text:
Why this problem?

python -m pip install -e thirdparty/diff-gaussian-rasterization-w-pose/
Looking in indexes: https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
Obtaining file:///data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose
Preparing metadata (setup.py) ... done
Installing collected packages: diff_gaussian_rasterization
DEPRECATION: Legacy editable install of diff_gaussian_rasterization==0.0.0 from file:///data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose (setup.py develop) is deprecated. pip 25.0 will enforce this behaviour change. A possible replacement is to add a pyproject.toml or enable --use-pep517, and use setuptools >= 64. If the resulting installation is not behaving as expected, try using --config-settings editable_mode=compat. Please consult the setuptools documentation for more information. Discussion can be found at https://github.com/pypa/pip/issues/11457
Running setup.py develop for diff_gaussian_rasterization
error: subprocess-exited-with-error
× python setup.py develop did not run successfully.
│ exit code: 1
╰─> [115 lines of output]
    running develop
    /data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/develop.py:41: EasyInstallDeprecationWarning: easy_install command is deprecated.
    !!

            ********************************************************************************
            Please avoid running ``setup.py`` and ``easy_install``.
            Instead, use pypa/build, pypa/installer or other
            standards-based tools.

            See https://github.com/pypa/setuptools/issues/917 for details.
            ********************************************************************************

    !!
      easy_install.initialize_options(self)
    /data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.
    !!

            ********************************************************************************
            Please avoid running ``setup.py`` directly.
            Instead, use pypa/build, pypa/installer or other
            standards-based tools.

            See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
            ********************************************************************************

    !!
      self.initialize_options()
    running egg_info
    writing diff_gaussian_rasterization.egg-info/PKG-INFO
    writing dependency_links to diff_gaussian_rasterization.egg-info/dependency_links.txt
    writing top-level names to diff_gaussian_rasterization.egg-info/top_level.txt
    reading manifest file 'diff_gaussian_rasterization.egg-info/SOURCES.txt'
    adding license file 'LICENSE.md'
    writing manifest file 'diff_gaussian_rasterization.egg-info/SOURCES.txt'
    running build_ext
    /data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py:416: UserWarning: The detected CUDA version (11.7) has a minor version mismatch with the version that was used to compile PyTorch (11.8). Most likely this shouldn't be a problem.
      warnings.warn(CUDA_MISMATCH_WARN.format(cuda_str_version, torch.version.cuda))
    building 'diff_gaussian_rasterization._C' extension
    Emitting ninja build file /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/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)
    [1/4] /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/backward.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
    FAILED: /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.o
    /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/backward.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
    nvcc fatal   : Unsupported gpu architecture 'compute_89'
    [2/4] /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/forward.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
    FAILED: /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.o
    /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/forward.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
    nvcc fatal   : Unsupported gpu architecture 'compute_89'
    [3/4] /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/rasterizer_impl.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
    FAILED: /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.o
    /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/rasterizer_impl.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
    nvcc fatal   : Unsupported gpu architecture 'compute_89'
    [4/4] /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/rasterize_points.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
    FAILED: /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.o
    /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/rasterize_points.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
    nvcc fatal   : Unsupported gpu architecture 'compute_89'
    ninja: build stopped: subcommand failed.
    Traceback (most recent call last):
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 2104, in _run_ninja_build
        subprocess.run(
      File "/data/miniconda3/envs/splatSLAM/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 34, in <module>
      File "/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/setup.py", line 17, in <module>
        setup(
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/__init__.py", line 117, in setup
        return distutils.core.setup(**attrs)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 183, in setup
        return run_commands(dist)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 199, in run_commands
        dist.run_commands()
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 954, in run_commands
        self.run_command(cmd)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/dist.py", line 950, in run_command
        super().run_command(command)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 973, in run_command
        cmd_obj.run()
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/develop.py", line 35, in run
        self.install_for_development()
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/develop.py", line 112, in install_for_development
        self.run_command('build_ext')
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 316, in run_command
        self.distribution.run_command(command)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/dist.py", line 950, in run_command
        super().run_command(command)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 973, in run_command
        cmd_obj.run()
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 98, in run
        _build_ext.run(self)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 359, in run
        self.build_extensions()
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 868, in build_extensions
        build_ext.build_extensions(self)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 476, in build_extensions
        self._build_extensions_serial()
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 502, in _build_extensions_serial
        self.build_extension(ext)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 263, in build_extension
        _build_ext.build_extension(self, ext)
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 557, in build_extension
        objects = self.compiler.compile(
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 681, in unix_wrap_ninja_compile
        _write_ninja_file_and_compile_objects(
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 1784, in _write_ninja_file_and_compile_objects
        _run_ninja_build(
      File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 2120, in _run_ninja_build
        raise RuntimeError(message) from e
    RuntimeError: Error compiling objects for extension
    [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.

error: subprocess-exited-with-error
× python setup.py develop did not run successfully.
│ exit code: 1
╰─> [115 lines of output]
running develop
/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/develop.py:41: EasyInstallDeprecationWarning: easy_install command is deprecated.
!!
        ********************************************************************************
        Please avoid running ``setup.py`` and ``easy_install``.
        Instead, use pypa/build, pypa/installer or other
        standards-based tools.

        See https://github.com/pypa/setuptools/issues/917 for details.
        ********************************************************************************

!!
  easy_install.initialize_options(self)
/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.
!!

        ********************************************************************************
        Please avoid running ``setup.py`` directly.
        Instead, use pypa/build, pypa/installer or other
        standards-based tools.

        See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
        ********************************************************************************

