Merge pull request #100 from diningphil/plotter_metric_storage_fix

minor on plotter

Author: diningphil

CHANGELOG.md

@@ -1,4 +1,10 @@
 # Changelog
+## [1.5.9] Minor fix
+
+## Changed
+  - Replaced torch.save with atomic_save of PyDGN to handle cases where metrics data storage corrupted the file
+
+
 ## [1.5.8] Minor fix
 
 ## Fixed

docs/conf.py

@@ -24,7 +24,7 @@
 author = "Federico Errica"
 
 # The full version, including alpha/beta/rc tags
-release = "1.5.8"
+release = "1.5.9"
 
 
 # -- General configuration ---------------------------------------------------

pydgn/training/callback/plotter.py

@@ -2,6 +2,7 @@
 from pathlib import Path
 
 import torch
+from pydgn.training.util import atomic_save
 from torch.utils.tensorboard import SummaryWriter
 
 from pydgn.static import *
@@ -33,7 +34,7 @@ def __init__(self,
         self.writer = SummaryWriter(log_dir=Path(self.exp_path, "tensorboard"))
 
         self.stored_metrics = {"losses": {}, "scores": {}}
-        self.stored_metrics_path = Path(self.exp_path, "metrics_data.torch")
+        self.stored_metrics_path = Path(self.exp_path, "metrics_data.pt")
         if os.path.exists(self.stored_metrics_path):
             self.stored_metrics = torch.load(self.stored_metrics_path)
 
@@ -87,11 +88,7 @@ def on_epoch_end(self, state: State):
                     self.stored_metrics[t][k].append(v.item())
 
         if self.store_on_disk:
-            try:
-                torch.save(self.stored_metrics, self.stored_metrics_path)
-            except RuntimeError as e:
-                print(e)
-
+            atomic_save(self.stored_metrics, self.stored_metrics_path)
 
     def on_fit_end(self, state: State):
         """

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "pydgn"
-version = "1.5.8"
+version = "1.5.9"
 description = "A Python Package for Deep Graph Networks"
 authors = [ { name="Federico Errica", email="f.errica@protonmail.com" } ]
 readme = "README.md"