Merge branch 'materialsvirtuallab:main' into main

.github/workflows/testing.yml

@@ -44,7 +44,7 @@ jobs:
         run: |
           pytest --cov=matgl tests --color=yes
       - name: Upload coverage reports to Codecov
-        uses: codecov/codecov-action@v3
+        uses: codecov/codecov-action@v4
         env:
           CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
 

docs/Gemfile.lock

@@ -224,8 +224,7 @@ GEM
     rb-fsevent (0.11.2)
     rb-inotify (0.10.1)
       ffi (~> 1.0)
-    rexml (3.3.6)
-      strscan
+    rexml (3.3.9)
     rouge (3.26.0)
     ruby2_keywords (0.0.5)
     rubyzip (2.3.2)
@@ -240,7 +239,6 @@ GEM
       faraday (>= 0.17.3, < 3)
     simpleidn (0.2.1)
       unf (~> 0.1.4)
-    strscan (3.1.0)
     terminal-table (1.8.0)
       unicode-display_width (~> 1.1, >= 1.1.1)
     typhoeus (1.4.0)

pyproject.toml

@@ -57,7 +57,7 @@ dependencies = [
     "pydantic",
     "torchdata<=0.7.1",
     "boto3",
-    "numpy<2.0.0"
+    "numpy<3.0.0"
 ]
 version = "1.1.3"
 

requirements.txt

@@ -1,10 +1,11 @@
 dgl==2.2.1
 torch==2.2.1
 lightning==2.4.0
-pymatgen==2024.10.3
+pymatgen==2024.10.29
 ase==3.23.0
 pydantic==2.9.2
+numpy==2.1.3
 torchdata==0.7.1
-boto3==1.35.44
-numpy==1.26.4
+boto3==1.35.55
 sympy==1.13.3
+

src/matgl/graph/converters.py

@@ -50,7 +50,7 @@ def get_graph_from_processed_structure(
             DGLGraph object, state_attr
 
         """
-        u, v = torch.tensor(src_id), torch.tensor(dst_id)
+        u, v = torch.tensor(src_id, dtype=matgl.int_th), torch.tensor(dst_id, dtype=matgl.int_th)
         g = dgl.graph((u, v), num_nodes=len(structure))
         # TODO: Need to check if the variable needs to be double or float, now use float
         pbc_offset = torch.tensor(images, dtype=matgl.float_th)