How to train and validate over two datamodule

1

Hello,
I have two datamodule let’s call them datamodule_train and datamodule_own_dataset
I would like to train on datamodule_train and evaluate every n epoch on the validation_set of datamodule_train AND the validation_set of datamodule_own_dataset and logs information from both validation_set.
How can I do it in a efficient way?

I can’t try to just get the train/testloaders and feed them to the trainer because they are in fact pytorch geometrics dataset and the transformation datamodule->train_dataloaders didn’t work.

I already tried to create some callback as a workaround:

class MyTrueCallback(pl.Callback):
def init(self,true_data):
self.true_data=true_data

def on_validation_epoch_end(self,trainer,pl_module):

trainer.validate(model=pl_module,datamodule=self.true_data)
return

but it failed on logging in the validation_loop of trainer trainer.validate(…) with this error:

self.log("val/miou", miou, prog_bar=True)

You are trying to self.log() but the loop’s result collection is not registered yet. This is most likely because you are trying to log in a predict hook, but it doesn’t support logging