code: def __init__(
      self,
      base_layer: nn.Module,
      adapter_name: str,
      r: int = 0,
      lora_alpha: int = 1,
      lora_dropout: float = 0.0,
      init_lora_weights: Union[bool, str] = True,
      use_rslora: bool = False,
      **kwargs,
  ) -> None:
      super().__init__()
      LoraLayer.__init__(self, base_layer)
  
      self._active_adapter = adapter_name
      self.update_layer(
          adapter_name,
          r,
          lora_alpha,
          lora_dropout,
          init_lora_weights,
          use_rslora,
      )
  
imports: import math
  import warnings
  from typing import Any, List, Optional, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from transformers.pytorch_utils import Conv1D
  from peft.tuners.tuners_utils import BaseTunerLayer
  from peft.utils.other import transpose
  from .config import LoraConfig
label_desc: Use image node_id 1 to create a new Embedding object from inherited base classes: nn, LoraLayer with example: obj = Embedding(base_layer, adapter_name, r, lora_alpha, lora_dropout, init_lora_weights, use_rslora)