一、编译相关
1.submodules/simple-knn/simple_knn.cu(90): error: identifier "FLT_MAX" is undefined
me.minn = { FLT_MAX, FLT_MAX, FLT_MAX };
部署photoreg工程，在编译simple_knn的时候，报错：
(photoreg) lee@lee-System-Product-Name:~/project/PhotoRegCodes$ pip install submodules/simple-knn
Processing ./submodules/simple-knnPreparing metadata (setup.py) ... done
Building wheels for collected packages: simple_knnBuilding wheel for simple_knn (setup.py) ... errorerror: subprocess-exited-with-error× python setup.py bdist_wheel did not run successfully.│ exit code: 1╰─> [113 lines of output]running bdist_wheelrunning buildrunning build_ext/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/utils/cpp_extension.py:414: UserWarning: The detected CUDA version (12.5) has a minor version mismatch with the version that was used to compile PyTorch (12.4). Most likely this shouldn't be a problem.warnings.warn(CUDA_MISMATCH_WARN.format(cuda_str_version, torch.version.cuda))/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/utils/cpp_extension.py:424: UserWarning: There are no g++ version bounds defined for CUDA version 12.5warnings.warn(f'There are no {compiler_name} version bounds defined for CUDA version {cuda_str_version}')building 'simple_knn._C' extension/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/utils/cpp_extension.py:1965: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].warnings.warn(Emitting ninja build file /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/build.ninja...Compiling objects...Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)[1/3] /usr/local/cuda/bin/nvcc --generate-dependencies-with-compile --dependency-output /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/simple_knn.o.d -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/TH -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/lee/miniconda3/envs/photoreg/include/python3.8 -c -c /home/lee/project/PhotoRegCodes/submodules/simple-knn/simple_knn.cu -o /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/simple_knn.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'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_89,code=compute_89 -gencode=arch=compute_89,code=sm_89 -std=c++17FAILED: /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/simple_knn.o/usr/local/cuda/bin/nvcc --generate-dependencies-with-compile --dependency-output /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/simple_knn.o.d -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/TH -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/lee/miniconda3/envs/photoreg/include/python3.8 -c -c /home/lee/project/PhotoRegCodes/submodules/simple-knn/simple_knn.cu -o /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/simple_knn.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'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_89,code=compute_89 -gencode=arch=compute_89,code=sm_89 -std=c++17/home/lee/project/PhotoRegCodes/submodules/simple-knn/simple_knn.cu:23: warning: "__CUDACC__" redefined23 | #define __CUDACC__|<command-line>: note: this is the location of the previous definition/home/lee/project/PhotoRegCodes/submodules/simple-knn/simple_knn.cu:23: warning: "__CUDACC__" redefined23 | #define __CUDACC__|<command-line>: note: this is the location of the previous definition/home/lee/project/PhotoRegCodes/submodules/simple-knn/simple_knn.cu(90): error: identifier "FLT_MAX" is undefinedme.minn = { FLT_MAX, FLT_MAX, FLT_MAX };^/home/lee/project/PhotoRegCodes/submodules/simple-knn/simple_knn.cu(154): error: identifier "FLT_MAX" is undefinedfloat best[3] = { FLT_MAX, FLT_MAX, FLT_MAX };^2 errors detected in the compilation of "/home/lee/project/PhotoRegCodes/submodules/simple-knn/simple_knn.cu".