Source code for ignite.handlers
from typing import Any, Callable, Optional, Union
from ignite.engine import Engine
from ignite.engine.events import Events
from ignite.handlers.checkpoint import Checkpoint, DiskSaver, ModelCheckpoint
from ignite.handlers.early_stopping import EarlyStopping
from ignite.handlers.ema_handler import EMAHandler
from ignite.handlers.lr_finder import FastaiLRFinder
from ignite.handlers.param_scheduler import (
BaseParamScheduler,
ConcatScheduler,
CosineAnnealingScheduler,
CyclicalScheduler,
LinearCyclicalScheduler,
LRScheduler,
ParamGroupScheduler,
ParamScheduler,
PiecewiseLinear,
create_lr_scheduler_with_warmup,
)
from ignite.handlers.state_param_scheduler import (
ExpStateScheduler,
LambdaStateScheduler,
MultiStepStateScheduler,
PiecewiseLinearStateScheduler,
StateParamScheduler,
StepStateScheduler,
)
from ignite.handlers.stores import EpochOutputStore
from ignite.handlers.terminate_on_nan import TerminateOnNan
from ignite.handlers.time_limit import TimeLimit
from ignite.handlers.time_profilers import BasicTimeProfiler, HandlersTimeProfiler
from ignite.handlers.timing import Timer
__all__ = [
"ModelCheckpoint",
"Checkpoint",
"DiskSaver",
"Timer",
"EarlyStopping",
"TerminateOnNan",
"global_step_from_engine",
"TimeLimit",
"EpochOutputStore",
"ConcatScheduler",
"CosineAnnealingScheduler",
"LinearCyclicalScheduler",
"LRScheduler",
"ParamGroupScheduler",
"ParamScheduler",
"PiecewiseLinear",
"CyclicalScheduler",
"create_lr_scheduler_with_warmup",
"FastaiLRFinder",
"EMAHandler",
"BasicTimeProfiler",
"HandlersTimeProfiler",
"BaseParamScheduler",
"StateParamScheduler",
"LambdaStateScheduler",
"PiecewiseLinearStateScheduler",
"ExpStateScheduler",
"StepStateScheduler",
"MultiStepStateScheduler",
]
[docs]def global_step_from_engine(engine: Engine, custom_event_name: Optional[Events] = None) -> Callable:
"""Helper method to setup `global_step_transform` function using another engine.
This can be helpful for logging trainer epoch/iteration while output handler is attached to an evaluator.
Args:
engine: engine which state is used to provide the global step
custom_event_name: registered event name. Optional argument, event name to use.
Returns:
global step based on provided engine
"""
def wrapper(_: Any, event_name: Events) -> int:
if custom_event_name is not None:
event_name = custom_event_name
return engine.state.get_event_attrib_value(event_name)
return wrapper