RTX51 编译出现错误: I/O ERROR ON INPUT FILE: EXCEPTION 的解决方案

最新推荐文章于 2024-08-07 15:07:41 发布
原创 最新推荐文章于 2024-08-07 15:07:41 发布 · 1.3w 阅读 · 5 ·
CC 4.0 BY-SA版权
版权声明：本文为博主原创文章，遵循 CC 4.0 BY-SA 版权协议，转载请附上原文出处链接和本声明。
文章标签：

#RXT51 #tiny 编译出错 #keil

本文介绍了一个关于RTX51.Lib文件未找到导致的FATALERRORL210错误，并提供了解决方案，即在Keil软件中将Operating System设置为RTX-51tiny。



** FATAL ERROR L210: I/O ERROR ON INPUT FILE: EXCEPTION 0021H: PATH OR FILE NOT FOUND FILE: C:\KEIL\C51\LIB\RTX51.LIBTarget not created


解决方法非常简单就是在options 设置operating 为 RTX-51 tiny

刚开始 我以为工程里没包含C:\KEIL\C51\LIB\RTX51.LIB，在keil一直找，结果加入工程之后 还是不行。其实方法很简单，干开始学这个没多久，希望能帮助到新手吧！


C51FPS.lib.rar
04-15
keil软件中所需要的C51FPS.LIB. 出现错误提示:*** FATAL ERROR L210: I/O ERROR ON INPUT FILE: EXCEPTION 0021H: PATH OR FILE NOT FOUND FILE: E:\KEIL\C51\LIB\C51FPS.LIB 加入math.h头文件后，因为缺少所需要的C51FPS.LIB导致的下载错误。将C51FPS.LIB下载放入LIB文件夹（E:\KEIL\C51\LIB\C51FPS.LIB）即可。
c51fps.lib
07-20
很多朋友在用keil仿真时，有时编译不成功，出现错误提示:*** FATAL ERROR L210: I/O ERROR ON INPUT FILE: EXCEPTION 0021H: PATH OR FILE NOT FOUND FILE: E:\KEIL\C51\LIB\C51FPS.LIB ,这是由于虽然math.h这个头文件添加进去了，但是很多朋友装的keil c不是完整版本，缺少c51fps.lib这个进行浮点运算的库文件，下载这个库文件添加keil c的库中就可以编译成功了。
STC单片机操作系统——RTX51 Tiny
分享嵌入式Linux技术知识
06-15 1万+
RTX51 是keil公司开发的一款实时操作系统，其有两个版本：1.Tiny 2.Full，区别如下： RTX51 Full：使用四个任务优先权完成同时存在时间片轮转调度和抢先的任务切换 RTX51工作在 与中断功能相似的状态下 信号和信息可以通过邮箱系统在任务之间互相传递 你可以从一存 储池中分配和释放内存 你可以强迫一个任务等待中断 超时或者是从另一个任务或中断发出的 信号或信息 ...
KEIL51调试时的一些错误（转载，如有侵权，立即删除）
weixin_45902894的博客
02-17 1万+
(1)提示无M51文件 编译时候提示： F:…\XX.M51 File has been changed outside the editor, reload ？ 解决方法： 重新生成项目，产生STARTUP.A51即可。 (2)L15重复调用 ***WARNING L15: MULTIPLE CALL TO SEGMENT SEGMENT: ?PR?SPI_RECEIVE_WORD?D_SPI ...
FATAL ERROR L210: I/O ERROR ON INPUT FILE:
weixin_46656968的博客
08-07 513
FATAL ERROR L210：I/O ERROR ON INPUT FILE
keil： I/O ERROR ON INPUT FILE: EXCEPTION 的解决方案
weixin_49921105的博客
12-09 5515
太君报错日常 解决方法就是在options 设置operating system为 RTX-51 tiny 但是如果还报错！！！！！！！ 可能是你keil到期了 用注册机再注册一下。。。 且Support Period那里的时间一定要在你现在所在年份之后！！！ ...
keil2报错：FATAL ERROR L210：I/O ERROR ON INPUT FILE
r135792uuuu博客
01-26 5424
C51编程Keil2报错解决：FATAL ERROR L210：I/O ERROR ON INPUT FILE
*** FATAL ERROR L210: I/O ERROR ON INPUT FILE: EXCEPTION 0021H: PATH OR FILE NOT FOUND FILE: D:\KEIL5\C51\LIB\RTX51.LIB
05-15
好的，我现在需要帮用户解决Keil编译时出现的FATAL ERROR L210，这个错误提示是文件路径或RTX51.LIB找不到。首先，我得回忆一下用户提供的引用内容，尤其是引用[1]和[2]中提到的问题，都是关于RTX51.LIB在链接阶段找...
PRINT(".\Listings\13751267669.map") *** ERROR L210: I/O ERROR ON INPUT FILE: EXCEPTION 0021H: PATH OR FILE NOT FOUND FILE: .\Objects\ADC.obj
03-24
</think>针对Keil编译时出现的`L210 I/O error: PATH OR FILE NOT FOUND`问题，以下是分步解决方案： --- ### **问题原因** 该错误表示编译器在链接阶段找不到指定文件（如`RTX51.LIB`或`c51fps.lib`），可能由以下...