!!
  self.initialize_options()
running egg_info
writing diff_gaussian_rasterization.egg-info/PKG-INFO
writing dependency_links to diff_gaussian_rasterization.egg-info/dependency_links.txt
writing top-level names to diff_gaussian_rasterization.egg-info/top_level.txt
reading manifest file 'diff_gaussian_rasterization.egg-info/SOURCES.txt'
adding license file 'LICENSE.md'
writing manifest file 'diff_gaussian_rasterization.egg-info/SOURCES.txt'
running build_ext
/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py:416: UserWarning: The detected CUDA version (11.7) has a minor version mismatch with the version that was used to compile PyTorch (11.8). Most likely this shouldn't be a problem.
  warnings.warn(CUDA_MISMATCH_WARN.format(cuda_str_version, torch.version.cuda))
building 'diff_gaussian_rasterization._C' extension
Emitting ninja build file /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/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)
[1/4] /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/backward.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
FAILED: /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.o
/data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/backward.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/backward.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
nvcc fatal   : Unsupported gpu architecture 'compute_89'
[2/4] /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/forward.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
FAILED: /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.o
/data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/forward.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/forward.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
nvcc fatal   : Unsupported gpu architecture 'compute_89'
[3/4] /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/rasterizer_impl.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
FAILED: /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.o
/data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/cuda_rasterizer/rasterizer_impl.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/cuda_rasterizer/rasterizer_impl.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
nvcc fatal   : Unsupported gpu architecture 'compute_89'
[4/4] /data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/rasterize_points.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
FAILED: /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.o
/data/miniconda3/envs/splatSLAM/bin/nvcc --generate-dependencies-with-compile --dependency-output /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.o.d -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/TH -I/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/include/THC -I/data/miniconda3/envs/splatSLAM/include -I/data/miniconda3/envs/splatSLAM/include/python3.10 -c -c /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/rasterize_points.cu -o /data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/build/temp.linux-x86_64-cpython-310/rasterize_points.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'"'"'' -I/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/third_party/glm/ -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=sm_89 -std=c++17
nvcc fatal   : Unsupported gpu architecture 'compute_89'
ninja: build stopped: subcommand failed.
Traceback (most recent call last):
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 2104, in _run_ninja_build
    subprocess.run(
  File "/data/miniconda3/envs/splatSLAM/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 34, in <module>
  File "/data/weiboren/code/SplatSLAM/thirdparty/diff-gaussian-rasterization-w-pose/setup.py", line 17, in <module>
    setup(
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/__init__.py", line 117, in setup
    return distutils.core.setup(**attrs)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 183, in setup
    return run_commands(dist)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 199, in run_commands
    dist.run_commands()
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 954, in run_commands
    self.run_command(cmd)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/dist.py", line 950, in run_command
    super().run_command(command)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 973, in run_command
    cmd_obj.run()
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/develop.py", line 35, in run
    self.install_for_development()
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/develop.py", line 112, in install_for_development
    self.run_command('build_ext')
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 316, in run_command
    self.distribution.run_command(command)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/dist.py", line 950, in run_command
    super().run_command(command)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 973, in run_command
    cmd_obj.run()
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 98, in run
    _build_ext.run(self)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 359, in run
    self.build_extensions()
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 868, in build_extensions
    build_ext.build_extensions(self)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 476, in build_extensions
    self._build_extensions_serial()
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 502, in _build_extensions_serial
    self.build_extension(ext)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 263, in build_extension
    _build_ext.build_extension(self, ext)
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 557, in build_extension
    objects = self.compiler.compile(
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 681, in unix_wrap_ninja_compile
    _write_ninja_file_and_compile_objects(
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 1784, in _write_ninja_file_and_compile_objects
    _run_ninja_build(
  File "/data/miniconda3/envs/splatSLAM/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 2120, in _run_ninja_build
    raise RuntimeError(message) from e
RuntimeError: Error compiling objects for extension
[end of output]

The cudatoolkit-dev 11.7 doesn't support the 4090.
That's what nvcc fatal   : Unsupported gpu architecture 'compute_89' suggests at least.
I recommend you remove it and try to install the regular cuda-toolkit 11.8 with
conda install nvidia/label/cuda-11.8.0::cuda-toolkit
Most likely there will be libraries missing. You can look them up here and install the ones required.
Good Luck

Sorry for the late reply. Our codebase was tested with CUDA 11.3 and CUDA 11.7 but no newer version. Hopefully it should still work.

Thank you very much

The cudatoolkit-dev 11.7 doesn't support the 4090. That's what nvcc fatal : Unsupported gpu architecture 'compute_89' suggests. I recommend you remove it and try to install the regular cuda-toolkit 11.8 with conda install nvidia/label/cuda-11.8.0::cuda-toolkit Most likely there will be libraries missing. You can look them up here and install the ones required. cuDNN is available here. Good Luck

yes I solve this problem by your solution

CUDA 11.8 is also OK

Great! Closing the issue.

authors: TFArkS YUBO427 eriksandstroem

repo: google-research/Splat-SLAM


text:
Wiki Chinese dump preprocessing: #lines not matching

The BERT Chinese model was trained from wikipedia dump. According to #155 , BERT original model got 25M lines/sentences after pre-processing.
However,  I got 12.5M lines(sentences) after pre-processing.  Can someone let me know what could be wrong with my steps?
What I did:

download https://dumps.wikimedia.org/zhwiki/latest/zhwiki-latest-pages-articles.xml.bz2
use  WikiExtractor.py to extract the paragraphs. I got total 14.7M lines.
use a script to split the paragraphs into sentences. Ignore empty lines in wiki extracts. Add new line for wiki  only. I got total 12.5M lines.

I found the reason for my issue. I need to include both simplified and traditional Chinese versions. That'll be totally 25M.

The BERT Chinese model was trained from wikipedia dump. According to #155 , BERT original model got 25M lines/sentences after pre-processing.
However, I got 12.5M lines(sentences) after pre-processing. Can someone let me know what could be wrong with my steps?
What I did:

download https://dumps.wikimedia.org/zhwiki/latest/zhwiki-latest-pages-articles.xml.bz2
use  WikiExtractor.py to extract the paragraphs. I got total 14.7M lines.
use a script to split the paragraphs into sentences. Ignore empty lines in wiki extracts. Add new line for wiki  only. I got total 12.5M lines.

Hey @LiweiPeng,
I am not sure where to get the simplified Chinese version of Wikipedia.
I can't find the code (like zh) for simplified Chinese, or do I need to use an automatic converter?
Victor

@VictorSanh I used the opencc tool (https://github.com/BYVoid/OpenCC) to convert all wikipedia Chinese text into simplified Chinese version and traditional Chinese version. Then use BERT to train both versions together.
I did other tests where only simplified Chinese wiki are used. The results are not as good as using both simplified and traditional for XNLI dataset.

Thank you @LiweiPeng for you answer!
Just to make sure, which config files (the json files) are you calling? t2s.json?
Did you use the Taiwan standard?

t2s json to convert to simplified Chinese. s2t.json to convert to traditional Chinese.

So you are applying t2s.json to the output of wikiextractor to get the simplified Chinese version and then reapply s2t.json to the latter to get the traditional Chinese version (i.e. two steps process)?

her tests where only simplified Chinese wiki are us

Hi, this method works for me, thanks! But I have a few questions. Did you split tfrecord
into train and test?
Here is what I did after generating simplified and traditional chinese text files:

concate two txt files using "cat simplified.txt traditional.txt > all.txt"
generate tf record files using

python create_pretraining_data.py \
  --input_file=data/download/wikicorpus_zh/all.txt \
  --output_file=data/download/wikicorpus_zh/all.tfrecord \
  --vocab_file=data/download/google_pretrained_weights/chinese_L-12_H-768_A-12/vocab.txt \
  --do_lower_case=True \
  --max_seq_length=128 \
  --max_predictions_per_seq=20 \
  --masked_lm_prob=0.15 \
  --random_seed=12345 \
  --dupe_factor=5

In this way, I could train using all.tfrecord as training set. However, no test or eval set is generated. May I ask, how did you split zhwiki into different sets? Thank you!

source: gharchive/issue

authors: LiweiPeng VictorSanh notabigfish

repo: google-research/bert

license_type: permissive

license_source: github-api


text:
How to read the causal-label?

