kaggle notebook 处理临时脚本的方法

#=写入项目临时代码
aaa='''
#!/usr/bin/env python
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#============这个脚本通过finetune instructpix2pix来得到更好的模型.

"""Script to fine-tune InstructPix2Pix."""

import argparse
import logging
import math
import os
from pathlib import Path
from typing import Optional

import accelerate
import datasets
import diffusers
import numpy as np
import PIL
import requests
import torch
import torch.nn.functional as F
import torch.utils.checkpoint
import transformers
from accelerate import Accelerator
from accelerate.logging import get_logger
from accelerate.utils import ProjectConfiguration, set_seed
from datasets import load_dataset
from diffusers import (AutoencoderKL, DDPMScheduler,
                       StableDiffusionInstructPix2PixPipeline,
                       UNet2DConditionModel)
from diffusers.optimization import get_scheduler
from diffusers.training_utils import EMAModel
from diffusers.utils import check_min_version, deprecate, is_wandb_available
from diffusers.utils.import_utils import is_xformers_available
from huggingface_hub import HfFolder, Repository, create_repo, whoami
from packaging import version
from torchvision import transforms
from tqdm.auto import tqdm
from transformers import CLIPTextModel, CLIPTokenizer

# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
check_min_version("0.15.0.dev0")

logger = get_logger(__name__, log_level="INFO")

DATASET_NAME_MAPPING = {
    "sayakpaul/cartoonizer-dataset": (
        "original_image",
        "edit_prompt",
        "cartoonized_image",
    ),
}
WANDB_TABLE_COL_NAMES = ["original_image", "edited_image", "edit_prompt"]


def parse_args():
    parser = argparse.ArgumentParser(
        description="Simple example of a training script for InstructPix2Pix."
    )
    parser.add_argument(
        "--pretrained_model_name_or_path",
        type=str,
        default=None,
        required=True,
        help="Path to pretrained model or model identifier from huggingface.co/models.",
    )
    parser.add_argument(
        "--revision",
        type=str,
        default=None,
        required=False,
        help="Revision of pretrained model identifier from huggingface.co/models.",
    )
    parser.add_argument(
        "--dataset_name",
        type=str,
        default=None,
        help=(
            "The name of the Dataset (from the HuggingFace hub) to train on (could be your own, possibly private,"
            " dataset). It can also be a path pointing to a local copy of a dataset in your filesystem,"
            " or to a folder containing files that 

标签：脚本,parser,--,image,args,kaggle,notebook,add,train	

From： https://www.cnblogs.com/zhangbo2008/p/17458830.html