Fix TPOT test mode parameters and disable aeon telemetry

- Update `TPOTClassifierClass` to provide `skopt` compatible parameter spaces (using `Integer`) when both `test_mode` and `bayessearch` are enabled. This ensures tests running with Bayesian optimization do not fail due to incompatible parameter grid formats.
- Set `AEON_TRACKING` environment variable to "False" in `global_params.py` to disable telemetry and prevent potential SSL errors in restricted environments.

Author: SamoraHunter

ml_grid/model_classes/tpot_classifier_class.py

@@ -35,9 +35,16 @@ def __init__(
         self.parameter_space: Union[List[Dict[str, Any]], Dict[str, Any]]
 
         if getattr(global_parameters, "test_mode", False):
-            self.parameter_space = [
-                {"generations": [2], "population_size": [5], "max_time_mins": [1]}
-            ]
+            if global_parameters.bayessearch:
+                self.parameter_space = {
+                    "generations": Integer(2, 5),
+                    "population_size": Integer(5, 10),
+                    "max_time_mins": Integer(1, 2),
+                }
+            else:
+                self.parameter_space = [
+                    {"generations": [2], "population_size": [5], "max_time_mins": [1]}
+                ]
         elif global_parameters.bayessearch:
             # A slightly larger space for Bayesian search, but still constrained
             self.parameter_space = {

ml_grid/util/global_params.py

@@ -10,6 +10,9 @@
 from typing import Any, Callable, Dict, List, Union
 import logging
 
+# Disable aeon telemetry to prevent SSL errors in restricted environments
+os.environ["AEON_TRACKING"] = "False"
+
 
 # --- FIX for TensorFlow "libdevice not found" error ---
 # This error occurs when TensorFlow on GPU cannot locate the CUDA device libraries,