class_docstr: Class to store a quantum transform with its ``args``, ``kwargs`` and classical co-transforms.  Use
  :func:`~.pennylane.transform`.
  
  .. warning::
  
      This class is developer-facing and should not be used directly. Instead, use
      :func:`qml.transform <pennylane.transform>` if you would like to make a custom
      transform.
  
  .. seealso:: :func:`~.pennylane.transform`
class_docstr_tok: ["Class","to","store","a","quantum","transform","with","its","``","args","``",",","``","kwargs","``","and","classical","co-transforms",".","Use",":","func",":","`","~.pennylane.transform","`",".","..","warning",":",":","This","class","is","developer-facing","and","should","not","be","used","directly",".","Instead",",","use",":","func",":","`","qml.transform","<","pennylane.transform",">","`","if","you","would","like","to","make","a","custom","transform",".","..","seealso",":",":",":","func",":","`","~.pennylane.transform","`"]
code: def __init__(
      self,
      transform,
      args=None,
      kwargs=None,
      classical_cotransform=None,
      is_informative=False,
      final_transform=False,
  ):  # pylint:disable=redefined-outer-name,too-many-arguments
      self._transform = transform
      self._args = args or []
      self._kwargs = kwargs or {}
      self._classical_cotransform = classical_cotransform
      self._is_informative = is_informative
      self._final_transform = is_informative or final_transform
  
imports: import functools
  import os
  import copy
  import warnings
  import types
  import pennylane
label_desc: Use image node_id 1 to create a new TransformContainer object  with example: obj = TransformContainer(transform, args, kwargs, classical_cotransform, is_informative, final_transform)