PowerShell 7 环境已加载 (版本: 7.5.2) PS C:\Users\Administrator\Desktop> cd E:\PyTorch_Build\pytorch PS E:\PyTorch_Build\pytorch> .\pytorch_env\Scripts\activate (pytorch_env) PS E:\PyTorch_Build\pytorch> # 退出虚拟环境 (pytorch_env) PS E:\PyTorch_Build\pytorch> deactivate PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 删除旧环境 PS E:\PyTorch_Build\pytorch> Remove-Item -Recurse -Force .\pytorch_env PS E:\PyTorch_Build\pytorch> Remove-Item -Recurse -Force .\cuda_env PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 创建新虚拟环境 PS E:\PyTorch_Build\pytorch> python -m venv rtx5070_env PS E:\PyTorch_Build\pytorch> .\rtx5070_env\Scripts\activate (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装基础编译工具 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install -U pip setuptools wheel ninja cmake Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pip in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (22.3.1) Collecting pip Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b7/3f/945ef7ab14dc4f9d7f40288d2df998d1837ee0888ec3659c813487572faa/pip-25.2-py3-none-any.whl (1.8 MB) Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (65.5.0) Collecting setuptools Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a3/dc/17031897dae0efacfea57dfd3a82fdd2a2aeb58e0ff71b77b87e44edc772/setuptools-80.9.0-py3-none-any.whl (1.2 MB) Collecting wheel Using cached https://pypi.tuna.tsinghua.edu.cn/packages/0b/2c/87f3254fd8ffd29e4c02732eee68a83a1d3c346ae39bc6822dcbcb697f2b/wheel-0.45.1-py3-none-any.whl (72 kB) Collecting ninja Using cached https://pypi.tuna.tsinghua.edu.cn/packages/29/45/c0adfbfb0b5895aa18cec400c535b4f7ff3e52536e0403602fc1a23f7de9/ninja-1.13.0-py3-none-win_amd64.whl (309 kB) Collecting cmake Using cached https://pypi.tuna.tsinghua.edu.cn/packages/7c/d0/73cae88d8c25973f2465d5a4457264f95617c16ad321824ed4c243734511/cmake-4.1.0-py3-none-win_amd64.whl (37.6 MB) ERROR: To modify pip, please run the following command: E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\python.exe -m pip install -U pip setuptools wheel ninja cmake [notice] A new release of pip available: 22.3.1 -> 25.2 [notice] To update, run: python.exe -m pip install --upgrade pip (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证 CUDA 安装 (rtx5070_env) PS E:\PyTorch_Build\pytorch> nvcc --version # 应显示 CUDA 12.x nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 正确更新 pip 和工具链 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python -m pip install -U pip setuptools wheel ninja cmake Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pip in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (22.3.1) Collecting pip Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b7/3f/945ef7ab14dc4f9d7f40288d2df998d1837ee0888ec3659c813487572faa/pip-25.2-py3-none-any.whl (1.8 MB) Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (65.5.0) Collecting setuptools Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a3/dc/17031897dae0efacfea57dfd3a82fdd2a2aeb58e0ff71b77b87e44edc772/setuptools-80.9.0-py3-none-any.whl (1.2 MB) Collecting wheel Using cached https://pypi.tuna.tsinghua.edu.cn/packages/0b/2c/87f3254fd8ffd29e4c02732eee68a83a1d3c346ae39bc6822dcbcb697f2b/wheel-0.45.1-py3-none-any.whl (72 kB) Collecting ninja Using cached https://pypi.tuna.tsinghua.edu.cn/packages/29/45/c0adfbfb0b5895aa18cec400c535b4f7ff3e52536e0403602fc1a23f7de9/ninja-1.13.0-py3-none-win_amd64.whl (309 kB) Collecting cmake Using cached https://pypi.tuna.tsinghua.edu.cn/packages/7c/d0/73cae88d8c25973f2465d5a4457264f95617c16ad321824ed4c243734511/cmake-4.1.0-py3-none-win_amd64.whl (37.6 MB) Installing collected packages: wheel, setuptools, pip, ninja, cmake Attempting uninstall: setuptools Found existing installation: setuptools 65.5.0 Uninstalling setuptools-65.5.0: Successfully uninstalled setuptools-65.5.0 Attempting uninstall: pip Found existing installation: pip 22.3.1 Uninstalling pip-22.3.1: Successfully uninstalled pip-22.3.1 Successfully installed cmake-4.1.0 ninja-1.13.0 pip-25.2 setuptools-80.9.0 wheel-0.45.1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip --version # 应显示 25.2+ pip 25.2 from E:\PyTorch_Build\pytorch\rtx5070_env\lib\site-packages\pip (python 3.10) (rtx5070_env) PS E:\PyTorch_Build\pytorch> cmake --version # 应显示 4.1.0+ cmake version 4.1.0 CMake suite maintained and supported by Kitware (kitware.com/cmake). (rtx5070_env) PS E:\PyTorch_Build\pytorch> ninja --version # 应显示 1.13.0+ 1.13.0.git.kitware.jobserver-pipe-1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置 CUDA 12.1 环境变量 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDA_PATH = "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:PATH = "$env:CUDA_PATH\bin;" + $env:PATH (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证 CUDA 版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> nvcc --version # 应显示 release 12.1 nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置 cuDNN 路径（根据实际安装位置） (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDNN_INCLUDE_DIR = "$env:CUDA_PATH\include" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDNN_LIBRARY = "$env:CUDA_PATH\lib\x64\cudnn.lib" (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装必要依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install pyyaml numpy typing_extensions Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting pyyaml Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b5/84/0fa4b06f6d6c958d207620fc60005e241ecedceee58931bb20138e1e5776/PyYAML-6.0.2-cp310-cp310-win_amd64.whl (161 kB) Collecting numpy Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a3/dd/4b822569d6b96c39d1215dbae0582fd99954dcbcf0c1a13c61783feaca3f/numpy-2.2.6-cp310-cp310-win_amd64.whl (12.9 MB) Collecting typing_extensions Using cached