class_docstr: Implementation of Lottery Tickets Pruning for PyTorch models.
  
  :param model: Model that needs to be pruned
  :type model: torch.nn.Module
  :param train_loader: Dataloader for training
  :type train_loader: torch.utils.data.DataLoader
  :param test_loader: Dataloader for validation/testing
  :type test_loader: torch.utils.data.DataLoader
  :param loss_fn: Loss function to be used for training
  :type loss_fn: torch.nn.Module
  :param device: Device used for implementation ("cpu" by default)
  :type device: torch.device
code: def __init__(
      self,
      model,
      train_loader,
      test_loader,
      loss_fn=nn.CrossEntropyLoss(),
      device="cpu",
  ):
      super().__init__(
          model, train_loader, test_loader, loss_fn, device
      )
  
      self.initial_state_dict = copy.deepcopy(self.model.state_dict())
  
file_path: KD_Lib/KD_Lib/Pruning/lottery_tickets/lottery_tickets.py
imports: import copy
  import numpy
  import torch
  import torch.nn
  from ..common import BaseIterativePruner
label_desc: Use image node_id 1 to create a new LotteryTicketsPruner object from inherited base classes: BaseIterativePruner with example: obj = LotteryTicketsPruner(model, train_loader, test_loader, loss_fn, device)