Source code for arctic_training.config.checkpoint

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from pathlib import Path
from typing import TYPE_CHECKING
from typing import Type

from pydantic import Field
from pydantic import field_validator

from arctic_training.config.base import BaseConfig
from arctic_training.config.utils import HumanInt
from arctic_training.registry import get_registered_checkpoint_engine

if TYPE_CHECKING:
    from arctic_training.checkpoint.engine import CheckpointEngine


[docs] class CheckpointConfig(BaseConfig): type: str = "" """ Checkpoint engine type. """ output_dir: Path """ Checkpoint output directory. If directory does not exist, it will be created. """ enabled: bool = True """ Enable this checkpoint engine. """ auto_resume: bool = False """ If a checkpoint is found in the output directory, resume training from that checkpoint. """ save_every_n_steps: HumanInt = Field(default=0, ge=0) """ How often to trigger a checkpoint save by training global step count. """ save_every_n_epochs: HumanInt = Field(default=0, ge=0) """ How often to trigger a checkpoint save by training epoch count. """ save_end_of_training: bool = False """ Whether to save a checkpoint at the end of training. """ @property def engine(self) -> Type["CheckpointEngine"]: return get_registered_checkpoint_engine(name=self.type) @field_validator("output_dir", mode="after") @classmethod def resolve_output_dir(cls, v: Path) -> Path: return v.resolve()