Use MPS backend if available and use_device=None, add CHGNET_DEVICE env var

.github/workflows/test.yml

@@ -44,6 +44,8 @@ jobs:
 
       - name: Run Tests
         run: pytest --capture=no --cov --cov-report=xml .
+        env:
+          CHGNET_DEVICE: cpu
 
       - name: Codacy coverage reporter
         if: ${{ matrix.os == 'ubuntu-latest' && github.event_name == 'push' }}

chgnet/model/dynamics.py

@@ -3,6 +3,7 @@
 import contextlib
 import inspect
 import io
+import os
 import pickle
 import sys
 from typing import TYPE_CHECKING, Literal
@@ -51,7 +52,7 @@
 class CHGNetCalculator(Calculator):
     """CHGNet Calculator for ASE applications."""
 
-    implemented_properties = ("energy", "forces", "stress", "magmoms")
+    implemented_properties = ("energy", "forces", "stress", "magmoms")  # type: ignore
 
     def __init__(
         self,
@@ -81,7 +82,8 @@ def __init__(
         super().__init__(**kwargs)
 
         # Determine the device to use
-        if use_device == "mps" and torch.backends.mps.is_available():
+        use_device = use_device or os.getenv("CHGNET_DEVICE")
+        if use_device in ("mps", None) and torch.backends.mps.is_available():
             self.device = "mps"
         else:
             self.device = use_device or ("cuda" if torch.cuda.is_available() else "cpu")
@@ -95,7 +97,7 @@ def __init__(
         print(f"CHGNet will run on {self.device}")
 
     @property
-    def version(self) -> str:
+    def version(self) -> str | None:
         """The version of CHGNet."""
         return self.model.version
 

chgnet/model/model.py

@@ -707,7 +707,8 @@ def load(
         )
 
         # Determine the device to use
-        if use_device == "mps" and torch.backends.mps.is_available():
+        use_device = use_device or os.getenv("CHGNET_DEVICE")
+        if use_device in ("mps", None) and torch.backends.mps.is_available():
             device = "mps"
         else:
             device = use_device or ("cuda" if torch.cuda.is_available() else "cpu")
@@ -763,7 +764,7 @@ class BatchedGraph:
     directed2undirected: Tensor
     atom_positions: Sequence[Tensor]
     strains: Sequence[Tensor]
-    volumes: Sequence[Tensor]
+    volumes: Sequence[Tensor] | Tensor
 
     @classmethod
     def from_graphs(
@@ -790,8 +791,7 @@ def from_graphs(
         batched_atom_graph, batched_bond_graph = [], []
         directed2undirected = []
         atom_owners = []
-        atom_offset_idx = 0
-        n_undirected = 0
+        atom_offset_idx = n_undirected = 0
 
         for graph_idx, graph in enumerate(graphs):
             # Atoms
@@ -807,7 +807,7 @@ def from_graphs(
             else:
                 strain = None
                 lattice = graph.lattice
-            volumes.append(torch.det(lattice))
+            volumes.append(torch.dot(lattice[0], torch.cross(lattice[1], lattice[2])))
             strains.append(strain)
 
             # Bonds

pyproject.toml

@@ -50,6 +50,7 @@ find = { include = ["chgnet*"], exclude = ["tests", "tests*"] }
 [tool.ruff]
 target-version = "py39"
 include = ["**/pyproject.toml", "*.ipynb", "*.py", "*.pyi"]
+[tool.ruff.lint]
 select = [
     "B",    # flake8-bugbear
     "C4",   # flake8-comprehensions
@@ -94,6 +95,7 @@ ignore = [
     "D104",    # Missing docstring in public package
     "D205",    # 1 blank line required between summary line and description
     "DTZ005",  # use of datetime.now() without timezone
+    "E731",    # do not assign a lambda expression, use a def
     "EM",
     "ERA001",  # found commented out code
     "FBT001",  # Boolean positional argument in function
@@ -114,7 +116,7 @@ pydocstyle.convention = "google"
 isort.required-imports = ["from __future__ import annotations"]
 isort.split-on-trailing-comma = false
 
-[tool.ruff.per-file-ignores]
+[tool.ruff.lint.per-file-ignores]
 "site/*" = ["INP001", "S602"]
 "tests/*" = ["ANN201", "D103", "INP001", "S101"]
 # E402 Module level import not at top of file

tests/test_model.py

@@ -220,29 +220,37 @@ def test_as_to_from_dict() -> None:
     assert model_3.todict() == to_dict
 
 
-def test_model_load_version_params(capsys: pytest.CaptureFixture) -> None:
+def test_model_load_version_params(
+    capsys: pytest.CaptureFixture, monkeypatch: pytest.MonkeyPatch
+) -> None:
     model = CHGNet.load(use_device="cpu")
-    assert model.version == "0.3.0"
-    assert model.n_params == 412_525
+    v030_key, v030_params = "0.3.0", 412_525
+    assert model.version == v030_key
+    assert model.n_params == v030_params
     stdout, stderr = capsys.readouterr()
-    assert (
-        stdout
-        == f"""CHGNet v{model.version} initialized with {model.n_params:,} parameters
-CHGNet will run on cpu\n"""
+    expected_stdout = lambda version, params: (
+        f"CHGNet v{version} initialized with {params:,} parameters\n"
+        "CHGNet will run on cpu\n"
     )
+    assert stdout == expected_stdout(v030_key, v030_params)
     assert stderr == ""
 
-    model = CHGNet.load(model_name="0.2.0", use_device="cpu")
-    assert model.version == "0.2.0"
-    assert model.n_params == 400_438
+    v020_key, v020_params = "0.2.0", 400_438
+    model = CHGNet.load(model_name=v020_key, use_device="cpu")
+    assert model.version == v020_key
+    assert model.n_params == v020_params
     stdout, stderr = capsys.readouterr()
-    assert (
-        stdout
-        == f"""CHGNet v{model.version} initialized with {model.n_params:,} parameters
-CHGNet will run on cpu\n"""
-    )
+    assert stdout == expected_stdout(v020_key, v020_params)
     assert stderr == ""
 
     model_name = "0.1.0"  # invalid
     with pytest.raises(ValueError, match=f"Unknown {model_name=}"):
         CHGNet.load(model_name=model_name)
+
+    #     # set CHGNET_DEVICE to "cuda" and test
+    monkeypatch.setenv("CHGNET_DEVICE", env_device := "foobar")
+    with pytest.raises(
+        RuntimeError,
+        match=f"Expected one of cpu, .+type at start of device string: {env_device}",
+    ):
+        CHGNet.load()