class_docstr: Wrap a free function into a nn.Module.
  Can be useful to build a model block, and include activations or light tensor alterations
class_docstr_tok: ["Wrap","a","free","function","into","a","nn.Module",".","Can","be","useful","to","build","a","model","block",",","and","include","activations","or","light","tensor","alterations"]
code: def __init__(self, function):
      super().__init__()
      self.function = function
  
imports: import logging
  import math
  import warnings
  from enum import Enum
  from typing import Dict, List, Tuple
  import torch
  import torch.distributed
  import torch.nn
  import torch.nn.functional
  from torch.nn.modules.utils import _ntuple
  from torch.utils.checkpoint import checkpoint
  from vissl.data.collators.collator_helper import MultiDimensionalTensor
  from vissl.utils.activation_checkpointing import checkpoint_trunk
  from vissl.utils.env import get_machine_local_and_dist_rank
  from vissl.utils.misc import is_apex_available
label_desc: Use image node_id 1 to create a new Wrap object from inherited base classes: nn with example: obj = Wrap(function)