Issue Description:
Hi, thanks for your amazing work! I'm encountering an issue while parsing TFRecord files using TensorFlow. I'm unable to parse the data within them, and I'm getting the following error message:
Error Message:
2023-09-08 15:07:54.635147: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at example_parsing_ops.cc:94: INVALID_ARGUMENT: Could not parse example input, value: '
...
InvalidArgumentError: {{function_node _wrapped__ParseExampleV2_Tdense_0_num_sparse_2_ragged_split_types_0_ragged_value_types_0_sparse_types_2_device/job:localhost/replica:0/task:0/device:CPU:0}} Could not parse example input, value: '
Specifications:

TensorFlow Version: 2.0.0
Operating System: Ubuntu 20.04

Background:
I'm encountering an issue while attempting to parse TFRecord files using TensorFlow. The error message suggests a problem with parsing the example input.
Issue Details:
I've defined the dataset description, including variable-length features (VarLenFeature), but it seems there's an issue during parsing. Here's a code snippet:
filename = "causal_labels.tfrecord"
dataset = tf.data.TFRecordDataset(filename, compression_type='')
data = next(dataset.as_numpy_iterator())

features_description = {}
causal_features = {
    'scenario_id': tf.io.VarLenFeature(tf.string),
    'labeler_results': tf.io.VarLenFeature(tf.string),
}

features_description.update(causal_features)
parsed = tf.io.parse_single_example(data, features_description)

Expected Outcome:
I hope to successfully parse the data within the TFRecord file for further data processing and analysis.
Please help me identify the cause of the parsing issue and how to resolve it. Thank you for your assistance!

Great , I have solved this problem.

Hi! Could you please give me some ideas on how you solved the problem? I am encountering the same problem.

I resolved this by using the proto file. Thanks.

I also encountered the same problem. How did you solve it in the end? Could you share the code?

repo: google-research/causal-agents

license_source: bigquery


text:
Support LEF/DEF

Please add a comment if you need/want LEF/DEF support so we can prioritize asks.

There's a python API for openDB that supports LEF and DEF writing.

@tfboyd I work inside Google (ethanmoon@) as well on open source hardware EDA tools. Would love to discuss how to integrate this into some of our work.

@tfboyd We are a hardware security research group at University of Florida. We need LEF/DEF support to utilize CircuitTraining for our research.

@tfboyd I am doing research into floorplan, I need LEF/DEF support to validate the CircuitTraining on other open source datasets.

We are having a similar issue internally.  I realize that sounds absurd.  Our current process exports from another tool and is never reading LEF/DEF.  I wish I had an ETA. We currently do not have a person assigned. I do appreciate this ping because it helps me try in increase the priority even higher.
I am linking this entire thread into our weekly sync.

We are having a similar issue internally. I realize that sounds absurd. Our current process exports from another tool and is never reading LEF/DEF. I wish I had an ETA. We currently do not have a person assigned. I do appreciate this ping because it helps me try in increase the priority even higher.
I am linking this entire thread into our weekly sync.

Hi author,
Do you have any update ? I implemented the LEF/DEF extractor in python.
So far , the extractor realized in two steps: 1. Extract macros , std cells, pins and generate hypergraph data format for hmetis input. 2. Collect macros , clusters and pins and generate initial.plc and netlist.pb.txt
But I don't know how to define the “x” and "y"  of the cluster and the "weight" of the input. Could you offer a simple dataset to verify the extractor? Thanks

Hi everyone,
This is a repo (https://github.com/TILOS-AI-Institute/MacroPlacement/tree/main/CodeElements) discussed the details about the the "x" and "y" of the cluster.  They also provide the LEF/DEF translators.

@ZhiangWang033, thanks for sharing it.

We have added the grouping (clustering) code. This does require the netlist to already by in the protobuff structure which is documented here.  We are working with the third-party vendor to allow us to release the tcl script we use to export from the tool we use internally to the protobuf. That discussion is taking longer than expected. We do not directly use LEF/DEF internally for this flow or we would have open sourced that path already.

@ZhiangWang033 or @thesukantadey  did you successfully run the LEF/DEF translators?
The code seems stale.

It was a long time coming and a big thank you to TILOS-AI-Institute.
TILOS-AI-Institute has created a script to convert LEF/DEF and Bookshelf to the Netlist Protocol Buffer used as the input for circuit training.

authors: QuantamHD Yangxiaojun1230 ZhiangWang033 braamBeresford tfboyd thesukantadey


text:
Feature request: compare with IFS at higher spatial resolution of 0.1deg

In renewables forecasting, we care about wind speed, solar irradiation at the location of single wind/solar parks. ECMWF IFS with its 0.1deg resolution gives us good forecast performance, but anything at 0.25deg or less like GFS is far behind.
It would help us a lot if a comparison to ECMWF IFS can be done at the IFS' "native"* resolution of 0.1 lon/lat degrees. The other models can be bilinearly interpolated to match this grid. This would allow us to keep track of these AI models to see "are they useful for renewables forecasting yet".
*The IFS of course has a reduced Gaussian grid so technically the resolution is not really a regular grid of 0.1deg, but practically that's the highest level of detail you get.

Hey, that is a great point. We do have the raw high-res IFS HRES data but haven't converted it to Zarr yet. This has already been on my to do list for a while. I can't promise though when I will get to it, so stay tuned for now

Just chiming in that we'd be quite interested in this too! Both for the renewable forecasting case, and since ML forecasting models are now coming out forecasting at the higher resolution, primarily FengWu GHR which seems to forecast on the higher resolution grid.

We are currently discussing the best strategy to regrid the data :) But could be a few months before we share it publicly.

authors: The-Fonz jacobbieker raspstephan


text:
How Get Other Users of my website registration id

Hello
Please let me know how I can get other user of my website registration id to send push notifications.
please help me.
Regards,
Jaswant

Hey @Jaswant0039 I suggest posting this question to http://stackoverflow.com/questions/tagged/progressive-web-apps

repo: google/WebFundamentals


text:
Google Home App

I want to use Google Home App to Setup AIY my Voice Kit,But I can not do because it says that device was turned off. And it  says that my voice kit is a light.

You can't use the Google Home app to set it up, I think. You have to follow the instructions on the AIY website.

repo: google/aiyprojects-raspbian


text:
Adding benchmark to run as instrumentation tests for builds

IMPORTANT: All PRs must be linked to an issue (except for extremely trivial and straightforward changes).
Description
Added benchmark module to run as instrumentation test on FTL
Alternative(s) considered
Have you considered any alternatives? And if so, why have you chosen the approach in this PR?
NA
Type
Choose one: (Builds)
Screenshots (if applicable)
Checklist

[x] I have read and acknowledged the Code of conduct.
[x] I have read the Contributing page.
[x] I have signed the Google Individual CLA, or I am covered by my company's Corporate CLA.
[x] I have discussed my proposed solution with code owners in the linked issue(s) and we have agreed upon the general approach.
[x] I have run ./gradlew spotlessApply and ./gradlew spotlessCheck to check my code follows the style guide of this project.
[x] I have run ./gradlew check and ./gradlew connectedCheck to test my changes locally.
[x] I have built and run the demo app(s) to verify my change fixes the issue and/or does not break the demo app(s).

