Ray restored to cluster mode

Author: JQGoh

nixtla_tests/conftest.py

@@ -4,7 +4,6 @@
 import pandas as pd
 import pytest
 import ray
-import sys
 import utilsforecast.processing as ufp
 
 from copy import deepcopy
@@ -655,17 +654,10 @@ def dask_future_ex_vars_df_diff_cols(distributed_future_ex_vars_df, renamer):
 
 @pytest.fixture(scope="module")
 def ray_cluster_setup():
-    if sys.platform.startswith('win'):
-        # job could get stuck like
-        # https://github.com/Nixtla/nixtla/actions/runs/15506996482/job/43663088378?pr=647
-        # https://docs.ray.io/en/latest/ray-contribute/testing-tips.html#id3
-        # On Windows, support for multi-node Ray clusters is currently experimental and untested
-        ray.init(local_mode=True)
-    else:
-        ray_cluster = Cluster(initialize_head=True, head_node_args={"num_cpus": 2})
-        ray.init(address=ray_cluster.address, ignore_reinit_error=True)
-        # add mock node to simulate a cluster
-        ray_cluster.add_node(num_cpus=2)   
+    ray_cluster = Cluster(initialize_head=True, head_node_args={"num_cpus": 2})
+    ray.init(address=ray_cluster.address, ignore_reinit_error=True)
+    # add mock node to simulate a cluster
+    ray_cluster.add_node(num_cpus=2)
 
     yield
     ray.shutdown()