[2/3] c++ -MMD -MF /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/ext.o.d -pthread -B /home/lee/miniconda3/envs/photoreg/compiler_compat -Wno-unused-result -Wsign-compare -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /home/lee/miniconda3/envs/photoreg/include -fPIC -O2 -isystem /home/lee/miniconda3/envs/photoreg/include -fPIC -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/TH -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/lee/miniconda3/envs/photoreg/include/python3.8 -c -c /home/lee/project/PhotoRegCodes/submodules/simple-knn/ext.cpp -o /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/ext.o -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++17[3/3] /usr/local/cuda/bin/nvcc --generate-dependencies-with-compile --dependency-output /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/spatial.o.d -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/TH -I/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/lee/miniconda3/envs/photoreg/include/python3.8 -c -c /home/lee/project/PhotoRegCodes/submodules/simple-knn/spatial.cu -o /home/lee/project/PhotoRegCodes/submodules/simple-knn/build/temp.linux-x86_64-cpython-38/spatial.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'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=_C -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_89,code=compute_89 -gencode=arch=compute_89,code=sm_89 -std=c++17/home/lee/project/PhotoRegCodes/submodules/simple-knn/spatial.cu: In function ‘at::Tensor distCUDA2(const at::Tensor&)’:/home/lee/project/PhotoRegCodes/submodules/simple-knn/spatial.cu:23:64: warning: ‘T* at::Tensor::data() const [with T = float]’ is deprecated: Tensor.data<T>() is deprecated. Please use Tensor.data_ptr<T>() instead. [-Wdeprecated-declarations]23 | SimpleKNN::knn(P, (float3*)points.contiguous().data<float>(), means.contiguous().data<float>());| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/ATen/core/TensorBody.h:247:1: note: declared here247 | T * data() const {| ^ ~~/home/lee/project/PhotoRegCodes/submodules/simple-knn/spatial.cu:23:102: warning: ‘T* at::Tensor::data() const [with T = float]’ is deprecated: Tensor.data<T>() is deprecated. Please use Tensor.data_ptr<T>() instead. [-Wdeprecated-declarations]23 | SimpleKNN::knn(P, (float3*)points.contiguous().data<float>(), means.contiguous().data<float>());| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ^/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/include/ATen/core/TensorBody.h:247:1: note: declared here247 | T * data() const {| ^ ~~ninja: build stopped: subcommand failed.Traceback (most recent call last):File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 2105, in _run_ninja_buildsubprocess.run(File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/subprocess.py", line 516, in runraise 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 34, in <module>File "/home/lee/project/PhotoRegCodes/submodules/simple-knn/setup.py", line 21, in <module>setup(File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/__init__.py", line 117, in setupreturn distutils.core.setup(**attrs)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/core.py", line 183, in setupreturn run_commands(dist)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/core.py", line 199, in run_commandsdist.run_commands()File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/dist.py", line 954, in run_commandsself.run_command(cmd)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/dist.py", line 999, in run_commandsuper().run_command(command)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/dist.py", line 973, in run_commandcmd_obj.run()File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/command/bdist_wheel.py", line 410, in