lightning/pytorch_lightning/trainer/model_hooks.py

51 lines
2.0 KiB
Python

import inspect
from abc import ABC, abstractmethod
from pytorch_lightning.core.datamodule import LightningDataModule
from pytorch_lightning.core.lightning import LightningModule
class TrainerModelHooksMixin(ABC):
def is_function_implemented(self, f_name, model=None):
if model is None:
model = self.get_model()
f_op = getattr(model, f_name, None)
return callable(f_op)
def is_overridden(self, method_name: str, model: LightningModule = None) -> bool:
if model is None:
model = self.get_model()
# if you pass DataModule instead of None or a LightningModule, we use LightningDataModule as super
# TODO - refector this function to accept model_name, instance, parent so it makes more sense
super_object = LightningModule if not isinstance(model, LightningDataModule) else LightningDataModule
# assert model, 'no model passes'
if not hasattr(model, method_name):
# in case of calling deprecated method
return False
instance_attr = getattr(model, method_name)
if not instance_attr:
return False
super_attr = getattr(super_object, method_name)
# when code pointers are different, it was implemented
if hasattr(instance_attr, 'patch_loader_code'):
# cannot pickle __code__ so cannot verify if PatchDataloader
# exists which shows dataloader methods have been overwritten.
# so, we hack it by using the string representation
is_overridden = instance_attr.patch_loader_code != str(super_attr.__code__)
else:
is_overridden = instance_attr.__code__ is not super_attr.__code__
return is_overridden
def has_arg(self, f_name, arg_name):
model = self.get_model()
f_op = getattr(model, f_name, None)
return arg_name in inspect.signature(f_op).parameters
@abstractmethod
def get_model(self) -> LightningModule:
"""Warning: this is just empty shell for code implemented in other class."""