code: def __init__(
      self,
      models,
      optimizers,
      batch_size,
      loss_funcs,
      dataset,
      mining_funcs=None,
      iterations_per_epoch=None,
      data_device=None,
      dtype=None,
      loss_weights=None,
      sampler=None,
      collate_fn=None,
      lr_schedulers=None,
      gradient_clippers=None,
      freeze_these=(),
      freeze_trunk_batchnorm=False,
      label_hierarchy_level=0,
      dataloader_num_workers=2,
      data_and_label_getter=None,
      dataset_labels=None,
      set_min_label_to_zero=False,
      end_of_iteration_hook=None,
      end_of_epoch_hook=None,
  ):
      self.models = models
      self.optimizers = optimizers
      self.batch_size = batch_size
      self.loss_funcs = loss_funcs
      self.dataset = dataset
      self.mining_funcs = {} if mining_funcs is None else mining_funcs
      self.iterations_per_epoch = iterations_per_epoch
      self.data_device = data_device
      self.dtype = dtype
      self.sampler = sampler
      self.collate_fn = collate_fn
      self.lr_schedulers = lr_schedulers
      self.gradient_clippers = gradient_clippers
      self.freeze_these = freeze_these
      self.freeze_trunk_batchnorm = freeze_trunk_batchnorm
      self.label_hierarchy_level = label_hierarchy_level
      self.dataloader_num_workers = dataloader_num_workers
      self.loss_weights = loss_weights
      self.data_and_label_getter = data_and_label_getter
      self.dataset_labels = dataset_labels
      self.set_min_label_to_zero = set_min_label_to_zero
      self.end_of_iteration_hook = end_of_iteration_hook
      self.end_of_epoch_hook = end_of_epoch_hook
      self.loss_names = list(self.loss_funcs.keys())
      self.custom_setup()
      self.verify_dict_keys()
      self.initialize_models()
      self.initialize_data_device()
      self.initialize_label_mapper()
      self.initialize_loss_tracker()
      self.initialize_loss_weights()
      self.initialize_data_and_label_getter()
      self.initialize_hooks()
      self.initialize_lr_schedulers()
  
imports: import torch
  import tqdm
  from ..utils import common_functions
  from ..utils import loss_tracker
  from ..utils.key_checker import KeyChecker, KeyCheckerDict
label_desc: Use image node_id 1 to create a new BaseTrainer object  with example: obj = BaseTrainer(models, optimizers, batch_size, loss_funcs, dataset, mining_funcs, iterations_per_epoch, data_device, dtype, loss_weights, sampler, collate_fn, lr_schedulers, gradient_clippers, freeze_these, freeze_trunk_batchnorm, label_hierarchy_level, dataloader_num_workers, data_and_label_getter, dataset_labels, set_min_label_to_zero, end_of_iteration_hook, end_of_epoch_hook)