more logger

mlip_arena/models/utils.py

@@ -2,6 +2,13 @@
 
 import torch
 
+try:
+    from prefect.logging import get_run_logger
+
+    logger = get_run_logger()
+except (ImportError, RuntimeError):
+    from loguru import logger
+
 
 def get_freer_device() -> torch.device:
     """Get the GPU with the most free memory, or use MPS if available.
@@ -22,16 +29,16 @@ def get_freer_device() -> torch.device:
         ]
         free_gpu_index = mem_free.index(max(mem_free))
         device = torch.device(f"cuda:{free_gpu_index}")
-        print(
+        logger.info(
             f"Selected GPU {device} with {mem_free[free_gpu_index] / 1024**2:.2f} MB free memory from {device_count} GPUs"
         )
     elif torch.backends.mps.is_available():
         # If no CUDA GPUs are available but MPS is, use MPS
-        print("No GPU available. Using MPS.")
+        logger.info("No GPU available. Using MPS.")
         device = torch.device("mps")
     else:
         # Fallback to CPU if neither CUDA GPUs nor MPS are available
-        print("No GPU or MPS available. Using CPU.")
+        logger.info("No GPU or MPS available. Using CPU.")
         device = torch.device("cpu")
 
     return device

mlip_arena/tasks/elasticity.py

@@ -48,8 +48,6 @@
 from prefect.states import State
 
 from ase import Atoms
-from ase.filters import *  # type: ignore
-from ase.optimize import *  # type: ignore
 from ase.optimize.optimize import Optimizer
 from mlip_arena.models import MLIPEnum
 from mlip_arena.tasks.optimize import run as OPT
@@ -81,6 +79,8 @@ def run(
     atoms: Atoms,
     calculator_name: str | MLIPEnum,
     calculator_kwargs: dict | None = None,
+    dispersion: bool = False,
+    dispersion_kwargs: dict | None = None,
     device: str | None = None,
     optimizer: Optimizer | str = "BFGSLineSearch",  # type: ignore
     optimizer_kwargs: dict | None = None,
@@ -124,6 +124,8 @@ def run(
         atoms=atoms,
         calculator_name=calculator_name,
         calculator_kwargs=calculator_kwargs,
+        dispersion=dispersion,
+        dispersion_kwargs=dispersion_kwargs,
         device=device,
         optimizer=optimizer,
         optimizer_kwargs=optimizer_kwargs,

mlip_arena/tasks/neb.py

@@ -39,7 +39,7 @@
 from __future__ import annotations
 
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Literal
+from typing import Any, Literal
 
 from prefect import task
 from prefect.cache_policies import INPUTS, TASK_SOURCE
@@ -54,13 +54,9 @@
 from ase.utils.forcecurve import fit_images
 from mlip_arena.models import MLIPEnum
 from mlip_arena.tasks.optimize import run as OPT
-from mlip_arena.tasks.utils import get_calculator
+from mlip_arena.tasks.utils import get_calculator, logger, pformat
 from pymatgen.io.ase import AseAtomsAdaptor
 
-
-if TYPE_CHECKING:
-    pass
-
 _valid_optimizers: dict[str, Optimizer] = {
     "MDMin": MDMin,
     "FIRE": FIRE,
@@ -86,7 +82,7 @@ def _generate_task_run_name():
         atoms = parameters["start"]
     else:
         raise ValueError("No images or start atoms found in parameters")
-    
+
     calculator_name = parameters["calculator_name"]
 
     return f"{task_name}: {atoms.get_chemical_formula()} - {calculator_name}"
@@ -156,20 +152,17 @@ def run(
     criterion = criterion or {}
 
     optimizer_instance = optimizer(neb, trajectory=traj_file, **optimizer_kwargs)  # type: ignore
-
+    logger.info(f"Using optimizer: {optimizer_instance}")
+    logger.info(pformat(optimizer_kwargs))
+    logger.info(f"Criterion: {pformat(criterion)}")
     optimizer_instance.run(**criterion)
 
     neb_tool = NEBTools(neb.images)
-    barrier = neb_tool.get_barrier()
-
-    forcefit = fit_images(neb.images)
-
-    images = neb.images
 
     return {
-        "barrier": barrier,
-        "images": images,
-        "forcefit": forcefit,
+        "barrier": neb_tool.get_barrier(),
+        "images": neb.images,
+        "forcefit": fit_images(neb.images),
     }
 
 
@@ -261,7 +254,7 @@ def run_from_end_points(
         )
     )
 