runself.run_command("build")File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/cmd.py", line 316, in run_commandself.distribution.run_command(command)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/dist.py", line 999, in run_commandsuper().run_command(command)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/dist.py", line 973, in run_commandcmd_obj.run()File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/command/build.py", line 135, in runself.run_command(cmd_name)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/cmd.py", line 316, in run_commandself.distribution.run_command(command)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/dist.py", line 999, in run_commandsuper().run_command(command)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/dist.py", line 973, in run_commandcmd_obj.run()File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/command/build_ext.py", line 98, in run_build_ext.run(self)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/command/build_ext.py", line 359, in runself.build_extensions()File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 866, in build_extensionsbuild_ext.build_extensions(self)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/command/build_ext.py", line 476, in build_extensionsself._build_extensions_serial()File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/command/build_ext.py", line 502, in _build_extensions_serialself.build_extension(ext)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/command/build_ext.py", line 263, in build_extension_build_ext.build_extension(self, ext)File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/setuptools/_distutils/command/build_ext.py", line 557, in build_extensionobjects = self.compiler.compile(File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 679, in unix_wrap_ninja_compile_write_ninja_file_and_compile_objects(File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1785, in _write_ninja_file_and_compile_objects_run_ninja_build(File "/home/lee/miniconda3/envs/photoreg/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 2121, in _run_ninja_buildraise RuntimeError(message) from eRuntimeError: Error compiling objects for extension[end of output]note: This error originates from a subprocess, and is likely not a problem with pip.ERROR: Failed building wheel for simple_knnRunning setup.py clean for simple_knn
Failed to build simple_knn
ERROR: ERROR: Failed to build installable wheels for some pyproject.toml based projects (simple_knn)根据error信息，simple_knn.cu第90行me.minn = { FLT_MAX, FLT_MAX, FLT_MAX }中的"FLT_MAX" 变量没有定义，所以找到这个文件打开然后在前面加上一行include的代码引入即可：最后重新pip install simple-knn即可完成编译安装
二、python第三方库与conda
1.InvalidSpec: The package "nvidia/linux-64::cuda-compiler==12.6.2=0" is not available for the specified platform
输入photoreg安装环境的命令，但是报错
(photoreg) lee@lee-System-Product-Name:~/project/PhotoRegCodes$ conda install pytorch torchvision torchaudio cuda-toolkit=11.8 -c pytorch -c nvidia
Channels:- pytorch- nvidia- conda-forge- http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free- defaults
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: failedInvalidSpec: The package "nvidia/linux-64::cuda-compiler==12.6.2=0" is not available for the specified platform上面这个命令在试图安装cuda工具包以及对应的pytorch，其实因为系统里面已经安装了全局的cuda包，没有必要再重复安装某些包，比如cuda编译器等。
（1）查看相关的pytorch版本以及与cuda的对应关系
(photoreg) lee@lee-System-Product-Name:~/project/PhotoRegCodes$ conda search pytorch -c pytorch
Loading channels: done（节选）
# Name Version Build Channel
pytorch 2.3.0 cpu_generic_py310h0ab6cb9_0 conda-forge
pytorch 2.3.0 cpu_generic_py310ha4c588e_1 conda-forge
pytorch 2.3.0 cpu_generic_py311h255d53b_0 conda-forge
pytorch 2.3.0 cpu_generic_py311h8ca351a_1 conda-forge
