Auto3D.config.OptimizationConfig
- class Auto3D.config.OptimizationConfig(opt_steps: int = 2000, convergence_threshold: float = 0.01, patience: int = 250, batchsize_atoms: int = 1024, energy_tol: float = 0.001, energy_patience: int = 3)
Bases:
objectConfiguration for geometry optimization.
This dataclass encapsulates all parameters related to the FIRE optimizer and convergence criteria, replacing the previous untyped dict approach.
Example
>>> config = OptimizationConfig(opt_steps=1000, convergence_threshold=0.005) >>> optimizer = optimizing(in_f, out_f, model, device, config)
- __init__(opt_steps: int = 2000, convergence_threshold: float = 0.01, patience: int = 250, batchsize_atoms: int = 1024, energy_tol: float = 0.001, energy_patience: int = 3) None
Methods
__init__([opt_steps, convergence_threshold, ...])to_dict()Convert to dict for backward compatibility with existing code.
Attributes
Number of atoms per optimization batch.
Force convergence threshold in eV/Angstrom.
Number of steps energy must be stable before considering converged.
Energy convergence threshold in eV.
Maximum number of optimization steps per structure.
Number of steps without force decrease before dropping a conformer as oscillating.
- convergence_threshold: float = 0.01
Force convergence threshold in eV/Angstrom. Structure converges when maximum force falls below this value.
- patience: int = 250
Number of steps without force decrease before dropping a conformer as oscillating.
- batchsize_atoms: int = 1024
Number of atoms per optimization batch. Larger values use more GPU memory but may be faster.