content: import torch
  
  from nnunetv2.training.nnUNetTrainer.nnUNetTrainer import nnUNetTrainer
  
  
  class nnUNetTrainer_5epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          """used for debugging plans etc"""
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 5
  
  
  class nnUNetTrainer_1epoch(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          """used for debugging plans etc"""
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 1
  
  
  class nnUNetTrainer_10epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          """used for debugging plans etc"""
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 10
  
  
  class nnUNetTrainer_20epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 20
  
  
  class nnUNetTrainer_50epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 50
  
  
  class nnUNetTrainer_100epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 100
  
  
  class nnUNetTrainer_250epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 250
  
  
  class nnUNetTrainer_500epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 500
  
  
  class nnUNetTrainer_750epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 750
  
  
  class nnUNetTrainer_2000epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 2000
  
      
  class nnUNetTrainer_4000epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 4000
  
  
  class nnUNetTrainer_8000epochs(nnUNetTrainer):
      def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict,
                   device: torch.device = torch.device('cuda')):
          super().__init__(plans, configuration, fold, dataset_json, device)
          self.num_epochs = 8000
  