@anchita-g can you resolve conflicts after your last PR got merged?

source: gharchive/pull-request

repo: google/android-fhir


text:
Closes #705: Add a function to enable overriding document IDs

Add a function DesignDocOverride(id) that can be used to override the document ID used by any child/descendent generated DesignCompose functions. DesignDocOverride internally just uses a CompositionLocalProvider to provide the document ID, which is checked and used in the DesignDocInternal function.
Add a HelloBye example that uses this function to change the document ID.

I agree it would be good to comment the limitations and annotate the API appropriately, as Tim suggests.

repo: google/automotive-design-compose


text:
Move Mozilla sites to their own ports

Since the Mozilla sites use a specific combination of protocols, they should probably be moved to their own ports, just like the TLS 1.x and SSL x.0 sites.

Hmm, we can drop connections with the wrong domain using SNI on intermediate and modern.
I would be okay with this, but we should fix #184 first (or find it to be infeasible).

authors: lgarron marumari


text:
"Scorecard supply-chain security" GitHub CI action has been consistently failing

Example: https://github.com/google/closure-compiler/actions/runs/9704666554/job/26785314354
Error: Unable to resolve action `ossf/scorecard-action@v2`, unable to find version `v2`

Not a meaningful fix, but the misconfigured action is at least turned off as of https://github.com/google/closure-compiler/pull/4176, allowing us to see when the build breaks.

authors: blickly lauraharker

repo: google/closure-compiler


text:
Prevent NO_TRANSPILE being set as input language

The #setLanguage(LanguageMode) method has a check that NO_TRANSPILE is not set as input language, but it checked the instance variable instead of checking the method parameter.

Nice catch, thanks!

authors: blickly oxc


text:
goog.async.Deferred sometimes does not throw unhandled errors

This issue was imported from Closure Library's previous home at http://closure-library.googlecode.com
The link to the original issue is:
https://code.google.com/p/closure-library/issues/detail?id=632

Can't repro. This works in this test case:
https://jsfiddle.net/c2c6zvrk/2/

authors: joeltine nanaze

repo: google/closure-library


text:
Constructive geometry

Additional operations should be added to combine shapes:
intersection :: [Picture] -> Picture
difference :: Picture -> Picture -> Picture

(Names are debatable.)  intersection should produce a picture bounded by the intersection of the list.  The second should produce a picture containing all areas of the first image that are not also in the second.  Note that together with the existing pictures, this gives the three basic operations for constructive geometry.
The implementation is a little tricky.  Combining two images in this way can be done with globalCompositeOperation (https://developer.mozilla.org/samples/canvas-tutorial/6_1_canvas_composite.html)  But getting the resulting shapes to nest correctly will involve using off-screen canvases as temporaries.  Since creating a new off-screen canvas is expensive, this should involve determining the minimum number of offscreen canvases needed, and reusing them between frames.

I really want to do this!
The big blocker isn't so much that the implementation is tricky, as that the semantics are unclear when computing the intersection, difference, or union of pictures with color and transparency.  In an ideal world, we'd have separated "Shape" from "Picture", and the former would have no concept of color or transparency.  But CodeWorld doesn't make that distinction, so we need a reasonable answer for union, intersection, and difference that incorporates color and transparency.  I also want to preserve the property that coloring a shape with full transparency makes it equivalent to blank, and I want to use pictures and & instead of a distinct union, to avoid adding too many similar functions.

I think there may be a synergy between this and #1397.  My theory on #1397 is that &, which is currently used to overlay images, is just too much like the English word.  One could imagine replacing it with a different operator.  I might choose |+| because it sort of looks like overlaying two images (from a side view).  That opens the door to |*| for intersection, and |-| for subtraction.
I think this definitely needs field testing before making a decision.  I'll have to see whether I can find a good setting for that field testing.

repo: google/codeworld


text:
Auto-save

Also, make it really obvious when you haven't saved yet.

Actually, we think you should just be prompted for a project name when you click New, so it's impossible to have an unsaved project.  That plus auto-save would solve the problem completely.

(Following up) Actually, the idea of never having a project that's unsaved is impossible.  You don't need to even be logged in to use CodeWorld.  You can also open other people's CodeWorld projects by sharing a URL with a hash, and whether or not you are logged in by cookies, we don't want to add an interstitial phase to prompt for a project name, nor automatically add the shared code to your account.
So here's the new proposal.

If you have an existing project open, it auto-saves.
If the code isn't an existing project, and the buffer is dirty, add an obvious warning sign.

Whether you're prompted to save a newly created project when you're logged in is an open question.  But you should be able to say "no".  I actually routinely open CodeWorld to hack at some quick idea that I don't want to save.  I've done it hundreds of times, and I don't want a hundred one-off test projects in my menu every time I log in.

I guess we can store something like buffers in local storage. We have some empty space down from project buttons.

Or better to call it drafts. This way we can have current buffer, which will save on switching to another buffer. It will silently update per time. It will not contain directories.
If one buffer going to be saved as full project with name - it will be deleted from drafts.
Maybe it is over complicated for users, because it yet another project type, one more UI thing and one more place for mess. Also not logged in users can use it as light replace of full projects tool.

I agree that this is too complicated for users.

authors: cdsmith nixorn


text:
Add another "." or "/"

Hi, im trying to redirect to websites as "https://es.wikipedia.org/wiki/Aguascalientes" but i cant add the "/Aguascalientes" how do i add "/"

Im refering this part to add the HTTPS and .com or .org but i cant add "/" or another dot
https://github.com/google/eddystone/blob/master/eddystone-url/README.md#eddystone-url-http-url-encoding

I use instead https://goo.gl/ sorry

repo: google/eddystone


text:
Fix: Update curly lint rule

Went with multi-line based on lighthouse's eslintrc rules.
mutli-line: allow brace-less single-line if, else if, else, for, while, or do
The alternative one would be,
multi: http://eslint.org/docs/rules/curly#multi

I think this rule doesn't quite fit because technically the JS style guide only allows single line if statements (i.e. it doesn't allow if (foo) foo++; else doSomething();.
Though maybe it's better to have something turned on here than not since I think it's not very common to do the example above.

Hmmm you are correct it doesn't but I also don't see a rule to accomplish this with the current eslint configuration.
I think it would be better than not having any rule on it. Is that the only case missed by this rule?

Yeah, I think it's better to have an overly permissive rule than nothing (since nothing is also not correct). What I don't want is something that will incorrectly error on technically valid code.
Can you update your changes to keep the comment and then I'll merge?