https://pypi.tuna.tsinghua.edu.cn/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl (44 kB) Installing collected packages: typing_extensions, pyyaml, numpy Successfully installed numpy-2.2.6 pyyaml-6.0.2 typing_extensions-4.15.0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装 GPU 相关依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install mkl mkl-include intel-openmp Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting mkl Using cached https://pypi.tuna.tsinghua.edu.cn/packages/91/ae/025174ee141432b974f97ecd2aea529a3bdb547392bde3dd55ce48fe7827/mkl-2025.2.0-py2.py3-none-win_amd64.whl (153.6 MB) Collecting mkl-include Using cached https://pypi.tuna.tsinghua.edu.cn/packages/06/87/3eee37bf95c6b820b6394ad98e50132798514ecda1b2584c71c2c96b973c/mkl_include-2025.2.0-py2.py3-none-win_amd64.whl (1.3 MB) Collecting intel-openmp Using cached https://pypi.tuna.tsinghua.edu.cn/packages/89/ed/13fed53fcc7ea17ff84095e89e63418df91d4eeefdc74454243d529bf5a3/intel_openmp-2025.2.1-py2.py3-none-win_amd64.whl (34.0 MB) Collecting tbb==2022.* (from mkl) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/4e/d2/01e2a93f9c644585088188840bf453f23ed1a2838ec51d5ba1ada1ebca71/tbb-2022.2.0-py3-none-win_amd64.whl (420 kB) Collecting intel-cmplr-lib-ur==2025.2.1 (from intel-openmp) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a8/70/938e81f58886fd4e114d5a5480d98c1396e73e40b7650f566ad0c4395311/intel_cmplr_lib_ur-2025.2.1-py2.py3-none-win_amd64.whl (1.2 MB) Collecting umf==0.11.* (from intel-cmplr-lib-ur==2025.2.1->intel-openmp) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/33/a0/c8d755f08f50ddd99cb4a29a7e950ced7a0903cb72253e57059063609103/umf-0.11.0-py2.py3-none-win_amd64.whl (231 kB) Collecting tcmlib==1.* (from tbb==2022.*->mkl) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/91/7b/e30c461a27b97e0090e4db822eeb1d37b310863241f8c3ee56f68df3e76e/tcmlib-1.4.0-py2.py3-none-win_amd64.whl (370 kB) Installing collected packages: tcmlib, mkl-include, umf, tbb, intel-cmplr-lib-ur, intel-openmp, mkl Successfully installed intel-cmplr-lib-ur-2025.2.1 intel-openmp-2025.2.1 mkl-2025.2.0 mkl-include-2025.2.0 tbb-2022.2.0 tcmlib-1.4.0 umf-0.11.0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装必要依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install pyyaml numpy typing_extensions Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pyyaml in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (6.0.2) Requirement already satisfied: numpy in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2.2.6) Requirement already satisfied: typing_extensions in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (4.15.0) (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装 GPU 相关依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install mkl mkl-include intel-openmp Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: mkl in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: mkl-include in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: intel-openmp in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.1) Requirement already satisfied: tbb==2022.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from mkl) (2022.2.0) Requirement already satisfied: intel-cmplr-lib-ur==2025.2.1 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-openmp) (2025.2.1) Requirement already satisfied: umf==0.11.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-cmplr-lib-ur==2025.2.1->intel-openmp) (0.11.0) Requirement already satisfied: tcmlib==1.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from tbb==2022.*->mkl) (1.4.0) (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置编译参数 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:USE_CUDA=1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:USE_CUDNN=1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CMAKE_GENERATOR="Ninja" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:MAX_JOBS=8 # 根据 CPU 核心数设置 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 运行编译 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py install ` >> --cmake ` >> --cmake-only ` >> --cmake-generator="Ninja" ` >> --verbose ` >> -DCMAKE_CUDA_COMPILER="${env:CUDA_PATH}\bin\nvcc.exe" ` >> -DCUDNN_INCLUDE_DIR="${env:CUDNN_INCLUDE_DIR}" ` >> -DCUDNN_LIBRARY="${env:CUDNN_LIBRARY}" ` >> -DTORCH_CUDA_ARCH_LIST="8.9;9.0;12.0" Building wheel torch-2.9.0a0+git2d31c3d option --cmake-generator not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> python rtx5070_test.py ============================================================ Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\rtx5070_test.py", line 39, in <module> verify_gpu_support() File "E:\PyTorch_Build\pytorch\rtx5070_test.py", line 6, in verify_gpu_support if not torch.cuda.is_available(): AttributeError: module 'torch' has no attribute 'cuda' (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置编译架构参数 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:TORCH_CUDA_ARCH_LIST="8.9;9.0;12.0" (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 使用正确的编译命令 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py install ` >> --cmake ` >> --verbose ` >> -DCMAKE_CUDA_COMPILER="${env:CUDA_PATH}\bin\nvcc.exe" ` >> -DCUDNN_INCLUDE_DIR="${env:CUDNN_INCLUDE_DIR}" ` >> -DCUDNN_LIBRARY="${env:CUDNN_LIBRARY}" ` >> -DCMAKE_GENERATOR="Ninja" ` >> -DUSE_CUDA=ON ` >> -DUSE_CUDNN=ON Building wheel torch-2.9.0a0+git2d31c3d option -D not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> python enhanced_test.py ============================================================ Python 版本: 3.10.10 Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\enhanced_test.py", line 64, in <module> verify_installation() File "E:\PyTorch_Build\pytorch\enhanced_test.py", line 11, in verify_installation print(f"\nPyTorch 版本: {torch.__version__}") AttributeError: module 'torch' has no attribute '__version__' (rtx5070_env) PS E:\PyTorch_Build\pytorch>