pytorch 2.3.0 cpu_generic_py312h2f1fc2b_1 conda-forge
pytorch 2.3.0 cpu_generic_py312hab8db8b_0 conda-forge
pytorch 2.3.0 cpu_generic_py38h1fa1760_1 conda-forge
pytorch 2.3.0 cpu_generic_py38hbe06502_0 conda-forge
pytorch 2.3.0 cpu_generic_py39h87eea44_0 conda-forge
pytorch 2.3.0 cpu_generic_py39he75b87c_1 conda-forge
pytorch 2.3.0 cpu_mkl_py310h75865b9_101 conda-forge
pytorch 2.3.0 cpu_mkl_py310hcb3bde6_100 conda-forge
pytorch 2.3.0 cpu_mkl_py311h9835ca6_100 conda-forge
pytorch 2.3.0 cpu_mkl_py311hcb16b95_101 conda-forge
pytorch 2.3.0 cpu_mkl_py312h3b258cc_101 conda-forge
pytorch 2.3.0 cpu_mkl_py312he7b903e_100 conda-forge
pytorch 2.3.0 cpu_mkl_py38h1c8c993_100 conda-forge
pytorch 2.3.0 cpu_mkl_py38h51400c9_101 conda-forge
pytorch 2.3.0 cpu_mkl_py39h85c4de8_101 conda-forge
pytorch 2.3.0 cpu_mkl_py39hb6713ec_100 conda-forge
pytorch 2.3.0 cpu_py310h08bb5f6_1 pkgs/main
pytorch 2.3.0 cpu_py310h1ce4368_1 pkgs/main
pytorch 2.3.0 cpu_py310h2a1f63a_0 pkgs/main
pytorch 2.3.0 cpu_py310hcb105a3_0 pkgs/main
pytorch 2.3.0 cpu_py311h0178f48_1 pkgs/main
pytorch 2.3.0 cpu_py311h6fe12db_1 pkgs/main
pytorch 2.3.0 cpu_py311h991c31c_0 pkgs/main
pytorch 2.3.0 cpu_py311ha0631a7_0 pkgs/main
pytorch 2.3.0 cpu_py312h1f09096_0 pkgs/main
pytorch 2.3.0 cpu_py312h544eda6_0 pkgs/main
pytorch 2.3.0 cpu_py312h5a90aa3_1 pkgs/main
pytorch 2.3.0 cpu_py312hde650b8_1 pkgs/main
pytorch 2.3.0 cpu_py38h08bb5f6_1 pkgs/main
pytorch 2.3.0 cpu_py38h1ce4368_1 pkgs/main
pytorch 2.3.0 cpu_py38h2a1f63a_0 pkgs/main
pytorch 2.3.0 cpu_py38hcb105a3_0 pkgs/main
pytorch 2.3.0 cpu_py39h08bb5f6_1 pkgs/main
pytorch 2.3.0 cpu_py39h1ce4368_1 pkgs/main
pytorch 2.3.0 cpu_py39h2a1f63a_0 pkgs/main
pytorch 2.3.0 cpu_py39hcb105a3_0 pkgs/main
pytorch 2.3.0 cuda118_py310h6f85f1b_300 conda-forge
pytorch 2.3.0 cuda118_py310h954aa82_301 conda-forge
pytorch 2.3.0 cuda118_py311h4ee7bbc_301 conda-forge
pytorch 2.3.0 cuda118_py311h6c9cb27_300 conda-forge
pytorch 2.3.0 cuda118_py312h3690e1b_301 conda-forge
pytorch 2.3.0 cuda118_py312h4faf3bd_300 conda-forge
pytorch 2.3.0 cuda118_py38h25d1429_300 conda-forge
pytorch 2.3.0 cuda118_py38h32d93a2_301 conda-forge
pytorch 2.3.0 cuda118_py39hbf661d7_301 conda-forge
pytorch 2.3.0 cuda118_py39hd44be3b_300 conda-forge
pytorch 2.3.0 cuda120_py310h2c91c31_301 conda-forge
pytorch 2.3.0 cuda120_py310h7891b24_300 conda-forge
pytorch 2.3.0 cuda120_py311h2667f23_300 conda-forge
pytorch 2.3.0 cuda120_py311hf6aebf0_301 conda-forge
pytorch 2.3.0 cuda120_py312h26b3cf7_301 conda-forge
pytorch 2.3.0 cuda120_py312hf9a1e0a_300 conda-forge
pytorch 2.3.0 cuda120_py38hc4689d7_301 conda-forge
pytorch 2.3.0 cuda120_py38heb61fd4_300 conda-forge
pytorch 2.3.0 cuda120_py39h17b67e0_301 conda-forge
pytorch 2.3.0 cuda120_py39h365aa7c_300 conda-forge
pytorch 2.3.0 gpu_cuda118py310h15c2a99_100 pkgs/main
pytorch 2.3.0 gpu_cuda118py310h7338b40_100 pkgs/main
pytorch 2.3.0 gpu_cuda118py310h796af20_101 pkgs/main
pytorch 2.3.0 gpu_cuda118py310hb74dfbf_101 pkgs/main
pytorch 2.3.0 gpu_cuda118py311h3118142_101 pkgs/main
pytorch 2.3.0 gpu_cuda118py311h3911fe7_101 pkgs/main
pytorch 2.3.0 gpu_cuda118py311h6b76543_100 pkgs/main
pytorch 2.3.0 gpu_cuda118py311hd2d20a8_100 pkgs/main
pytorch 2.3.0 gpu_cuda118py38h15c2a99_100 pkgs/main
pytorch 2.3.0 gpu_cuda118py38h7338b40_100 pkgs/main
pytorch 2.3.0 gpu_cuda118py38h796af20_101 pkgs/main
pytorch 2.3.0 gpu_cuda118py38hb74dfbf_101 pkgs/main
pytorch 2.3.0 gpu_cuda118py39h15c2a99_100 pkgs/main
pytorch 2.3.0 gpu_cuda118py39h7338b40_100 pkgs/main
pytorch 2.3.0 gpu_cuda118py39h796af20_101 pkgs/main
pytorch 2.3.0 gpu_cuda118py39hb74dfbf_101 pkgs/main
pytorch 2.3.0 py3.10_cpu_0 pytorch
pytorch 2.3.0 py3.10_cuda11.8_cudnn8.7.0_0 pytorch
pytorch 2.3.0 py3.10_cuda12.1_cudnn8.9.2_0 pytorch
pytorch 2.3.0 py3.11_cpu_0 pytorch