@philipwalton I re-added but inline with the new rule and capped the line at 80 chars

authors: philipwalton stramel

repo: google/eslint-config-google


text:
Triangle Tutorial is not working after changing to Filament v1.10.0

Describe the bug
Triangle Tutorial is not working after v1.10.0 is released.
This is probably due to the material breakage in Filament, as described in the release notes. I think it needs to be rebuilt.
To Reproduce
Steps to reproduce the behavior:

Go to Filament's Triangle Tutorial page
https://google.github.io/filament/webgl/tutorial_triangle.html

The following error is displayed on the console.
filament.js:9
in filament::MaterialParser *filament::createParser(filament::backend::Backend, const void *, size_t):69

filament.js:9
reason: Material version mismatch. Expected 11 but received 10.

filament.js:9
Uncaught (in promise) RuntimeError: abort(undefined). Build with -s ASSERTIONS=1 for more info.
    at abort (https://unpkg.com/filament/filament.js:9:10953)
    at _abort (https://unpkg.com/filament/filament.js:9:112511)
    at https://unpkg.com/filament@1.10.0/filament.wasm:wasm-function[243]:0x9bcb
    at https://unpkg.com/filament@1.10.0/filament.wasm:wasm-function[271]:0xcbd3
    at https://unpkg.com/filament@1.10.0/filament.wasm:wasm-function[1686]:0x1006cb
    at https://unpkg.com/filament@1.10.0/filament.wasm:wasm-function[1038]:0x980b7
    at Engine$_createMaterial [as _createMaterial] (eval at new_ (https://unpkg.com/filament/filament.js:9:90896), <anonymous>:9:10)
    at Engine.Filament.Engine.createMaterial (https://unpkg.com/filament/filament.js:247:29)
    at new App (https://google.github.io/filament/webgl/tutorial_triangle.js:31:24)
    at https://google.github.io/filament/webgl/tutorial_triangle.js:83:16

Expected behavior
It is expected that the triangle will be displayed without any error.
Screenshots
The canvas is black and nothing is displayed
Desktop (please complete the following information):

OS: Windows 10 + Chrome 90.0.4430.212
GPU: NVIDIA GTX RTX 2060
Backend: WebGL(ANGLE)

Additional context
The same error appears in the console in Firefox.

Gah, thank you for the bug report!  Will fix ASAP.

repo: google/filament


text:
nnx: add qkv_features back to MHA

What does this PR do?
Fixes #3564. Adds qkv_features back to MultiHeadAttention.

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (c997093) 56.17% compared to head (eb850d8) 56.19%.
Report is 4 commits behind head on main.

Additional details and impacted files
@@            Coverage Diff             @@
##             main    #3566      +/-   ##
==========================================
+ Coverage   56.17%   56.19%   +0.02%
==========================================
  Files         100      100
  Lines       11890    11924      +34
==========================================
+ Hits         6679     6701      +22
- Misses       5211     5223      +12

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

authors: cgarciae codecov-commenter

repo: google/flax


text:
DRC/LVS updates to improve performance

Fixes #<issue_number_goes_here>

It's a good idea to open an issue first for discussion.

[ ] Tests pass
[ ] Appropriate changes to README are included in PR

This needs to be rebased onto master.

@atorkmabrains - This pull request needs a better description on how you improve the performance of the DRC/LVS.

@mithro Done. I have updated the description.

authors: atorkmabrains mithro


text:
Organization Secrets

Closes #1525 and when available for use I intend to address after bumping to the new go-github version the usage for https://github.com/terraform-providers/terraform-provider-github/issues/468

GitHub Blog: https://github.blog/changelog/2020-05-14-organization-secrets/
GitHub API documentation: https://developer.github.com/v3/actions/secrets/#get-an-organization-public-key

Coverage:

[x] Get an organization public key
[x] List organization secrets
[x] Get an organization secret
[x] Create or update an organization secret
[x] List selected repositories for an organization secret
[x] Set selected repositories for an organization secret
[x] Add selected repository to an organization secret
[x] Remove selected repository from an organization secret
[x] Delete an organization secret

Closing in favor of https://github.com/google/go-github/pull/1535

repo: google/go-github


text:
Make GetArchiveLink behave the same as other calls

All available calls in the go-github package close the resp.Body before returning.
Because the GetArchiveLink method doesn’t use the Do method, we have to make sure the body is closed here as well.

@shurcooL updated the PR according to your feedback.

@shurcooL oeps! Seems I cannot do two things at the same time :wink: Updated!

@shurcooL really sorry for all my sloppiness with this PR! Should be OK now...

@shurcooL any idea when this will be merged? Thx...

This PR only needs a second review now.
@gmlewis Can You take a look at this as well?

I apologize for the delay.
Thank you, @svanharmelen and @shurcooL!
LGTM. Merging.

Included in https://github.com/google/go-github/commit/466070b0580728e63bd1a415e0019639e55d7148.

No problem! Thx!

authors: gmlewis shurcooL svanharmelen


text:
Retry http failures in ServiceAccountCredentials.refreshAccessToken

As reported in https://github.com/GoogleCloudPlatform/google-cloud-java/issues/1545 , users have seen failures in ServiceAccountCredentials.refreshAccessToken, which has no retries on the http call. These failures should be retried.
java.io.IOException: Error getting access token for service account:
         at com.google.auth.oauth2.ServiceAccountCredentials.refreshAccessToken(ServiceAccountCredentials.java:319)
         at com.google.auth.oauth2.OAuth2Credentials.refresh(OAuth2Credentials.java:149)
         at com.google.auth.oauth2.OAuth2Credentials.getRequestMetadata(OAuth2Credentials.java:135)
         at com.google.auth.http.HttpCredentialsAdapter.initialize(HttpCredentialsAdapter.java:96)
         at com.google.cloud.HttpServiceOptions$1.initialize(HttpServiceOptions.java:224)
         at com.google.api.client.http.HttpRequestFactory.buildRequest(HttpRequestFactory.java:93)
         at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:423)
         at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:352)
         at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.execute(AbstractGoogleClientRequest.java:469)
         at com.google.cloud.storage.spi.DefaultStorageRpc.create(DefaultStorageRpc.java:245)
         ... 10 more
 Caused by: java.net.SocketTimeoutException: connect timed out
  ...

