class_docstr: Configuration class of [`LoKrModel`].
  
  Args:
      r (`int`):
          LoKr rank.
      alpha (`int`):
          The alpha parameter for LoKr scaling.
      rank_dropout (`float`):
          The dropout probability for rank dimension during training.
      module_dropout (`float`):
          The dropout probability for disabling LoKr modules during training.
      use_effective_conv2d (`bool`):
          Use parameter effective decomposition for Conv2d with ksize > 1 ("Proposition 3" from FedPara paper).
      decompose_both (`bool`):
          Perform rank decomposition of left kronecker product matrix.
      decompose_factor (`int`):
          Kronecker product decomposition factor.
      target_modules (`Optional[Union[List[str], str]]`):
          The names of the modules to apply the adapter to. If this is specified, only the modules with the specified
          names will be replaced. When passing a string, a regex match will be performed. When passing a list of
          strings, either an exact match will be performed or it is checked if the name of the module ends with any
          of the passed strings. If this is specified as 'all-linear', then all linear/Conv1D modules are chosen,
          excluding the output layer. If this is not specified, modules will be chosen according to the model
          architecture. If the architecture is not known, an error will be raised -- in this case, you should specify
          the target modules manually.
      init_weights (`bool`):
          Whether to perform initialization of adapter weights. This defaults to `True`, passing `False` is
          discouraged.
      layers_to_transform (`Union[List[int], int]`):
          The layer indices to transform. If a list of ints is passed, it will apply the adapter to the layer indices
          that are specified in this list. If a single integer is passed, it will apply the transformations on the
          layer at this index.
      layers_pattern (`str`):
          The layer pattern name, used only if `layers_to_transform` is different from `None`.
      rank_pattern (`dict`):
          The mapping from layer names or regexp expression to ranks which are different from the default rank
          specified by `r`.
      alpha_pattern (`dict`):
          The mapping from layer names or regexp expression to alphas which are different from the default alpha
          specified by `alpha`.
      modules_to_save (`Optional[List[str]]`):
          List of modules apart from adapter layers to be set as trainable and saved in the final checkpoint.
code: def __post_init__(self):
      self.peft_type = PeftType.LOKR
  
imports: from dataclasses import dataclass, field
  from typing import List, Optional, Union
  from peft.tuners.lycoris_utils import LycorisConfig
  from peft.utils import PeftType
label_desc: Use image node_id 1 for calling the LoKrConfig obj's underlying member method code with example usage: obj.__post_init__() without return types