• transformers安装避坑


    1.4 下载rust编辑器

    看到这里你肯定会疑惑了,我们不是要用python的吗

    这个我也不知道,你下了就对了,不然后面的transformers无法安装

    因为是windows到官网选择推荐的下载方式https://www.rust-lang.org/tools/install

    在这里插入图片描述
    执行文件,输入1即可。

    在这里插入图片描述
    测试是否安装成功。
    在这里插入图片描述

    避坑2:所有的下载都必须git clone,不要本地下载

    这是因为git clone下载时会自动有个node tree,我不知道这hash值具体有什么用的,应该类似钥匙,如果本地下载后,它们就会没有这个hash值,运行webui-user.bat时就会提示错误。

    错误类似:

    reference is not a tree: 24268930bf1dce879235a7fddd0b2355b84d7ea6

    2.1 在完成上述步骤后,就运行webui-user.bat

    等一会,等到命令行工具显示下载installing GFPGAN时,就Ctrl+C停止批量工具操作,这时会产生一个\venv\Scripts的路径。

    2.2 git clone命令与相应操作如下(看自己安装目录更改)

    使用git bash工具

    git clone https://github.com/TencentARC/GFPGAN.git "D:\SD\venv\Scripts\GFPGAN"
    

    之后在命令行到D:\SD\venv\Scripts\GFPGAN输入如下的命令。

    D:\SD\venv\Scripts\python.exe -m pip install basicsr facexlib 
    D:\SD\venv\Scripts\python.exe -m pip install -r requirements.txt 
    D:\SD\venv\Scripts\python.exe setup.py develop
    D:\SD\venv\Scripts\python.exe -m pip install realesrgan
    

    然后到下载open_clip,也是同样的git bash

    git clone https://github.com/mlfoundations/open_clip "D:\SD\venv\Scripts\open_clip"
    

    命令行到D:\SD\venv\Scripts\open_clip输入如下的命令。

    D:\SD\venv\Scripts\python.exe setup.py build install
    

    也是同样的操作到CLIP

    git clone https://github.com/openai/CLIP.git "D:\SD\venv\Scripts\CLIP"
    

    到相应的目录下,输入如下命令

    D:\SD\venv\Scripts\python.exe -m pip install ftfy regex tqdm
    D:\SD\venv\Scripts\python.exe setup.py build install
    
    2.3 gitclone与安装依赖

    其实操作也跟2.2类型,相应操作也是合起来如下,没有repositories文件夹,就自己新建一个:

    git clone https://github.com/Stability-AI/stablediffusion.git "D:\SD\repositories\stable-diffusion-stability-ai" 
    
    git clone https://github.com/CompVis/taming-transformers.git "D:\SD\repositories\taming-transformers" 
    
    git clone https://github.com/crowsonkb/k-diffusion.git "D:\SD\repositories\k-diffusion"
    
    git clone https://github.com/sczhou/CodeFormer.git "D:\SD\repositories\CodeFormer" 
    
    git clone https://github.com/salesforce/BLIP.git "D:\SD\repositories\BLIP"
    

    但是要到上面涉及到的每个目录下,检查是否有requirements.txt文件,有就到对应目录的命令行,执行如下命令

    D:\SD\venv\Scripts\python.exe -m pip install -r requirements.txt 
    
    2.4 pip transformers时,麻烦的tokenziers错误
    解决方案:网络问题,试多几次(这里我用了差不多3~4h弄成功了)

    尽管之前已经安装好了rust编辑器,但是它还会提示各种千奇百怪的错误,比如我下面这个。

    Building wheels for collected packages: tokenizers
      Building wheel for tokenizers (pyproject.toml) ... error
      error: subprocess-exited-with-error
    