最新发布
09-02
由于之前编译失败，torch模块没有安装，所以出现了`AttributeError: module 'torch' has no attribute '__version__'`。如果编译安装成功，这个问题应该会解决。 因此，我们重新整理一下： 1. 设置环境变量...
C51必要文件
06-15
KEIL文件
非常实用的C51教程
04-21
最經典的C51教程，最經典的C51教程，最經典的C51教程
(li) lenovo@lenovo-ThinkStation-P920:/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan$ pip install -v --no-cache-dir --force-reinstall . 2>&1 | tee build.log Using pip 25.1 from /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/pip (python 3.10) Looking in indexes: https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple Processing /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan Preparing metadata (setup.py): started Running command python setup.py egg_info A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.6 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2. Traceback (most recent call last): File "<string>", line 2, in <module> File "<pip-setuptools-caller>", line 35, in <module> File "/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py", line 17, in <module> import torch File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/__init__.py", line 1471, in <module> from .functional import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/functional.py", line 9, in <module> import torch.nn.functional as F File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/__init__.py", line 1, in <module> from .modules import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/__init__.py", line 35, in <module> from .transformer import TransformerEncoder, TransformerDecoder, \ File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py", line 20, in <module> device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.) device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), torch.__version__ = 2.2.0+cu118 CUDA_HOME = /home/lenovo/anaconda3/envs/li CUDA version: 11.8 /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py:759: SetuptoolsDeprecationWarning: License classifiers are deprecated. !! ******************************************************************************** Please consider removing the following classifiers in favor of a SPDX license expression: License :: OSI Approved :: BSD License See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! self._finalize_license_expression() running egg_info creating /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info writing /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/PKG-INFO writing dependency_links to /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/dependency_links.txt writing requirements to /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/requires.txt writing top-level names to /tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/top_level.txt writing manifest file '/tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/SOURCES.txt' reading manifest file '/tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/SOURCES.txt' writing manifest file '/tmp/pip-pip-egg-info-w2djvsss/selective_scan.egg-info/SOURCES.txt' Preparing metadata (setup.py): finished with status 'done' Collecting torch (from selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/0a/7c/0a5b3aee977596459ec45be2220370fde8e017f651fecc40522fd478cb1e/torch-2.7.1-cp310-cp310-manylinux_2_28_x86_64.whl (821.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 821.2/821.2 MB 1.1 MB/s eta 0:00:00 Collecting packaging (from selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/20/12/38679034af332785aac8774540895e234f4d07f7545804097de4b666afd8/packaging-25.0-py3-none-any.whl (66 kB) Collecting ninja (from selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/eb/7a/455d2877fe6cf99886849c7f9755d897df32eaf3a0fba47b56e615f880f7/ninja-1.11.1.4-py3-none-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (422 kB) Collecting einops (from selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/87/62/9773de14fe6c45c23649e98b83231fffd7b9892b6cf863251dc2afa73643/einops-0.8.1-py3-none-any.whl (64 kB) Collecting filelock (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/4d/36/2a115987e2d8c300a974597416d9de88f2444426de9571f4b59b2cca3acc/filelock-3.18.0-py3-none-any.whl (16 kB) Collecting typing-extensions>=4.10.0 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/69/e0/552843e0d356fbb5256d21449fa957fa4eff3bbc135a74a691ee70c7c5da/typing_extensions-4.14.0-py3-none-any.whl (43 kB) Collecting sympy>=1.13.3 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/a2/09/77d55d46fd61b4a135c444fc97158ef34a095e5681d0a6c10b75bf356191/sympy-1.14.0-py3-none-any.whl (6.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 946.1 kB/s eta 0:00:00 Link requires a different Python (3.10.18 not in: '>=3.11'): https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/eb/8d/776adee7bbf76365fdd7f2552710282c79a4ead5d2a46408c9043a2b70ba/networkx-3.5-py3-none-any.whl (from https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/networkx/) (requires-python:>=3.11) Link requires a different Python (3.10.18 not in: '>=3.11'): https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/6c/4f/ccdb8ad3a38e583f214547fd2f7ff1fc160c43a75af88e6aec213404b96a/networkx-3.5.tar.gz (from https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/networkx/) (requires-python:>=3.11) Link requires a different Python (3.10.18 not in: '>=3.11'): https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/3f/a1/46c1b6e202e3109d2a035b21a7e5534c5bb233ee30752d7f16a0bd4c3989/networkx-3.5rc0-py3-none-any.whl (from https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/networkx/) (requires-python:>=3.11) Link requires a different Python (3.10.18 not in: '>=3.11'): https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/90/7e/0319606a20ced20730806b9f7fe91d8a92f7da63d76a5c388f87d3f7d294/networkx-3.5rc0.tar.gz (from https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/networkx/) (requires-python:>=3.11) Collecting networkx (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/b9/54/dd730b32ea14ea797530a4479b2ed46a6fb250f682a9cfb997e968bf0261/networkx-3.4.2-py3-none-any.whl (1.