# --------------------------------------------------------
# What Matters When Repurposing Diffusion Models for General Dense Perception Tasks? (https://arxiv.org/abs/2403.06090)
# Github source: https://github.com/aim-uofa/GenPercept
# Copyright (c) 2024, Advanced Intelligent Machines (AIM)
# Licensed under The BSD 2-Clause License [see LICENSE for details]
# Author: Guangkai Xu (https://github.com/guangkaixu/)
# --------------------------------------------------------------------------
# This code is based on Marigold and diffusers codebases
# https://github.com/prs-eth/marigold
# https://github.com/huggingface/diffusers
# --------------------------------------------------------
# If you find this code useful, we kindly ask you to cite our paper in your work.
# Please find bibtex at: https://github.com/aim-uofa/GenPercept#%EF%B8%8F-citation
# More information about the method can be found at https://github.com/aim-uofa/GenPercept
# --------------------------------------------------------------------------

from .genpercept_trainer import GenPerceptTrainer


trainer_cls_name_dict = {
    "GenPerceptTrainer": GenPerceptTrainer,
}


def get_trainer_cls(trainer_name):
    return trainer_cls_name_dict[trainer_name]