      × Building wheel for tokenizers (pyproject.toml) did not run successfully.
      │ exit code: 1
      ╰─> [62 lines of output]
          running bdist_wheel
          running build
          running build_py
          creating build
          creating build\lib.win-amd64-cpython-310
          creating build\lib.win-amd64-cpython-310\tokenizers
          copying py_src\tokenizers\__init__.py -> build\lib.win-amd64-cpython-310\tokenizers
          creating build\lib.win-amd64-cpython-310\tokenizers\models
          copying py_src\tokenizers\models\__init__.py -> build\lib.win-amd64-cpython-310\tokenizers\models
          creating build\lib.win-amd64-cpython-310\tokenizers\decoders
          copying py_src\tokenizers\decoders\__init__.py -> build\lib.win-amd64-cpython-310\tokenizers\decoders
          creating build\lib.win-amd64-cpython-310\tokenizers\normalizers
          copying py_src\tokenizers\normalizers\__init__.py -> build\lib.win-amd64-cpython-310\tokenizers\normalizers
          creating build\lib.win-amd64-cpython-310\tokenizers\pre_tokenizers
          copying py_src\tokenizers\pre_tokenizers\__init__.py -> build\lib.win-amd64-cpython-310\tokenizers\pre_tokenizers
          creating build\lib.win-amd64-cpython-310\tokenizers\processors
          copying py_src\tokenizers\processors\__init__.py -> build\lib.win-amd64-cpython-310\tokenizers\processors
          creating build\lib.win-amd64-cpython-310\tokenizers\trainers
          copying py_src\tokenizers\trainers\__init__.py -> build\lib.win-amd64-cpython-310\tokenizers\trainers
          creating build\lib.win-amd64-cpython-310\tokenizers\implementations
          copying py_src\tokenizers\implementations\base_tokenizer.py -> build\lib.win-amd64-cpython-310\tokenizers\implementations
          copying py_src\tokenizers\implementations\bert_wordpiece.py -> build\lib.win-amd64-cpython-310\tokenizers\implementations
          copying py_src\tokenizers\implementations\byte_level_bpe.py -> build\lib.win-amd64-cpython-310\tokenizers\implementations
          copying py_src\tokenizers\implementations\char_level_bpe.py -> build\lib.win-amd64-cpython-310\tokenizers\implementations
          copying py_src\tokenizers\implementations\sentencepiece_bpe.py -> build\lib.win-amd64-cpython-310\tokenizers\implementations
          copying py_src\tokenizers\implementations\sentencepiece_unigram.py -> build\lib.win-amd64-cpython-310\tokenizers\implementations
          copying py_src\tokenizers\implementations\__init__.py -> build\lib.win-amd64-cpython-310\tokenizers\implementations
          creating build\lib.win-amd64-cpython-310\tokenizers\tools
          copying py_src\tokenizers\tools\visualizer.py -> build\lib.win-amd64-cpython-310\tokenizers\tools
          copying py_src\tokenizers\tools\__init__.py -> build\lib.win-amd64-cpython-310\tokenizers\tools
          copying py_src\tokenizers\__init__.pyi -> build\lib.win-amd64-cpython-310\tokenizers
          copying py_src\tokenizers\models\__init__.pyi -> build\lib.win-amd64-cpython-310\tokenizers\models
          copying py_src\tokenizers\decoders\__init__.pyi -> build\lib.win-amd64-cpython-310\tokenizers\decoders
          copying py_src\tokenizers\normalizers\__init__.pyi -> build\lib.win-amd64-cpython-310\tokenizers\normalizers
          copying py_src\tokenizers\pre_tokenizers\__init__.pyi -> build\lib.win-amd64-cpython-310\tokenizers\pre_tokenizers
          copying py_src\tokenizers\processors\__init__.pyi -> build\lib.win-amd64-cpython-310\tokenizers\processors
          copying py_src\tokenizers\trainers\__init__.pyi -> build\lib.win-amd64-cpython-310\tokenizers\trainers
          copying py_src\tokenizers\tools\visualizer-styles.css -> build\lib.win-amd64-cpython-310\tokenizers\tools
          running build_ext
          running build_rust
          cargo rustc --lib --message-format=json-render-diagnostics --manifest-path Cargo.toml --release -v --features pyo3/extension-module --crate-type cdylib --
          warning: unused manifest key: target.x86_64-apple-darwin.rustflags
              Updating crates.io index
          warning: spurious network error (2 tries remaining): failed to send request: 鎿嶄綔瓒呮椂
          ; class=Os (2)
          warning: spurious network error (1 tries remaining): failed to send request: 鎿嶄綔瓒呮椂
          ; class=Os (2)
          error: failed to get `env_logger` as a dependency of package `tokenizers-python v0.10.3 (C:\Users\LENOVO\AppData\Local\Temp\pip-install-bw47mt33\tokenizers_3b1650888a634bdab4e4c98d147e7833)`
    