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 883.3 kB/s eta 0:00:00 Collecting jinja2 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl (134 kB) Collecting fsspec (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/bb/61/78c7b3851add1481b048b5fdc29067397a1784e2910592bc81bb3f608635/fsspec-2025.5.1-py3-none-any.whl (199 kB) Collecting nvidia-cuda-nvrtc-cu12==12.6.77 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/75/2e/46030320b5a80661e88039f59060d1790298b4718944a65a7f2aeda3d9e9/nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl (23.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 1.1 MB/s eta 0:00:00 Collecting nvidia-cuda-runtime-cu12==12.6.77 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/e1/23/e717c5ac26d26cf39a27fbc076240fad2e3b817e5889d671b67f4f9f49c5/nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (897 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 897.7/897.7 kB 1.7 MB/s eta 0:00:00 Collecting nvidia-cuda-cupti-cu12==12.6.80 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/49/60/7b6497946d74bcf1de852a21824d63baad12cd417db4195fc1bfe59db953/nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (8.9 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.9/8.9 MB 1.1 MB/s eta 0:00:00 Collecting nvidia-cudnn-cu12==9.5.1.17 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/2a/78/4535c9c7f859a64781e43c969a3a7e84c54634e319a996d43ef32ce46f83/nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl (571.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 571.0/571.0 MB 1.1 MB/s eta 0:00:00 Collecting nvidia-cublas-cu12==12.6.4.1 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/af/eb/ff4b8c503fa1f1796679dce648854d58751982426e4e4b37d6fce49d259c/nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (393.1 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 393.1/393.1 MB 889.2 kB/s eta 0:00:00 Collecting nvidia-cufft-cu12==11.3.0.4 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/8f/16/73727675941ab8e6ffd86ca3a4b7b47065edcca7a997920b831f8147c99d/nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (200.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 200.2/200.2 MB 761.5 kB/s eta 0:00:00 Collecting nvidia-curand-cu12==10.3.7.77 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/73/1b/44a01c4e70933637c93e6e1a8063d1e998b50213a6b65ac5a9169c47e98e/nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (56.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.3/56.3 MB 1.1 MB/s eta 0:00:00 Collecting nvidia-cusolver-cu12==11.7.1.2 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/f0/6e/c2cf12c9ff8b872e92b4a5740701e51ff17689c4d726fca91875b07f655d/nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (158.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 158.2/158.2 MB 881.4 kB/s eta 0:00:00 Collecting nvidia-cusparse-cu12==12.5.4.2 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/06/1e/b8b7c2f4099a37b96af5c9bb158632ea9e5d9d27d7391d7eb8fc45236674/nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (216.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 216.6/216.6 MB 1.4 MB/s eta 0:00:00 Collecting nvidia-cusparselt-cu12==0.6.3 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/3b/9a/72ef35b399b0e183bc2e8f6f558036922d453c4d8237dab26c666a04244b/nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl (156.8 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 156.8/156.8 MB 887.6 kB/s eta 0:00:00 Collecting nvidia-nccl-cu12==2.26.2 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/67/ca/f42388aed0fddd64ade7493dbba36e1f534d4e6fdbdd355c6a90030ae028/nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 201.3/201.3 MB 1.1 MB/s eta 0:00:00 Collecting nvidia-nvtx-cu12==12.6.77 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/56/9a/fff8376f8e3d084cd1530e1ef7b879bb7d6d265620c95c1b322725c694f4/nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB) Collecting nvidia-nvjitlink-cu12==12.6.85 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/9d/d7/c5383e47c7e9bf1c99d5bd2a8c935af2b6d705ad831a7ec5c97db4d82f4f/nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.7/19.7 MB 1.9 MB/s eta 0:00:00 Collecting nvidia-cufile-cu12==1.11.1.6 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/b2/66/cc9876340ac68ae71b15c743ddb13f8b30d5244af344ec8322b449e35426/nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 1.9 MB/s eta 0:00:00 Collecting triton==3.3.1 (from torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/8d/a9/549e51e9b1b2c9b854fd761a1d23df0ba2fbc60bd0c13b489ffa518cfcb7/triton-3.3.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.6/155.6 MB 758.4 kB/s eta 0:00:00 Collecting setuptools>=40.8.0 (from triton==3.3.1->torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/a3/dc/17031897dae0efacfea57dfd3a82fdd2a2aeb58e0ff71b77b87e44edc772/setuptools-80.9.0-py3-none-any.whl (1.