code: def get_embedding_layer_name(model, layer, is_prompt_learning):
      """Get the name of the embedding module for a given layer."""
      for name, module in model.named_modules():
          if (
              is_prompt_learning and module == layer
          ) or module == getattr(layer, "base_layer", None):
              return name
      return None
  
file_path: peft/src/peft/utils/save_and_load.py
imports: import os
  import warnings
  from typing import Optional
  import torch
  from huggingface_hub import file_exists, hf_hub_download
  from huggingface_hub.utils import EntryNotFoundError
  from safetensors.torch import load_file
  from .other import EMBEDDING_LAYER_NAMES, SAFETENSORS_WEIGHTS_NAME, WEIGHTS_NAME, infer_device
  from .peft_types import PeftType
label_desc: Use image node_id 2 for calling a global function with example usage: get_embedding_layer_name(model, layer, is_prompt_learning) and returns: None, name