          Caused by:
            failed to load source for dependency `env_logger`
    
          Caused by:
            Unable to update registry `crates-io`
    
          Caused by:
            failed to fetch `https://github.com/rust-lang/crates.io-index`
    
          Caused by:
            failed to send request: 鎿嶄綔瓒呮椂
            ; class=Os (2)
          error: `cargo rustc --lib --message-format=json-render-diagnostics --manifest-path Cargo.toml --release -v --features pyo3/extension-module --crate-type cdylib --` failed with code 101
          [end of output]
    
      note: This error originates from a subprocess, and is likely not a problem with pip.
      ERROR: Failed building wheel for tokenizers
    Failed to build tokenizers
    

    后面我找了网上不少答案,发现它们的回答根本就不统一,后面我问了一下chatGPT,人家的回答如下:

    说人话:chatGPT不知道为什么会这样啊?

    注意

    其实就是网络问题,跟你的工具版本没关系的,你多试几次,或者找找有没有更快下载的通道

    在这里插入图片描述

    错误信息表明在安装过程中构建tokenizers包的wheel文件出现了问题。错误发生在运行cargo rustc命令时,该命令用于编译Rust代码。

    具体的错误信息如下:

    error: failed to get `env_logger` as a dependency of package `tokenizers-python v0.10.3`
    

    这个错误表明构建过程无法获取tokenizers包所需的env_logger依赖项。

    错误进一步说明了以下内容:

    Caused by:
      Unable to update registry `crates-io`
    
    Caused by:
      failed to fetch `https://github.com/rust-lang/crates.io-index`
    
    Caused by:
      failed to send request: 鎿嶄綔瓒呮椂
    ; class=Os (2)
    

    这些消息表明更新注册表和获取所需的依赖项时出现了问题。错误信息failed to send request: 鎿嶄綔瓒呮椂表明可能存在网络问题或者crates.io索引的临时问题。

    以下是解决该问题的几个步骤:

    1. 检查网络连接:确保您拥有稳定的互联网连接,并能够访问外部资源。

    2. 重试安装:有时网络问题可能是暂时的。再次尝试运行安装命令,看看问题是否能够解决。

    3. 清除pip缓存:pip会缓存软件包以提高安装速度。然而,缓存文件有时会引发问题。您可以尝试通过运行以下命令清除pip缓存:

      pip cache purge
      
    4. 指定其他软件包源:您可以尝试从其他软件包源安装该软件包。例如,您可以使用--index-url选项来指定另一个软件包索引:

      pip install --index-url https://pypi.python.org/simple/ tokenizers
      
    5. 升级pip和setuptools:过时的pip和setuptools版本有时会引发问题。尝试运行以下命令升级它们:

      pip install --upgrade pip
      pip install --upgrade setuptools
      
    6. 安装Rust:tokenizers包依赖于Rust。确保您的系统上已安装Rust并且是最新版本。您可以按照官方Rust网站(https://www.rust-lang.org/tools/install)上的说明安装Rust。

    如果尝试了这些步骤后问题仍然存在,建议搜索与tokenizers包相关的类似问题或错误消息,看看是否有已知的解决方案或变通方法。您可以在论坛或问题跟踪器上寻找相关信息。

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  • 原文地址:https://blog.csdn.net/chaishen10000/article/details/134354776