pytorch 2.3.0 py3.11_cuda11.8_cudnn8.7.0_0 pytorch
pytorch 2.3.0 py3.11_cuda12.1_cudnn8.9.2_0 pytorch
pytorch 2.3.0 py3.12_cpu_0 pytorch
pytorch 2.3.0 py3.12_cuda11.8_cudnn8.7.0_0 pytorch
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pytorch 2.5.1 cuda120_py313h869cad7_303 conda-forge
pytorch 2.5.1 cuda120_py39h2e0a0f3_300 conda-forge
pytorch 2.5.1 cuda120_py39h2e0a0f3_302 conda-forge
pytorch 2.5.1 cuda120_py39hfb32a81_303 conda-forge
pytorch 2.5.1 cuda126_py310h4acf282_301 conda-forge
pytorch 2.5.1 cuda126_py310h4acf282_302 conda-forge
pytorch 2.5.1 cuda126_py310he4c8055_303 conda-forge
pytorch 2.5.1 cuda126_py311h8adc4d4_301 conda-forge
pytorch 2.5.1 cuda126_py311h8adc4d4_302 conda-forge
pytorch 2.5.1 cuda126_py311hd4abd4e_303 conda-forge
pytorch 2.5.1 cuda126_py312h7c58cdf_303 conda-forge
pytorch 2.5.1 cuda126_py312hb0dc81f_301 conda-forge
pytorch 2.5.1 cuda126_py312hb0dc81f_302 conda-forge
pytorch 2.5.1 cuda126_py313ha14af55_301 conda-forge
pytorch 2.5.1 cuda126_py313ha14af55_302 conda-forge
pytorch 2.5.1 cuda126_py313he9a4f5b_303 conda-forge
pytorch 2.5.1 cuda126_py39h07e2c9a_303 conda-forge
pytorch 2.5.1 cuda126_py39hfe5c751_301 conda-forge
pytorch 2.5.1 cuda126_py39hfe5c751_302 conda-forge
pytorch 2.5.1 py3.10_cpu_0 pytorch
pytorch 2.5.1 py3.10_cuda11.8_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.10_cuda12.1_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.10_cuda12.4_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.11_cpu_0 pytorch
pytorch 2.5.1 py3.11_cuda11.8_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.11_cuda12.1_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.11_cuda12.4_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.12_cpu_0 pytorch
pytorch 2.5.1 py3.12_cuda11.8_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.12_cuda12.1_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.12_cuda12.4_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.9_cpu_0 pytorch
pytorch 2.5.1 py3.9_cuda11.8_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.9_cuda12.1_cudnn9.1.0_0 pytorch
pytorch 2.5.1 py3.9_cuda12.4_cudnn9.1.0_0 pytorch （2）因为本地安装的cuda是12.5，并且作者命令中使用了python3.8，所以根据上面的版本号与对应关系，找一个能满足这两个条件的pytorch版本直接install即可，在安装的过程中，也会自动安装好pytorch需要的几个cuda包
(base) lee@lee-System-Product-Name:~/project/PhotoRegCodes$ conda create -n photoreg pytorch=2.4.1=py3.8_cuda12.4_cudnn9.1.0_0 torchvision torchaudio -c pytorch -c nvidia
Channels:- pytorch- nvidia- conda-forge- http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free- defaults
Platform: linux-64
Collecting package metadata (repodata.json): - Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /pkgs/r/noarch/repodata.json.zst\ Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /nvidia/noarch/repodata.json.zstRetrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /conda-forge/linux-64/repodata.json.zst/ Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /conda-forge/noarch/repodata.json.zst| Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /conda-forge/linux-64/repodata.json.zst/ Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /nvidia/noarch/repodata.json.zstRetrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /conda-forge/noarch/repodata.json.zst- Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /pkgs/r/noarch/repodata.json.zst\ Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /pkgs/r/noarch/repodata.json.zst| Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /conda-forge/noarch/repodata.json.zstRetrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'RemoteDisconnected('Remote end closed connection without response')': /conda-forge/linux-64/repodata.json.zstfailedProxyError: Conda cannot proceed due to an error in your proxy configuration.