Following testing investigations: Due to the limitations of various mechanisms available for dealing with timeouts in this context, it looks as though it will be exceedingly complicated to configure retrying in a way that's reliably compatible with the retrying specification used in GAX. Thus, for this use case, I'm planning to abandon this approach and instead use the distinct retrying functionality native to google-http-java-client.

authors: garrettjonesgoogle tcoffee-google

repo: google/google-auth-library-java


text:
Add multiselect for quick delete multiple accounts

Add multiselect for quick delete multiple accounts

FYI: The version in Google Play Store / Apple App store is not the same as this opensource version. They've diverged. This opensource version is also unlikely to end up in the app stores. This open source version doesn't get much love, but I'll accept well-written pull requests. But don't expect this feature to be implemented by Google.

authors: ThomasHabets skironDotNet

repo: google/google-authenticator-android


text:
Manpage for the PAM module

Hello,
As requested in #59, here is a manpage for the PAM module (pam_google_authenticator.8).
I also made some modifications to the binary manpage (google-authenticator.1) and in its help message.
Tony

Hand merged.
Thank you!

repo: google/google-authenticator-libpam


text:
WIP: new 310es reference shaders

Related issue #545:
1. binarysearch_bw

Features:

Perform a binary search
Use a struct data type
Use a do ... while loop
Use a switch statement
Use discard statement

2. mergesort_mosaic

Features:

Perform merge sort
Use a do ... while loop
Use a switch statement
Use discard statement

3. quicksort_palette

Features:

Perform quick sort
Use a do ... while loop
Use a switch statement
Use a struct data type

I tried them out and got some odd results.
mergesort_mosaic (no spirv-opt):

Some variants are not black (they look normal).
mergesort_mosaic (spirv-opt):

Some variants look black.
quicksort_palette (no spirv-opt):

quicksort_palette (spirv-opt):

I simplified mergesort_mosaic further:
mergesort_mosaic_3.frag.txt
Now I see a few wrong images, but I am still unsure if these are drivers bug or if the shader is just floating-point sensitive.

As @paulthomson has pointed out, there are undefined values caused by using derivative functions improperly so I slightly modified shaders and the following are the images produced by the latest shaders:

binarysearch_bw

mergesort_mosaic

quicksort_palette

@jiradeto Now that #665 is fixed, can you rebase?  Hopefully CI will pass for your new shaders.

authors: afd jiradeto paulthomson

repo: google/graphicsfuzz


text:
Make gtest-parallel to use python3

According to the Google Python style guide [1] and the Chromium Python
style guide [2], the shebang should be #!/usr/bin/env python3.
This is useful for running WebRTC unittests in python2-less environment.
[1] https://google.github.io/styleguide/pyguide.html
[2] https://chromium.googlesource.com/chromium/src/+/refs/heads/main/styleguide/python/python.md

Thank you, good catch!

authors: bc-lee pbos

repo: google/gtest-parallel


text:
Why are file opened in binary mode?

I think there are must be just 'r' here in hyou/client.py
  with open(json_path, 'rb') as f:
    json_text = f.read()

Besides that, 2to3 makes working module for python3.5 (One must run 2to3 to gdata and python-gflags)

I've never tried 2to3 by myself but it's good to hear it works with Python3.
I've fixed the open mode to 'r' as you pointed out. Thanks for report!

repo: google/hyou


text:
[spirv] Move vector.transfer_read scalarization earlier

This pattern was originally placed in ConvertToSPIRVPass, where
we generate mixed MemRef and SPIR-V ops. Moving it earlier to
after MemRef vectorization and let it generate pure vector ops.
This is a better layering.
This addresses the failure here.

I dont have context on this. Will let Thomas review it.

Approving since its just a move.

authors: MaheshRavishankar antiagainst

repo: google/iree


text:
Updating validations.py python script

Updated validations.py python script by adding print commands
Fixed the behavior of validate_user function in validations.py
Fixes #<issue_number_goes_here>

It's a good idea to open an issue first for discussion.

[ ] Tests pass
[ ] Appropriate changes to README are included in PR

@googlebot I signed it!

@googlebot I signed it!

repo: google/it-cert-automation-practice


text:
Force usernames to start with a letter.

Closes: #1
Fixes #<issue_number_goes_here>

It's a good idea to open an issue first for discussion.

[ ] Tests pass
[ ] Appropriate changes to README are included in PR

Now I have signed a CLA.

Unfortunately, I couldn't find a way to trigger again the checks without creating a new commit.

The git history of this forked repository was overwritten by an interactive rebase. Check the comment above and its UPDATE section.


text:
"TypeError: 'jaxlib.xla_extension.PyLocalBuffer' object is not iterable" when using JAX_DEBUG_NANS

I have a bit of JAX code that works fine but is producing some NaNs. I tried setting JAX_DEBUG_NANS=1, but it's now producing a new error in otherwise runnable code:
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
/usr/local/Cellar/python/3.7.3/Frameworks/Python.framework/Versions/3.7/lib/python3.7/runpy.py in run_module(mod_name, init_globals, run_name, alter_sys)
    203         run_name = mod_name
    204     if alter_sys:
--> 205         return _run_module_code(code, init_globals, run_name, mod_spec)
    206     else:
    207         # Leave the sys module alone

/usr/local/Cellar/python/3.7.3/Frameworks/Python.framework/Versions/3.7/lib/python3.7/runpy.py in _run_module_code(code, init_globals, mod_name, mod_spec, pkg_name, script_name)
     94         mod_globals = temp_module.module.__dict__
     95         _run_code(code, mod_globals, init_globals,
---> 96                   mod_name, mod_spec, pkg_name, script_name)
     97     # Copy the globals of the temporary module, as they
     98     # may be cleared when the temporary module goes away

/usr/local/Cellar/python/3.7.3/Frameworks/Python.framework/Versions/3.7/lib/python3.7/runpy.py in _run_code(code, run_globals, init_globals, mod_name, mod_spec, pkg_name, script_name)
     83                        __package__ = pkg_name,
     84                        __spec__ = mod_spec)
---> 85     exec(code, run_globals)
     86     return run_globals
     87

~/dev/research/research/estop/gym/half_cheetah/ppo/debug_run.py in <module>
    281   tic = time.time()
    282   optimizer, return_ = ppo_step(step_rngs[step], env_spec, train_config,
--> 283                                 optimizer, lambda t, s: t >= 200)
    284   print(f"elapsed = {time.time() - tic}, return = {return_}")

~/dev/research/research/estop/gym/half_cheetah/ppo/debug_run.py in ppo_step(rng, env_spec, train_config, params_optimizer, terminal_criterion)
    131
    132   # print(rewards)
--> 133   advantages = gae(train_config, rewards, V_t)
    134   # print(jp.max(jp.abs(advantages - gae_sketchy(train_config, rewards, V_t))))
    135   # print(advantages)

~/dev/research/research/estop/gym/half_cheetah/ppo/debug_run.py in gae(train_config, rewards, V_t)
    102   gamda = train_config.gae_gamma * train_config.gae_lambda
    103   _, gae = lax.scan(lambda carry, d: (d + gamda * carry, d + gamda * carry),
--> 104                     0.0, delta[::-1])
    105   return gae[::-1]
    106

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in scan(f, init, xs)
    452                     forward=True, length=length, jaxpr=jaxpr,
    453                     num_consts=len(consts), num_carry=num_carry,
--> 454                     linear=(False,) * (len(consts) + len(in_flat)))
    455   return tree_unflatten(out_tree, out)
    456

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in scan_bind(*args, **kwargs)
    758   return core.Primitive.bind(scan_p, *args, forward=forward, length=length,
    759                              jaxpr=jaxpr, num_consts=num_consts,
--> 760                              num_carry=num_carry, linear=linear)
    761
    762 scan_p = core.Primitive("scan")

