Add training for MACE

docs/source/apidoc/janus_core.rst

@@ -54,6 +54,16 @@ janus\_core.cli.md module
    :undoc-members:
    :show-inheritance:
 
+janus\_core.cli.train module
+----------------------------
+
+.. automodule:: janus_core.cli.train
+   :members:
+   :special-members:
+   :private-members:
+   :undoc-members:
+   :show-inheritance:
+
 janus\_core.cli.types module
 ----------------------------
 
@@ -104,6 +114,16 @@ janus\_core.helpers.mlip\_calculators module
    :undoc-members:
    :show-inheritance:
 
+janus\_core.helpers.train module
+--------------------------------
+
+.. automodule:: janus_core.helpers.train
+   :members:
+   :special-members:
+   :private-members:
+   :undoc-members:
+   :show-inheritance:
+
 janus\_core.calculations.single\_point module
 ---------------------------------------------
 

docs/source/conf.py

@@ -42,6 +42,9 @@
 }
 numpydoc_class_members_toctree = False
 
+# Mock import of MACE module to avoid breaking build
+autodoc_mock_imports = ["mace.cli.run_train"]
+
 intersphinx_mapping = {
     "python": ("https://docs.python.org/3", None),
     "numpy": ("https://numpy.org/doc/stable/", None),

janus_core/cli/janus.py

@@ -13,6 +13,13 @@
 app.command()(singlepoint)
 app.command()(geomopt)
 app.command()(md)
+# Train not imlpemented in older versions of MACE
+try:
+    from janus_core.cli.train import train
+
+    app.command()(train)
+except NotImplementedError:
+    pass
 
 
 @app.callback(invoke_without_command=True, help="")

janus_core/cli/train.py

@@ -0,0 +1,25 @@
+"""Set up MLIP training commandline interface."""
+
+from pathlib import Path
+from typing import Annotated
+
+from typer import Option, Typer
+
+from janus_core.helpers.train import train as run_train
+
+app = Typer()
+
+
+@app.command(help="Perform single point calculations and save to file.")
+def train(
+    mlip_config: Annotated[Path, Option(help="Configuration file to pass to MLIP CLI.")]
+):
+    """
+    Run training for MLIP by passing a configuration file to the MLIP's CLI.
+
+    Parameters
+    ----------
+    mlip_config : Path
+        Configuration file to pass to MLIP CLI.
+    """
+    run_train(mlip_config)

janus_core/helpers/train.py

@@ -0,0 +1,69 @@
+"""Train MLIP."""
+
+from pathlib import Path
+from typing import Optional
+
+try:
+    from mace.cli.run_train import run as run_train
+except ImportError as e:
+    raise NotImplementedError("Please update MACE to use this module.") from e
+from mace.tools import build_default_arg_parser as mace_parser
+import yaml
+
+from janus_core.helpers.janus_types import PathLike
+
+
+def check_files_exist(config: dict, req_file_keys: list[PathLike]) -> None:
+    """
+    Check files specified in the MLIP configuration file exist.
+
+    Parameters
+    ----------
+    config : dict
+        MLIP configuration file options.
+    req_file_keys : list[Pathlike]
+        List of files that must exist if defined in the configuration file.
+
+    Raises
+    ------
+    FileNotFoundError
+        If a key from `req_file_keys` is in the configuration file, but the
+        file corresponding to the configuration value do not exist.
+    """
+    for file_key in req_file_keys:
+        # Only check if file key is in the configuration file
+        if file_key in config and not Path(config[file_key]).exists():
+            raise FileNotFoundError(f"{config[file_key]} does not exist")
+
+
+def train(
+    mlip_config: PathLike, req_file_keys: Optional[list[PathLike]] = None
+) -> None:
+    """
+    Run training for MLIP by passing a configuration file to the MLIP's CLI.
+
+    Currently only supports MACE models, but this can be extended by replacing the
+    argument parsing.
+
+    Parameters
+    ----------
+    mlip_config : PathLike
+        Configuration file to pass to MLIP.
+    req_file_keys : Optional[list[PathLike]]
+        List of files that must exist if defined in the configuration file.
+        Default is ["train_file", "test_file", "valid_file", "statistics_file"].
+    """
+    if req_file_keys is None:
+        req_file_keys = ["train_file", "test_file", "valid_file", "statistics_file"]
+
+    # Validate inputs
+    with open(mlip_config, encoding="utf8") as file:
+        options = yaml.safe_load(file)
+    check_files_exist(options, req_file_keys)
+
+    if "foundation_model" in options:
+        print(f"Fine tuning model: {options['foundation_model']}")
+
+    # Path must be passed as a string
+    mlip_args = mace_parser().parse_args(["--config", str(mlip_config)])
+    run_train(mlip_args)