Check for typos and other configuration errors in any '.netrc' file in your home directory,
any environment variables ending in '_PROXY', and any other system-wide proxy
configuration settings.然后发现网络问题一直安装不了，于是添加设置国内的几个源
（3）conda设置国内的源
conda添加清华镜像源_conda配置清华镜像源-CSDN博客
最后完成pytorch与附带的几个cuda包的安装，像一些重复的包就没必要安装进去，比如cuda编译器，如果在conda环境下找不到，它就会自动使用全局也就是系统的cuda编译器来完成编译。
2.QObject::moveToThread: Current thread(...) is not the object`s thread. Cannot move to target thread(
在跑photoreg的时候，报这个错，网上的说法是conda中的pyqt库与pip的opencv库冲突了，有三种方法尝试解决：
QObject::moveToThread: Current thread(...) is not the object`s thread. Cannot move to target thread(_qobject::movetothread: current thread (0x17a7040) -CSDN博客
查看了我的opencv版本是4.10，但是我的电脑使用上面的方法没有用，所以就直接降级，一路降到了4.2的版本才正常！
3.ERROR: Exception in ASGI application
在部署好triposr运行python gradio_app.py的时候，报错
(triposr) lee@lee-System-Product-Name:~/project/TripoSR$ python gradio_app.py
/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/numba/np/ufunc/parallel.py:371: NumbaWarning: The TBB threading layer requires TBB version 2021 update 6 or later i.e., TBB_INTERFACE_VERSION >= 12060. Found TBB_INTERFACE_VERSION = 12050. The TBB threading layer is disabled.warnings.warn(problem)
/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/transformers/utils/generic.py:441: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead._torch_pytree._register_pytree_node(
/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/transformers/utils/generic.py:309: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead._torch_pytree._register_pytree_node(
Running on local URL: http://127.0.0.1:7860To create a public link, set `share=True` in `launch()`.
IMPORTANT: You are using gradio version 4.8.0, however version 4.44.1 is available, please upgrade.
--------
ERROR: Exception in ASGI application
Traceback (most recent call last):File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/type_adapter.py", line 270, in _init_core_attrsself._core_schema = _getattr_no_parents(self._type, '__pydantic_core_schema__')File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/type_adapter.py", line 112, in _getattr_no_parentsraise AttributeError(attribute)
AttributeError: __pydantic_core_schema__During handling of the above exception, another exception occurred:Traceback (most recent call last):File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/uvicorn/protocols/http/h11_impl.py", line 406, in run_asgiresult = await app( # type: ignore[func-returns-value]File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/uvicorn/middleware/proxy_headers.py", line 60, in __call__return await self.app(scope, receive, send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/fastapi/applications.py", line 1054, in __call__await super().__call__(scope, receive, send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/applications.py", line 113, in __call__await self.middleware_stack(scope, receive, send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/middleware/errors.py", line 187, in __call__raise excFile "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/middleware/errors.py", line 165, in __call__await self.app(scope, receive, _send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/middleware/cors.py", line 93, in __call__await self.simple_response(scope, receive, send, request_headers=headers)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/middleware/cors.py", line 144, in simple_responseawait self.app(scope, receive, send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/middleware/exceptions.py", line 62, in __call__await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/_exception_handler.py", line 53, in wrapped_appraise excFile "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/_exception_handler.py", line 42, in wrapped_appawait app(scope, receive, sender)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/routing.py", line 715, in __call__await self.middleware_stack(scope, receive, send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/routing.py", line 735, in appawait route.handle(scope, receive, send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/routing.py", line 288, in handleawait self.app(scope, receive, send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/routing.py", line 76, in appawait wrap_app_handling_exceptions(app, request)(scope, receive, send)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/_exception_handler.py", line 53, in wrapped_appraise excFile "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/_exception_handler.py", line 42, in wrapped_appawait app(scope, receive, sender)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/starlette/routing.py", line 73, in appresponse = await f(request)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/fastapi/routing.py", line 291, in appsolved_result = await solve_dependencies(File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/fastapi/dependencies/utils.py", line 666, in solve_dependencies) = await request_body_to_args( # body_params checked aboveFile "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/fastapi/dependencies/utils.py", line 891, in request_body_to_argsfields_to_extract = get_cached_model_fields(first_field.type_)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/fastapi/_compat.py", line 659, in get_cached_model_fieldsreturn get_model_fields(model)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/fastapi/_compat.py", line 285, in get_model_fieldsreturn [File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/fastapi/_compat.py", line 286, in <listcomp>ModelField(field_info=field_info, name=name)File "<string>", line 6, in __init__File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/fastapi/_compat.py", line 111, in __post_init__self._type_adapter: TypeAdapter[Any] = TypeAdapter(File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/type_adapter.py", line 257, in __init__self._init_core_attrs(rebuild_mocks=False)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/type_adapter.py", line 135, in wrappedreturn func(self, *args, **kwargs)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/type_adapter.py", line 277, in _init_core_attrsself._core_schema = _get_schema(self._type, config_wrapper, parent_depth=self._parent_depth)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/type_adapter.py", line 95, in _get_schemaschema = gen.generate_schema(type_)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 655, in generate_schemaschema = self._generate_schema_inner(obj)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 908, in _generate_schema_innerreturn self._annotated_schema(obj)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 2028, in _annotated_schemaschema = self._apply_annotations(source_type, annotations)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 2107, in _apply_annotationsschema = get_inner_schema(source_type)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_schema_generation_shared.py", line 83, in __call__schema = self._handler(source_type)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 2189, in new_handlerschema = metadata_get_schema(source, get_inner_schema)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 2185, in <lambda>lambda source, handler: handler(source)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_schema_generation_shared.py", line 83, in __call__schema = self._handler(source_type)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 2088, in inner_handlerschema = self._generate_schema_inner(obj)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 929, in _generate_schema_innerreturn self.match_type(obj)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 1029, in match_typereturn self._match_generic_type(obj, origin)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 1058, in _match_generic_typereturn self._union_schema(obj)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 1378, in _union_schemachoices.append(self.generate_schema(arg))File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 655, in generate_schemaschema = self._generate_schema_inner(obj)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 929, in _generate_schema_innerreturn self.match_type(obj)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 1038, in match_typereturn self._unknown_type_schema(obj)File "/home/lee/miniconda3/envs/triposr/lib/python3.10/site-packages/pydantic/_internal/_generate_schema.py", line 558, in _unknown_type_schemaraise PydanticSchemaGenerationError(
pydantic.errors.PydanticSchemaGenerationError: Unable to generate pydantic-core schema for <class 'starlette.requests.Request'>. Set `arbitrary_types_allowed=True` in the model_config to ignore this error or implement `__get_pydantic_core_schema__` on your type to fully support it.If you got this error by calling handler(<some type>) within `__get_pydantic_core_schema__` then you likely need to call `handler.generate_schema(<some type>)` since we do not call `__get_pydantic_core_schema__` on `<some type>` otherwise to avoid infinite recursion.这是由于gradio版本与pydantic版本不匹配导致的错误。
升级合适的版本即可解决，需要尝试多次
我查看了requirements.txt，因为作者推荐的python版本是>3.8，而我的是3.10，所有只升级gradio会因为其他库版本低而冲突，
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
tokenizers 0.14.1 requires huggingface_hub<0.18,>=0.16.4, but you have huggingface-hub 0.26.2 which is incompatible.ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
gradio 4.43.0 requires huggingface-hub>=0.19.3, but you have huggingface-hub 0.17.0 which is incompatible.
gradio-client 1.3.0 requires huggingface-hub>=0.19.3, but you have huggingface-hub 0.17.0 which is incompatible.ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
tokenizers 0.14.1 requires huggingface_hub<0.18,>=0.16.4, but you have huggingface-hub 0.26.2 which is incompatible.
so，我的解决办法是一键直接把当前的库全部升级，让pip去解决版本关系的问题:
pip install --upgrade -r requirements.txt 然后就行了不报错了
三、python代码bug
1.文件中的图片损坏，OSError: image file is truncated (7 bytes not processed)
【Bug解决】OSError: image file is truncated (7 bytes not processed)-CSDN博客
这位博主还写了检测图片是否有损坏的脚本，非常有用！
2.RuntimeError: PytorchStreamReader failed reading zip archive: failed finding central directory
在运行photoreg代码的时候报这个错，原因是要加载的预训练权重文件损坏或者不完整，另外代码中前面使用torch.hub.load（）下载过dino v2的模型，但是中间可能断了，所以，需要找到下载的缓存路径删除已下载的部分，重新下载
model = torch.hub.load('facebookresearch/dinov2', 'dinov2_vits14')缓存路径可以询问GTP：
四、软件使用
1.meshlab使用经验
MeshLab使用经验_meshlab背景颜色-CSDN博客
