code: def original_apply_o(self, X):
      O = self.o_proj(X)
      return O
  
imports: import torch
  from typing import Optional, Tuple, List, Union
  from torch.nn.functional import scaled_dot_product_attention
  from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask
  from transformers.models.llama.modeling_llama import logger, BaseModelOutputWithPast, CausalLMOutputWithPast
  from ..kernels import *
  from ._utils import *
  from ._utils import __version__
  from transformers.models.llama.modeling_llama import LlamaAttention, LlamaDecoderLayer, LlamaModel, LlamaForCausalLM
  from peft import PeftModelForCausalLM
  import gc
  import peft
  import bitsandbytes
  import numpy
  import types
  from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig, AutoConfig
  from transformers import set_seed
  from peft import LoraConfig, TaskType, get_peft_model
label_desc: Use image node_id 2 for calling a global function with example usage: original_apply_o(X) and returns: O