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.2/1.2 MB 872.9 kB/s eta 0:00:00 Collecting mpmath<1.4,>=1.1.0 (from sympy>=1.13.3->torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/43/e3/7d92a15f894aa0c9c4b49b8ee9ac9850d6e63b03c9c32c0367a13ae62209/mpmath-1.3.0-py3-none-any.whl (536 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 kB 919.5 kB/s eta 0:00:00 Collecting MarkupSafe>=2.0 (from jinja2->torch->selective_scan==0.0.2) Downloading https://mirrors.tuna.tsinghua.edu.cn/pypi/web/packages/22/35/137da042dfb4720b638d2937c38a9c2df83fe32d20e8c8f3185dbfef05f7/MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20 kB) Building wheels for collected packages: selective_scan DEPRECATION: Building 'selective_scan' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'selective_scan'. Discussion can be found at https://github.com/pypa/pip/issues/6334 Building wheel for selective_scan (setup.py): started Running command python setup.py bdist_wheel A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.6 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2. Traceback (most recent call last): File "<string>", line 2, in <module> File "<pip-setuptools-caller>", line 35, in <module> File "/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py", line 17, in <module> import torch File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/__init__.py", line 1471, in <module> from .functional import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/functional.py", line 9, in <module> import torch.nn.functional as F File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/__init__.py", line 1, in <module> from .modules import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/__init__.py", line 35, in <module> from .transformer import TransformerEncoder, TransformerDecoder, \ File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py", line 20, in <module> device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.) device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), torch.__version__ = 2.2.0+cu118 CUDA_HOME = /home/lenovo/anaconda3/envs/li CUDA version: 11.8 /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py:759: SetuptoolsDeprecationWarning: License classifiers are deprecated. !! ******************************************************************************** Please consider removing the following classifiers in favor of a SPDX license expression: License :: OSI Approved :: BSD License See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! self._finalize_license_expression() running bdist_wheel running build running build_ext /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py:425: UserWarning: There are no g++ version bounds defined for CUDA version 11.8 warnings.warn(f'There are no {compiler_name} version bounds defined for CUDA version {cuda_str_version}') building 'selective_scan_cuda_core' extension creating /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus Emitting ninja build file /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/build.ninja... Compiling objects... Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) [1/3] c++ -MMD -MF '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o'.d -pthread -B /home/lenovo/anaconda3/envs/li/compiler_compat -Wno-unused-result -Wsign-compare -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /home/lenovo/anaconda3/envs/li/include -fPIC -O2 -isystem /home/lenovo/anaconda3/envs/li/include -fPIC '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan.cpp' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o' -O3 -std=c++17 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 FAILED: /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o c++ -MMD -MF '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o'.d -pthread -B /home/lenovo/anaconda3/envs/li/compiler_compat -Wno-unused-result -Wsign-compare -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /home/lenovo/anaconda3/envs/li/include -fPIC -O2 -isystem /home/lenovo/anaconda3/envs/li/include -fPIC '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan.cpp' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan.o' -O3 -std=c++17 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 In file included from /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/ATen/cuda/CUDAContext.h:3, from /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan.cpp:5: /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/ATen/cuda/CUDAContextLight.h:6:10: fatal error: cuda_runtime_api.h: 没有那个文件或目录 6 | #include <cuda_runtime_api.h> | ^~~~~~~~~~~~~~~~~~~~ compilation terminated. [2/3] /home/lenovo/anaconda3/envs/li/bin/nvcc --generate-dependencies-with-compile --dependency-output '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o'.d '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan_core_fwd.cu' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o' -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -O3 -std=c++17 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT162_CONVERSIONS__ --expt-relaxed-constexpr --expt-extended-lambda --use_fast_math --ptxas-options=-v -lineinfo -arch=sm_86 --threads 4 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 FAILED: /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o /home/lenovo/anaconda3/envs/li/bin/nvcc --generate-dependencies-with-compile --dependency-output '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o'.d '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan_core_fwd.cu' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_fwd.o' -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -O3 -std=c++17 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT162_CONVERSIONS__ --expt-relaxed-constexpr --expt-extended-lambda --use_fast_math --ptxas-options=-v -lineinfo -arch=sm_86 --threads 4 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 <command-line>: fatal error: cuda_runtime.h: 没有那个文件或目录 compilation terminated. <command-line>: fatal error: cuda_runtime.h: 没有那个文件或目录 compilation terminated. fatal : Could not open input file /tmp/tmpxft_00005756_00000000-7_selective_scan_core_fwd.cpp1.ii [3/3] /home/lenovo/anaconda3/envs/li/bin/nvcc --generate-dependencies-with-compile --dependency-output '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o'.d '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan_core_bwd.cu' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o' -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -O3 -std=c++17 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT162_CONVERSIONS__ --expt-relaxed-constexpr --expt-extended-lambda --use_fast_math --ptxas-options=-v -lineinfo -arch=sm_86 --threads 4 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 FAILED: /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o /home/lenovo/anaconda3/envs/li/bin/nvcc --generate-dependencies-with-compile --dependency-output '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o'.d '-I/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan' -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/TH -I/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/include/THC -I/home/lenovo/anaconda3/envs/li/include -I/home/lenovo/anaconda3/envs/li/include/python3.10 -c -c '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/csrc/selective_scan/cus/selective_scan_core_bwd.cu' -o '/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/build/temp.linux-x86_64-cpython-310/csrc/selective_scan/cus/selective_scan_core_bwd.o' -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -O3 -std=c++17 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_BFLOAT16_OPERATORS__ -U__CUDA_NO_BFLOAT16_CONVERSIONS__ -U__CUDA_NO_BFLOAT162_OPERATORS__ -U__CUDA_NO_BFLOAT162_CONVERSIONS__ --expt-relaxed-constexpr --expt-extended-lambda --use_fast_math --ptxas-options=-v -lineinfo -arch=sm_86 --threads 4 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=selective_scan_cuda_core -D_GLIBCXX_USE_CXX11_ABI=0 <command-line>: fatal error: cuda_runtime.h: 没有那个文件或目录 compilation terminated. <command-line>: fatal error: cuda_runtime.h: 没有那个文件或目录 compilation terminated. fatal : Could not open input file /tmp/tmpxft_00005755_00000000-7_selective_scan_core_bwd.cpp1.ii ninja: build stopped: subcommand failed. Traceback (most recent call last): File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 2096, in _run_ninja_build subprocess.run( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/subprocess.py", line 526, in run raise CalledProcessError(retcode, process.args, subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "<string>", line 2, in <module> File "<pip-setuptools-caller>", line 35, in <module> File "/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py", line 146, in <module> setup( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/__init__.py", line 117, in setup return distutils.core.setup(**attrs) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 186, in setup return run_commands(dist) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 202, in run_commands dist.run_commands() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 1002, in run_commands self.run_command(cmd) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py", line 1104, in run_command super().run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 1021, in run_command cmd_obj.run() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/command/bdist_wheel.py", line 370, in run self.run_command("build") File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 357, in run_command self.distribution.run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py", line 1104, in run_command super().run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 1021, in run_command cmd_obj.run() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build.py", line 135, in run self.run_command(cmd_name) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 357, in run_command self.distribution.run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py", line 1104, in run_command super().run_command(command) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 1021, in run_command cmd_obj.run() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 99, in run _build_ext.run(self) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 368, in run self.build_extensions() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 871, in build_extensions build_ext.build_extensions(self) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 484, in build_extensions self._build_extensions_serial() File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 510, in _build_extensions_serial self.build_extension(ext) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 264, in build_extension _build_ext.build_extension(self, ext) File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 565, in build_extension objects = self.compiler.compile( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 684, in unix_wrap_ninja_compile _write_ninja_file_and_compile_objects( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 1774, in _write_ninja_file_and_compile_objects _run_ninja_build( File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 2112, in _run_ninja_build raise RuntimeError(message) from e RuntimeError: Error compiling objects for extension error: subprocess-exited-with-error × python setup.py bdist_wheel did not run successfully. │ exit code: 1 ╰─> See above for output. note: This error originates from a subprocess, and is likely not a problem with pip. full command: /home/lenovo/anaconda3/envs/li/bin/python3.10 -u -c ' exec(compile('"'"''"'"''"'"' # This is <pip-setuptools-caller> -- a caller that pip uses to run setup.py # # - It imports setuptools before invoking