configuring processor pipelines

[Tailor2019]

Hello!
@ChWick
@andbue
Please where can I retrieve the implementation of this method? and what design the "cls()" in the source code ?
Is the create_trainer() defines parameters for training before or after preprocessing the data?
Thanks a lot for your continuous help!

[andbue]

create_trainer is defined here:
https://github.com/Planet-AI-GmbH/tfaip/blob/516a1f176e979c0abeb305550be0682c25a059e3/tfaip/scenario/scenariobase.py#L290
it calls the __init__ of the trainer class defined in the scenario, in our case

calamari/calamari_ocr/ocr/scenario.py

Lines 27 to 30 in 5068248

	def trainer_cls(cls):
	from calamari_ocr.ocr.training.trainer import Trainer
	return Trainer

this means it calls this function:

calamari/calamari_ocr/ocr/training/trainer.py

Line 35 in d12c938

def __init__(self, params: TrainerParams, scenario, restore=False):

Everything until there just defines parameters. The setup of the pipelines and the training starts only with the train()-function

calamari/calamari_ocr/ocr/training/trainer.py

Line 70 in d12c938

def train(self, callbacks=None, **kwargs):

[Tailor2019]

@ChWick
@andbue
Thanks for your fast reply!
Please can you tell about some explanation about the setup of the pipelines.
thanks a lot!

[andbue]

Sorry, you do have to be a bit more specific here.

[Tailor2019]

@andbue
I mean the preprocessing and post processing pipelines.
How can I monitor these pipeline (which parameters can I use)
Does the definition of parameters occurs after or before launching the setup of the pipelines to run?
Thanks in advance!