Apple M1设备安装rust-bert失败：libtorch架构不兼容求助

尝试安装rust-bert库，在Apple M1设备上遇到适配ARM芯片的问题，具体表现为PyTorch与libtorch无法正常链接。核心原因是提示libtorch不支持mac arm64架构，试过Homebrew、PyTorch官方安装包、Anaconda三种方式安装，并修改符号链接，均未解决问题。也尝试过相关问题讨论里的两种解决方案，同样无效。rust-bert是一款应用广泛的优秀库，解决该问题对Rust社区会有很大帮助。

错误信息片段 #

= note: ld: warning: ignoring file /Users/peterweyand/Code/rust-bert/target/debug/build/torch-sys-d926b35b7e909d7c/out/libtorch/libtorch/lib/libtorch.dylib, building for macOS-arm64 but attempting to link with file built for macOS-x86_64
          ld: warning: ignoring file /Users/peterweyand/Code/rust-bert/target/debug/build/torch-sys-d926b35b7e909d7c/out/libtorch/libtorch/lib/libtorch_cpu.dylib, building for macOS-arm64 but attempting to link with file built for macOS-x86_64
          ld: warning: ignoring file /Users/peterweyand/Code/rust-bert/target/debug/build/torch-sys-d926b35b7e909d7c/out/libtorch/libtorch/lib/libc10.dylib, building for macOS-arm64 but attempting to link with file built for macOS-x86_64
          Undefined symbols for architecture arm64:

已尝试的解决操作 #

• 测试了相关问题讨论中的两种解决方案，无效
• 通过Homebrew、PyTorch官方安装包、Anaconda三种渠道安装PyTorch，并修改符号链接，问题依旧
• 尝试PyTorch 1.13.0、1.13.1、2.0.0三个版本，使用命令pip3 install torch===1.13.0安装，均出现相同错误，排除版本问题

环境信息 #

Versions

peterweyand@Peters-MacBook-Pro rust-bert % python collect_env.py
Collecting environment information...
PyTorch version: 2.0.0
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: macOS 13.1 (arm64)
GCC version: Could not collect
Clang version: 15.0.7
CMake version: version 3.25.1
Libc version: N/A

Python version: 3.8.16 (default, Mar 1 2023, 21:18:45) [Clang 14.0.6 ] (64-bit runtime)
Python platform: macOS-13.1-arm64-arm-64bit
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Apple M1 Pro

Versions of relevant libraries:
[pip3] numpy==1.24.2
[pip3] torch==2.0.0
[pip3] torchaudio==2.0.1
[pip3] torchvision==0.15.1
[conda] numpy 1.24.2 pypi_0 pypi
[conda] numpy-base 1.23.5 py38h90707a3_0
[conda] torch 2.0.0 pypi_0 pypi
[conda] torchaudio 2.0.1 pypi_0 pypi
[conda] torchvision 0.15.1 pypi_0 pypi

内容的提问来源于stack exchange，提问作者yosemeti