setup.py, to enable projects that directly # import from `distutils.core` to work with newer packaging standards. # - It provides a clear error message when setuptools is not installed. # - It sets `sys.argv[0]` to the underlying `setup.py`, when invoking `setup.py` so # setuptools doesn'"'"'t think the script is `-c`. This avoids the following warning: # manifest_maker: standard file '"'"'-c'"'"' not found". # - It generates a shim setup.py, for handling setup.cfg-only projects. import os, sys, tokenize, traceback try: import setuptools except ImportError: print( "ERROR: Can not execute `setup.py` since setuptools failed to import in " "the build environment with exception:", file=sys.stderr, ) traceback.print_exc() sys.exit(1) __file__ = %r sys.argv[0] = __file__ if os.path.exists(__file__): filename = __file__ with tokenize.open(__file__) as f: setup_py_code = f.read() else: filename = "<auto-generated setuptools caller>" setup_py_code = "from setuptools import setup; setup()" exec(compile(setup_py_code, filename, "exec")) '"'"''"'"''"'"' % ('"'"'/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py'"'"',), "<pip-setuptools-caller>", "exec"))' bdist_wheel -d /tmp/pip-wheel-fm2tmb40 cwd: /media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/ Building wheel for selective_scan (setup.py): finished with status 'error' ERROR: Failed building wheel for selective_scan Running setup.py clean for selective_scan Running command python setup.py clean A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.6 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2. Traceback (most recent call last): File "<string>", line 2, in <module> File "<pip-setuptools-caller>", line 35, in <module> File "/media/lenovo/PHILIPS/Mamba_20250409_ torch22_cuda118/VMamba-main/kernels/selective_scan/setup.py", line 17, in <module> import torch File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/__init__.py", line 1471, in <module> from .functional import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/functional.py", line 9, in <module> import torch.nn.functional as F File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/__init__.py", line 1, in <module> from .modules import * # noqa: F403 File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/__init__.py", line 35, in <module> from .transformer import TransformerEncoder, TransformerDecoder, \ File "/home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py", line 20, in <module> device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.) device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), torch.__version__ = 2.2.0+cu118 CUDA_HOME = /home/lenovo/anaconda3/envs/li CUDA version: 11.8 /home/lenovo/anaconda3/envs/li/lib/python3.10/site-packages/setuptools/dist.py:759: SetuptoolsDeprecationWarning: License classifiers are deprecated. !! ******************************************************************************** Please consider removing the following classifiers in favor of a SPDX license expression: License :: OSI Approved :: BSD License See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! self._finalize_license_expression() running clean removing 'build/temp.linux-x86_64-cpython-310' (and everything under it) 'build/lib.linux-x86_64-cpython-310' does not exist -- can't clean it 'build/bdist.linux-x86_64' does not exist -- can't clean it 'build/scripts-3.10' does not exist -- can't clean it removing 'build' Failed to build selective_scan ERROR: Failed to build installable wheels for some pyproject.toml based projects (selective_scan)
07-04
我们正在尝试安装一个名为`selective_scan`的包，但遇到了编译错误和NumPy兼容性问题。根据引用[2]和[4]，我们可以推断：1.该包可能是`mamba_ssm`的一部分，因为引用[1]和[4]都提到了安装`mamba_ssm`。 2.编译错误...
第一个遇到的问题，关于KEILL
因每天学习而伟大
01-16 1337
*** FATAL ERROR L210: I/O ERROR ON INPUT FILE: EXCEPTION 0021H: PATH OR FILE NOT FOUND FILE: bmnc.obj Target not created 如果你在单片机编程的时候出现上面的错误，是因为缺少c51fps.lib文件，把此文件下载后放到C:\KEIL\C51\LIB\C51FP
keil uVision 注册过期导致编译不通过
jacklood的博客
07-28 1万+
今日练习一个LED灯的程序，程序编写好之后，编译，一直报错，如下： *** FATAL ERROR L210: I/O ERROR ON INPUT FILE: EXCEPTION 0021H: PATH OR FILE NOT FOUND FILE: test.obj 百度后，查出原因如下： 在KEIL开发环bai境中指定目标操作系统： 菜单du project-> options for target ‘target1’ 选择 "驱动"页 在 L使用扩展连接LX51替换BL51
keil c语言 位域,联合体位域在keil c遇到的问题怎样解决？
weixin_36212459的博客
05-19 1072
联合体位域在keil c遇到的问题怎样解决？因为我想让一个字节对应多个位，所以最近在网上查了一些关于联合体定义位域的资料，但是我放到keil的编译环境里运行，查看变量时得出它并不是一位，而是一个字节的变量，麻烦有高手可以解释一下原因吗，附上一个简单的测试程序：查看uBit.sBit.b0结果是一字节的，假如定义改成"unsigned b0:1;",结果变量就成了两个字节的整形变量union uni...
keilC51编译常见错误和警告说明
热门推荐
weixin_38293850的博客
08-16 2万+
如对编译出错感兴趣的网友能否把你们常遇到的错误信息收集起来并提出最终的解决办法加以归纳以期共享！( 1 )L15 重复调用 ***WARNING L15: MULTIPLE CALL TO SEGMENT SEGMENT: ?PR?SPI_RECEIVE_WORD?D_SPI CALLER1: ?PR?VSYNC_INTERRUPT?MAIN CALLER2: ?C_C51STARTUP 该警告表示连接器发现有一个函数可能会被主函数和一个中断服务程序 ( 或者调用中断服务程序的函数 ) 同时调用 , 或者.
keil编译问题
weixin_47881158的博客
05-24 1805
Build target ‘Target 1’ linking… BL51 BANKED LINKER/LOCATER V5.03 - SN: Eval Version COPYRIGHT KEIL ELEKTRONIK GmbH 1987 - 2002 “JSQ.obj” TO “JSQ” *** FATAL ERROR L210: I/O ERROR ON INPUT FILE: EXCEPTION 0021H: PATH OR FILE NOT FOUND FILE: C:\KEIL\C51\LIB\
RTX51.LIB NOT FOUND
diegui9005的博客
05-23 303
C8051系列 --------------------------------------------------------- 编译通过了，但LINK时出错：***FATALERRORL210:I/OERRORONINPUTfile:EXCEPTION0021H:PATHORFILENOTFOUNDfile:C:\KE...
评论 7
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
红包 添加红包
表情包 插入表情
表情包 代码片
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

个

红包个数最小为10个

元

红包金额最低5元

当前余额3.43元 前往充值 >
需支付：10.00元
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付元
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明：

1.余额是钱包充值的虚拟货币，按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载，可以购买VIP、付费专栏及课程。

余额充值