class_docstr: A basic wrapper that links defaults transforms for the data block API
class_docstr_tok: ["A","basic","wrapper","that","links","defaults","transforms","for","the","data","block","API"]
code: def __init__(
      self,
      type_tfms: list = None,  # One or more `Transform`s
      item_tfms: list = None,  # `ItemTransform`s, applied on an item
      batch_tfms: list = None,  # `Transform`s or `RandTransform`s, applied by batch
      dl_type: TfmdDL = None,  # Task specific `TfmdDL`, defaults to `TfmdDL`
      dls_kwargs: dict = None,  # Additional arguments to be passed to `DataLoaders`
  ):
      self.type_tfms = L(type_tfms)
      self.item_tfms = ToTensor + L(item_tfms)
      self.batch_tfms = L(batch_tfms)
      self.dl_type, self.dls_kwargs = dl_type, (
          {} if dls_kwargs is None else dls_kwargs
      )
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from .core import *
  from .load import *
  from .external import *
  from .transforms import *
  from inspect import isfunction, ismethod
  from .load import _collate_types
label_desc: Use image node_id 1 to create a new TransformBlock object  with example: obj = TransformBlock(type_tfms, item_tfms, batch_tfms, dl_type, dls_kwargs)