code: def _generate_att_mask_and_pos_id(self):
      self.attention_mask = torch.full(
          (MAX_LENGTH, MAX_LENGTH),
          torch.finfo(torch.float16).min,
          device=self.device,
      )
      mask_cond = torch.arange(
          self.attention_mask.size(-1), device=self.device
      )
      self.attention_mask.masked_fill_(
          mask_cond
          < (mask_cond + 1).view(self.attention_mask.size(-1), 1),
          0,
      )
      self.attention_mask = self.attention_mask.to(torch.float16)[
          None, None, :, :
      ]
      self.position_ids = torch.arange(
          MAX_LENGTH, dtype=torch.long, device=self.device
      )[None, :]
  
imports: import argparse
  import gc
  import os
  import time
  import warnings
  from typing import Dict, List, Optional, Union
  import torch
  import torch.nn
  from accelerate import init_empty_weights
  from safetensors.torch import load_file, save_file
  from tqdm.auto import tqdm
  from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer
  from transformers.generation import GenerationMixin
  from transformers.modeling_outputs import CausalLMOutputWithPast
  from bigdl.llm import optimize_model
  from bigdl.llm.transformers.low_bit_linear import FP4Params, LowBitLinear
label_desc: Use image node_id 5 for calling the LowMemoryLlama obj's underlying member method code with example usage: obj._generate_att_mask_and_pos_id() without return types