class_docstr: Mixup for labels. Should be initialized in exactly the same way as
  :cla:`ffcv.transforms.ImageMixup`.
class_docstr_tok: ["Mixup","for","labels",".","Should","be","initialized","in","exactly","the","same","way","as",":","cla",":","`","ffcv.transforms.ImageMixup","`","."]
code: def declare_state_and_memory(
      self, previous_state: State
  ) -> Tuple[State, Optional[AllocationQuery]]:
      return (
          replace(previous_state, shape=(3,), dtype=np.float32),
          AllocationQuery((3,), dtype=np.float32),
      )
  
imports: from typing import Tuple
  from numba import objmode
  import numpy
  import torch
  import torch.nn.functional
  from dataclasses import replace
  from typing import Callable, Optional, Tuple
  from ..pipeline.allocation_query import AllocationQuery
  from ..pipeline.operation import Operation
  from ..pipeline.state import State
  from ..pipeline.compiler import Compiler
label_desc: Use image node_id 3 for calling the LabelMixup obj's underlying member method code with example usage: obj.declare_state_and_memory(previous_state) and returns: replace,  AllocationQuery