Tutorials v0.1 (#178)

Tutorial update and small fixes

* Tutorials update + Tutorial FNO
* Create a metric tracker callback
* Update PINN for logging
* Update plotter for plotting
* Small fix LabelTensor
* Small fix FNO

---------

Co-authored-by: Dario Coscia <dariocoscia@cli-10-110-13-250.WIFIeduroamSTUD.units.it>
Co-authored-by: Dario Coscia <dariocoscia@dhcp-176.eduroam.sissa.it>

pina/callbacks/__init__.py

@@ -1,7 +1,9 @@
 __all__ = [
     'SwitchOptimizer',
     'R3Refinement',
+    'MetricTracker'
 ]
 
 from .optimizer_callbacks import SwitchOptimizer
-from .adaptive_refinment_callbacks import R3Refinement
+from .adaptive_refinment_callbacks import R3Refinement
+from .processing_callbacks import MetricTracker

pina/callbacks/processing_callbacks.py

@@ -0,0 +1,25 @@
+'''PINA Callbacks Implementations'''
+
+from lightning.pytorch.callbacks import Callback
+import torch
+import copy
+
+
+class MetricTracker(Callback):
+    """
+    PINA implementation of a Lightining Callback to track relevant
+    metrics during training.
+    """
+    def __init__(self):
+        self._collection = []
+
+    def on_train_epoch_end(self, trainer, __):
+        self._collection.append(copy.deepcopy(trainer.logged_metrics)) # track them
+
+    @property
+    def metrics(self):
+        common_keys = set.intersection(*map(set, self._collection))
+        v = {k: torch.stack([dic[k] for dic in self._collection]) for k in common_keys}
+        return v
+
+