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/core.py in bind(self, *args, **kwargs)
    128     top_trace = find_top_trace(args)
    129     if top_trace is None:
--> 130       return self.impl(*args, **kwargs)
    131
    132     tracers = map(top_trace.full_raise, args)

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in _scan_impl(*args, **kwargs)
    473
    474   ys_init = _map(partial(_empty_array, length), y_avals)
--> 475   return fori_loop(0, length, body_fun, init + ys_init)
    476
    477 def _index_array(i, aval, x):

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in fori_loop(lower, upper, body_fun, init_val)
    117     return lax.add(i, lax._const(i, 1)), body_fun(i, x)
    118
--> 119   _, result = while_loop(while_cond_fun, while_body_fun, (lower, init_val))
    120   return result
    121

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in while_loop(cond_fun, body_fun, init_val)
    172   outs = while_p.bind(*itertools.chain(cond_consts, body_consts, init_vals),
    173                       cond_nconsts=len(cond_consts), cond_jaxpr=cond_jaxpr,
--> 174                       body_nconsts=len(body_consts), body_jaxpr=body_jaxpr)
    175   return tree_unflatten(body_tree, outs)
    176

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/core.py in bind(self, *args, **kwargs)
    128     top_trace = find_top_trace(args)
    129     if top_trace is None:
--> 130       return self.impl(*args, **kwargs)
    131
    132     tracers = map(top_trace.full_raise, args)

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/interpreters/xla.py in apply_primitive(prim, *args, **params)
    122   abstract_args = map(abstractify, args)
    123   compiled_fun = xla_primitive_callable(prim, *abstract_args, **params)
--> 124   return compiled_fun(*args)
    125
    126 @cache()

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/interpreters/xla.py in _execute_compiled_primitive(prim, compiled, backend, result_handler, *args)
    172   input_bufs = [device_put(x, device_num, backend=backend) for x in args]
    173   out_buf = compiled.Execute(input_bufs)
--> 174   if FLAGS.jax_debug_nans: check_nans(prim, out_buf)
    175   return result_handler(out_buf)
    176

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/interpreters/xla.py in check_nans(prim, bufs)
    177 def check_nans(prim, bufs):
    178   if prim.multiple_results:
--> 179     for buf in bufs:
    180       _check_nans(prim.name, buf.shape(), buf)
    181   else:

TypeError: 'jaxlib.xla_extension.PyLocalBuffer' object is not iterable
/Users/skainswo/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/IPython/core/interactiveshell.py:2826: UserWarning: Unknown failure executing module: <research.estop.gym.half_cheetah.ppo.debug_run>
  warn('Unknown failure executing module: <%s>' % mod_name)

In [1]:

The code lives in a private repo, but I'd be happy to grant access to members of the JAX team.

Here's a simple repro:
research 🔥 JAX_DEBUG_NANS=1 pipenv run ipython
Python 3.7.3 (default, Mar 27 2019, 09:23:15)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.8.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import jax.numpy as jp

In [2]: from jax import lax

In [3]: lax.scan(lambda c, x: (x, x), None, jp.arange(5))

/Users/skainswo/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lib/xla_bridge.py:115: UserWarning: No GPU/TPU found, falling back to CPU.
  warnings.warn('No GPU/TPU found, falling back to CPU.')
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-3-9bd627a0101d> in <module>
----> 1 lax.scan(lambda c, x: (x, x), None, jp.arange(5))

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in scan(f, init, xs)
    452                     forward=True, length=length, jaxpr=jaxpr,
    453                     num_consts=len(consts), num_carry=num_carry,
--> 454                     linear=(False,) * (len(consts) + len(in_flat)))
    455   return tree_unflatten(out_tree, out)
    456

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in scan_bind(*args, **kwargs)
    758   return core.Primitive.bind(scan_p, *args, forward=forward, length=length,
    759                              jaxpr=jaxpr, num_consts=num_consts,
--> 760                              num_carry=num_carry, linear=linear)
    761
    762 scan_p = core.Primitive("scan")

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/core.py in bind(self, *args, **kwargs)
    128     top_trace = find_top_trace(args)
    129     if top_trace is None:
--> 130       return self.impl(*args, **kwargs)
    131
    132     tracers = map(top_trace.full_raise, args)

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in _scan_impl(*args, **kwargs)
    473
    474   ys_init = _map(partial(_empty_array, length), y_avals)
--> 475   return fori_loop(0, length, body_fun, init + ys_init)
    476
    477 def _index_array(i, aval, x):

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in fori_loop(lower, upper, body_fun, init_val)
    117     return lax.add(i, lax._const(i, 1)), body_fun(i, x)
    118
--> 119   _, result = while_loop(while_cond_fun, while_body_fun, (lower, init_val))
    120   return result
    121

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/lax/lax_control_flow.py in while_loop(cond_fun, body_fun, init_val)
    172   outs = while_p.bind(*itertools.chain(cond_consts, body_consts, init_vals),
    173                       cond_nconsts=len(cond_consts), cond_jaxpr=cond_jaxpr,
--> 174                       body_nconsts=len(body_consts), body_jaxpr=body_jaxpr)
    175   return tree_unflatten(body_tree, outs)
    176

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/core.py in bind(self, *args, **kwargs)
    128     top_trace = find_top_trace(args)
    129     if top_trace is None:
--> 130       return self.impl(*args, **kwargs)
    131
    132     tracers = map(top_trace.full_raise, args)

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/interpreters/xla.py in apply_primitive(prim, *args, **params)
    122   abstract_args = map(abstractify, args)
    123   compiled_fun = xla_primitive_callable(prim, *abstract_args, **params)
--> 124   return compiled_fun(*args)
    125
    126 @cache()

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/interpreters/xla.py in _execute_compiled_primitive(prim, compiled, backend, result_handler, *args)
    172   input_bufs = [device_put(x, device_num, backend=backend) for x in args]
    173   out_buf = compiled.Execute(input_bufs)
--> 174   if FLAGS.jax_debug_nans: check_nans(prim, out_buf)
    175   return result_handler(out_buf)
    176

~/.local/share/virtualenvs/research-CJWjSlE2/lib/python3.7/site-packages/jax/interpreters/xla.py in check_nans(prim, bufs)
    177 def check_nans(prim, bufs):
    178   if prim.multiple_results:
--> 179     for buf in bufs:
    180       _check_nans(prim.name, buf.shape(), buf)
    181   else:

TypeError: 'jaxlib.xla_extension.PyLocalBuffer' object is not iterable

In [4]:

This looks like it might be #1401? Can you try updating your JAX to a version that includes #1429?
(It looks like we haven't made a PyPI release since then, but you should be able to use a source checkout of JAX with the latest prebuilt jaxlib.)

I just updated pypi to 0.1.47, which should include #1429. @samuela can you see if the issue still reproduces?

Upgrading to jax==0.1.47 fixed it!

authors: jekbradbury mattjj samuela

repo: google/jax


text:
Cuda Version：Does CUDA 10.2 support Jax?

