assert n_windows is not None
+        assert test_size is not None
 
         # Recover initial model if use_init_models.
         if use_init_models: