Fix deprecation warning for torch.load

.github/workflows/publish.yml

@@ -0,0 +1,31 @@
+name: Publish package to PyPI when a new version tag is pushed
+
+on:
+  push:
+    tags:
+      - 'v[0-9]+.[0-9]+.[0-9]+'
+
+jobs:
+  pypi-publish:
+    name: Publish release to PyPI
+    runs-on: ubuntu-latest
+    environment:
+      name: pypi
+      url: https://pypi.org/p/nnbma>
+    permissions:
+      id-token: write
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: "3.x"
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -q build
+      - name: Build package
+        run: |
+          python -m build
+      - name: Publish package distributions to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1

README.md

@@ -29,6 +29,6 @@ It enables to evaluate any neural network, its gradient, and its Hessian matrix
 
 If you do not have a Python environment compatible with the above dependencies, we advise you to create a specific conda environment to use this code (<https://conda.io/projects/conda/en/latest/user-guide/>).
 
-## Reference
+## References
 
 \[1\] Palud, P. & Einig, L. & Le Petit, F. & Bron, E. & Chainais, P. & Chanussot, J. & Pety, J. & Thouvenin, P.-A. & Languignon, D. & Beslić, I. & G. Santa-Maria, M. & Orkisz, J.H. & Ségal, L. & Zakardjian, A. & Bardeau, S. & Gerin, M. & Goicoechea, J.R. & Gratier, P. & Guzman, V. (2023). Neural network-based emulation of interstellar medium models. Astronomy & Astrophysics. 10.1051/0004-6361/202347074.

nnbma/__init__.py

@@ -1,3 +1,5 @@
+__version__ = "1.0.2"
+
 from .dataset import *
 from .layers import *
 from .learning import *

nnbma/networks/neural_network.py

@@ -728,7 +728,7 @@ def _recursive_load(path: str) -> "NeuralNetwork":
         module: nn.Module = type_module(**d)
 
         sd = module.state_dict()
-        sd.update(torch.load(template.format("state_dict.pth")))
+        sd.update(torch.load(template.format("state_dict.pth"), weights_only=True))
         module.load_state_dict(sd)
 
         return module

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "nnbma"
-version = "1.0.1"
+version = ["version"]
 authors = [
   "Lucas Einig", "Pierre Palud",
 ]