class_docstr: This is a thin wrapper for head execution, which records the output of
  wrapped module for executing the heads forked from this module.
code: def __init__(self, name, module):
      super().__init__()
      self.name = name
      self.output = torch.zeros(0)
      self._module = module
      # `ClassyBlock` isn't thread safe since it saves state. To avoid
      # doing this, the recommended workflow is to set `Model.wrapper_cls = None`
      # before instantiation (see the docs for `ClassyModel`). We support this
      # environment variable for older use cases but using it is not recommended.
      self._is_output_stateless = (
          os.environ.get("CLASSY_BLOCK_STATELESS") == "1"
      )
  
file_path: ClassyVision/classy_vision/models/classy_block.py
imports: import os
  import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new ClassyBlock object from inherited base classes: nn with example: obj = ClassyBlock(name, module)