disable compilation py>=3.14

pina/trainer.py

@@ -1,12 +1,17 @@
 """Module for the Trainer."""
 
 import sys
+import warnings
 import torch
 import lightning
-from .utils import check_consistency
+from .utils import check_consistency, custom_warning_format
 from .data import PinaDataModule
 from .solver import SolverInterface, PINNInterface
 
+# set the warning for compile options
+warnings.formatwarning = custom_warning_format
+warnings.filterwarnings("always", category=UserWarning)
+
 
 class Trainer(lightning.pytorch.Trainer):
     """
@@ -49,7 +54,8 @@ class Trainer(lightning.pytorch.Trainer):
         :param float val_size: The percentage of elements to include in the
             validation dataset. Default is ``0.0``.
         :param bool compile: If ``True``, the model is compiled before training.
-            Default is ``False``. For Windows users, it is always disabled.
+            Default is ``False``. For Windows users, it is always disabled. Not
+            supported for python version greater or equal than 3.14.
         :param bool repeat: Whether to repeat the dataset data in each
             condition during training. For further details, see the
             :class:`~pina.data.data_module.PinaDataModule` class. Default is
@@ -104,8 +110,17 @@ class Trainer(lightning.pytorch.Trainer):
         super().__init__(**kwargs)
 
         # checking compilation and automatic batching
-        if compile is None or sys.platform == "win32":
+        # compilation disabled for Windows and for Python 3.14+
+        if (
+            compile is None
+            or sys.platform == "win32"
+            or sys.version_info >= (3, 14)
+        ):
             compile = False
+            warnings.warn(
+                "Compilation is disabled for Python 3.14+ and for Windows.",
+                UserWarning,
+            )
 
         repeat = repeat if repeat is not None else False
 
@@ -325,3 +340,23 @@ class Trainer(lightning.pytorch.Trainer):
         if batch_size is not None:
             check_consistency(batch_size, int)
         return pin_memory, num_workers, shuffle, batch_size
+
+    @property
+    def compile(self):
+        """
+        Whether compilation is required or not.
+
+        :return: ``True`` if compilation is required, ``False`` otherwise.
+        :rtype: bool
+        """
+        return self._compile
+
+    @compile.setter
+    def compile(self, value):
+        """
+        Setting the value of compile.
+
+        :param bool value: Whether compilation is required or not.
+        """
+        check_consistency(value, bool)
+        self._compile = value