class_docstr: The :class:`~poutyne.ModelBundle` class provides a straightforward experimentation tool for efficient and entirely
  customizable finetuning of the whole neural network training procedure with PyTorch. The
  :class:`~poutyne.ModelBundle` object takes care of the training and testing processes while also managing to keep
  traces of all pertinent information via the automatic logging option.
  
  Use ``ModelBundle.from_*`` methods to instanciate a :class:`~poutyne.ModelBundle`.
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docstr: Returns the path inside the model bundle directory.
docstr_tok: ["Returns","the","path","inside","the","model","bundle","directory","."]
code: def get_path(self, *paths: str) -> str:
      """
      Returns the path inside the model bundle directory.
      """
      return os.path.join(self.directory, *paths)
  
imports: import os
  import warnings
  from typing import Any, Callable, Dict, List, Tuple, Union
  import torch
  from poutyne.framework.callbacks import AtomicCSVLogger, BestModelRestore, LRSchedulerCheckpoint, ModelCheckpoint, OptimizerCheckpoint, PeriodicSaveLambda, RandomStatesCheckpoint, TensorBoardLogger
  from poutyne.framework.model import Model
  from poutyne.plotting import plot_history
  from poutyne.utils import load_random_states, set_seeds
label_desc: Use image node_id 5 for calling the ModelBundle obj's underlying member method code with example usage: obj.get_path() and returns: os