class_docstr: Context manager to handle out of memory errors.
  
  Args:
      handle_oom: Whether to handle the error or not. If set to False,
          the exception will be propagated.
code: def __init__(self, handle_oom: bool = True):
      self.handle_oom = handle_oom
      self.oom_triggered = False
      self.oom_msg = None
  
file_path: pytorch_tabular/src/pytorch_tabular/utils/nn_utils.py
imports: import torch
  import torch.nn
  from .logger import get_logger
label_desc: Use image node_id 1 to create a new OutOfMemoryHandler object  with example: obj = OutOfMemoryHandler(handle_oom)