-    images = [s.to_ase_atoms() for s in path]
+    images = [s.to_ase_atoms(msonable=False) for s in path]
 
     return run.with_options(
         refresh_cache=not cache_subtasks,

mlip_arena/tasks/optimize.py

@@ -15,7 +15,8 @@
 from ase.optimize import *  # type: ignore
 from ase.optimize.optimize import Optimizer
 from mlip_arena.models import MLIPEnum
-from mlip_arena.tasks.utils import get_calculator
+from mlip_arena.tasks.utils import get_calculator, logger, pformat
+
 
 _valid_filters: dict[str, Filter] = {
     "Filter": Filter,
@@ -94,16 +95,20 @@ def run(
 
     if isinstance(filter, type) and issubclass(filter, Filter):
         filter_instance = filter(atoms, **filter_kwargs)
-        print(f"Using filter: {filter_instance}")
+        logger.info(f"Using filter: {filter_instance}")
+        logger.info(pformat(filter_kwargs))
 
-        optimizer_instance = optimizer(atoms, **optimizer_kwargs)
-        print(f"Using optimizer: {optimizer_instance}")
+        optimizer_instance = optimizer(filter_instance, **optimizer_kwargs)
+        logger.info(f"Using optimizer: {optimizer_instance}")
+        logger.info(pformat(optimizer_kwargs))
+        logger.info(f"Criterion: {pformat(criterion)}")
 
         optimizer_instance.run(**criterion)
-
     elif filter is None:
         optimizer_instance = optimizer(atoms, **optimizer_kwargs)
-        print(f"Using optimizer: {optimizer_instance}")
+        logger.info(f"Using optimizer: {optimizer_instance}")
+        logger.info(pformat(optimizer_kwargs))
+        logger.info(f"Criterion: {pformat(criterion)}")
         optimizer_instance.run(**criterion)
 
     return {

mlip_arena/tasks/utils.py

@@ -5,7 +5,7 @@
 from torch_dftd.torch_dftd3_calculator import TorchDFTD3Calculator
 
 from ase import units
-from ase.calculators.calculator import Calculator
+from ase.calculators.calculator import Calculator, BaseCalculator
 from ase.calculators.mixing import SumCalculator
 from mlip_arena.models import MLIPEnum
 from mlip_arena.models.utils import get_freer_device
@@ -21,7 +21,7 @@
 
 
 def get_calculator(
-    calculator_name: str | MLIPEnum | Calculator,
+    calculator_name: str | MLIPEnum | Calculator | SumCalculator,
     calculator_kwargs: dict | None,
     dispersion: bool = False,
     dispersion_kwargs: dict | None = None,
@@ -30,22 +30,24 @@ def get_calculator(
     """Get a calculator with optional dispersion correction."""
     device = device or str(get_freer_device())
 
-    logger.info("Using device: %s", device)
+    logger.info(f"Using device: {device}")
 
     calculator_kwargs = calculator_kwargs or {}
 
     if isinstance(calculator_name, MLIPEnum) and calculator_name in MLIPEnum:
-        assert issubclass(calculator_name.value, Calculator)
         calc = calculator_name.value(**calculator_kwargs)
     elif isinstance(calculator_name, str) and hasattr(MLIPEnum, calculator_name):
         calc = MLIPEnum[calculator_name].value(**calculator_kwargs)
-    elif isinstance(calculator_name, Calculator):
-        logger.warning("Using custom calculator: {calculator_name}")
+    elif isinstance(calculator_name, type) and issubclass(calculator_name, BaseCalculator):
+        logger.warning(f"Using custom calculator class: {calculator_name}")
+        calc = calculator_name(**calculator_kwargs)
+    elif isinstance(calculator_name, Calculator | SumCalculator):
+        logger.warning(f"Using custom calculator object (kwargs are ignored): {calculator_name}")
         calc = calculator_name
     else:
         raise ValueError(f"Invalid calculator: {calculator_name}")
 
-    logger.info("Using calculator: %s", calc)
+    logger.info(f"Using calculator: {calc}")
     if calculator_kwargs:
         logger.info(pformat(calculator_kwargs))
 
@@ -61,9 +63,9 @@ def get_calculator(
         )
         calc = SumCalculator([calc, disp_calc])
 
-        logger.info("Using dispersion: %s", disp_calc)
+        logger.info(f"Using dispersion: {disp_calc}")
         if dispersion_kwargs:
             logger.info(pformat(dispersion_kwargs))
 
-    assert isinstance(calc, Calculator) or isinstance(calc, SumCalculator)
+    assert isinstance(calc, Calculator | SumCalculator)
     return calc