import torch import datetime import types import deepspeed from transformers.deepspeed import HfDeepSpeedConfig import transformers import numpy as np from collections import OrderedDict from torch.utils.data import Dataset, DataLoader from torch.nn.utils import clip_grad_norm_ from torch.cuda.amp import autocast, GradScaler from torch.nn import DataParallel from torch.optim import lr_scheduler import torch.optim as optim import torch.nn as nn import torch.nn.functional as F from tqdm import tqdm import os import re import math import random import json import time import logging from copy import deepcopy import ipdb import argparse from model.ImageBind import data from transformers import LlamaTokenizer, LlamaForCausalLM, LlamaConfig from torch.nn.utils.rnn import pad_sequence from peft import LoraConfig, TaskType, get_peft_model logging.getLogger("transformers").setLevel(logging.WARNING) logging.getLogger("transformers.tokenization_utils").setLevel(logging.ERROR) os.environ['TOKENIZERS_PARALLELISM'] = 'false'