Update solvers (#434)

* Enable DDP training with batch_size=None and add validity check for split sizes
* Refactoring SolverInterfaces (#435)
* Solver update + weighting
* Updating PINN for 0.2
* Modify GAROM + tests
* Adding more versatile loggers
* Disable compilation when running on Windows
* Fix tests

---------

Co-authored-by: giovanni <giovanni.canali98@yahoo.it>
Co-authored-by: FilippoOlivo <filippo@filippoolivo.com>

pina/loss/scalar_weighting.py

@@ -0,0 +1,36 @@
+""" Module for Loss Interface """
+
+from .weighting_interface import WeightingInterface
+from ..utils import check_consistency
+
+
+class _NoWeighting(WeightingInterface):
+    def aggregate(self, losses):
+        return sum(losses.values())
+
+class ScalarWeighting(WeightingInterface):
+    """
+    TODO
+    """
+    def __init__(self, weights):
+        super().__init__()
+        check_consistency([weights], (float, dict, int))
+        if isinstance(weights, (float, int)):
+            self.default_value_weights = weights
+            self.weights = {}
+        else:
+            self.default_value_weights = 1
+            self.weights = weights
+
+    def aggregate(self, losses):
+        """
+        Aggregate the losses.
+
+        :param dict(torch.Tensor) losses: The dictionary of losses.
+        :return: The losses aggregation. It should be a scalar Tensor.
+        :rtype: torch.Tensor
+        """
+        return sum(
+            self.weights.get(condition, self.default_value_weights) * loss for
+            condition, loss in losses.items()
+        )