class_docstr: Mixed class token concat operation.
  
  Supported arguments are:
  
  - ``embed_dim``
  
  Prefix of cls_token will be sliced.
code: def freeze_weight(self, embed_dim, **kwargs) -> Any:
      from nni.nas.oneshot.pytorch.supermodule._operation_utils import (
          Slicable,
          MaybeWeighted,
      )
  
      embed_dim_ = MaybeWeighted(embed_dim)
      cls_token = Slicable(self.cls_token)[..., :embed_dim_]
  
      return {"cls_token": cls_token}
  
imports: from __future__ import annotations
  from typing import Tuple, cast, Any, Dict
  import torch
  import torch.nn
  import torch.nn.functional
  import nni
  from nni.mutable import Categorical, MutableExpression, frozen_context, ensure_frozen, Mutable
  from nni.nas.nn.pytorch import ParametrizedModule, ModelSpace, MutableModule, Repeat, MutableConv2d, MutableLinear, MutableLayerNorm
  from nni.nas.space import current_model
  from nni.nas.oneshot.pytorch.supermodule.operation import MixedOperation
  from nni.nas.profiler.pytorch.flops import FlopsResult
  from nni.nas.profiler.pytorch.utils import MutableShape, ShapeTensor, profiler_leaf_module
  from .utils.pretrained import load_pretrained_weight
  from .utils.nn import DropPath
label_desc: Use image node_id 2 for calling the MixedClassToken obj's underlying member method code with example usage: obj.freeze_weight(embed_dim) and returns: dict