Does CUDA 10.2 support Jax?

Yes, we do currently host prebuilt wheels for CUDA 10.2, with the extra requirement of cuDNN7 (as stated in the README). You should be able to install it using the following command:
pip install jax jaxlib==0.1.71+cuda102 -f https://storage.googleapis.com/jax-releases/jax_releases.html

Actually that's out of date. We've dropped support for all CUDA versions less than 11.1.
You can most likely build jaxlib yourself from source for an earlier CUDA version, but please note that all versions prior to 11.1 have known bugs (on NVidia's side, in ptxas) which we cannot work around. So I recommend upgrading your CUDA installation!

authors: apaszke hawkinsp kdpan


text:
Problem with my scroll

Hello. I use mdl and want to make my native scroll on the page.
Code below doesn't work, maybe mdl change $(window).scrollTop() and  $(window).height() :
$(window).scroll(function() {
if($(window).scrollTop() + $(window).height() >= $(document).height() - 200 && !inProgress) {
And this code is works:
$('mdl-layout__container').scroll(function() {
if($(window).scrollTop() + $(window).height() >= $(document).height() - 200 && !inProgress) {
but not correctly. I use previous function on another site without mdl, and it's work very well. Maybe somebody know how fix this?

Scrolling on the window doesn't currently occur due to the way layout is handled. You've figured out on your own that you need to attach it to the layout container.
Beyond that information, we can't really help with this. It is custom code integrating MDL into a project which we can't help with since it isn't a problem with the code we provide. Please try using StackOverflow for support and integration help.

@Garbee I ran into the same problem. It's a simple avtopodgruzka! Deystvetilna It does not work due to the fact that MDR uses $(window).
Is it possible to somehow decouple the parameter $(window)?

Instead of using above use this $('.mdl-layout__content').scroll(function() { if($('.mdl-layout__content').scrollTop() + $(window).height() >= $(document).height() - 200 && !inProgress) {
Reference link : - https://github.com/google/material-design-lite/issues/url

$('html, body, div').scroll(function() {
var offset = $('#overview').offset().top;
});

authors: Garbee Gesparo Henxed iHTCboy raviagarwal292

repo: google/material-design-lite


text:
When mdl-layout__header is wrapper insider a div the menu icon and drawer is not showing properly

When mdl-layout__header is NOT wrapped inside another div, the drawer icon is showing properly
<header class="mdl-layout__header">
...
</header>

<main class="mdl-layout__content">
....
</main>

However, when mdl-layout__header IS wrapped inside another div, the icon is gone
<div>
  <header class="mdl-layout__header">
    ...
  </header>
</div>

<main class="mdl-layout__content">
....
</main>

Since I am using anuglarjs for the front-end app, when create a directive where the header section is in, the icon and drawer does not function properly. However could I solve this problem?
<navigation></navigation>

<main class="mdl-layout__content">
....
</main>

When angularjs complied the template, the result is:
<navigation>
  <header class="mdl-layout__header">
      ...
    </header>
</navigation>

<main class="mdl-layout__content">
....
</main>

Please use StackOverflow for support and integration assistance. This tracker is only for problems with the code provided by Material Design Lite.
We provide the specific markup needed to make layout function properly. It is quite complex and due to achieving IE9 support for that necessary in 1.x. If your tool can't produce that markup, then you need to find a workaround in your tooling to provide it.
Thank you.

authors: Garbee joshuajazleung


text:
Adding reordering classes to the grid

This PR adds reordering classes to the grid, numbered 1 to 12 for the maximum number of columns on our grid. These are convenience classes that provide autoprefixed order attributes.
@surma @Garbee PTAL!

Also, this closes #239.

lgtm

:+1: Nice work :)

Thank you, gentlemen. Merging!

authors: Garbee sgomes surma


text:
Objectron javascript library doesn't work after building the app

Have I written custom code (as opposed to using a stock example script provided in MediaPipe)
None
OS Platform and Distribution
WSL Ubuntu 20.04.5
Mobile device if the issue happens on mobile device
No response
Browser and version if the issue happens on browser
Google Chrome 109.0.5414.120
Programming Language and version
JavaScript
MediaPipe version
No response
Bazel version
No response
Solution
Objectron
Android Studio, NDK, SDK versions (if issue is related to building in Android environment)
No response
Xcode & Tulsi version (if issue is related to building for iOS)
No response
Describe the actual behavior
Objectron is able to initialize in development but doesn't work after building the javascript application.

Describe the expected behaviour
Objectron should initialize in development and work after building the javascript application.

Standalone code/steps you may have used to try to get what you need
I'm using @mediapipe/objectron javascript package in my ViteJS application using ReactJS as template.
You can find a reproducible repository here: https://github.com/thisisrishabh22/mediapipe-threejs

Steps to reproduce:
1. Clone the repository
2. Install packages using: yarn install
3. Run in the development environment using: yarn dev
4. Create a production build using: yarn build
5. Run in the production environment using: yarn preview

Other info / Complete Logs
Unexpected Application Error!
sl.Objectron is not a constructor

Vg/<@http://localhost:4173/assets/index-d3345c5a.js:84:17875
Xl@http://localhost:4173/assets/index-d3345c5a.js:40:24263
Kr@http://localhost:4173/assets/index-d3345c5a.js:40:42317
iy@http://localhost:4173/assets/index-d3345c5a.js:40:41163
tr@http://localhost:4173/assets/index-d3345c5a.js:40:40212
Wf@http://localhost:4173/assets/index-d3345c5a.js:40:36824
Xn@http://localhost:4173/assets/index-d3345c5a.js:38:3274
dt/<@http://localhost:4173/assets/index-d3345c5a.js:40:34207

Hello @thisisrishabh22
Thanks for raising this issue. We are aware of the issue and working on a solution.
This seems to be happening due to the Rollup CommonJS plugin, since this plugin can't work with obfuscated packages and the JS source code for MediaPipe is not public. Rollup uses static analysis to determine its exports.
We are working on a solution to unveal the JS code. Meanwhile, can you refer to this workaround and let us know if this works for you?
PS: The link by the author has changed to this link

Hi @ayushgdev
I've referred to the workaround you've shared and tried to implement it in my application but it's actually not working.
Thanks

Hello @thisisrishabh22
We are refreshing our solutions into new Tasks API. They should not have this issue, as they are built using ESM. However, they are not mature enough to be used in production yet, but you can explore the new APIs here
Due to our existing infrastructure, it is difficult for us to release the existing libraries using ESM.

repo: google/mediapipe


text:
Unrecognized option: --experimental_repo_remote_exec

OS Platform and Distribution
macOS Ventura 13.4.1
Compiler version
No response
Programming Language and version
Python 3.9.16
Installed using virtualenv? pip? Conda?(if python)
Conda
MediaPipe version
no know
Bazel version
1.10
XCode and Tulsi versions (if iOS)
Latest
Android SDK and NDK versions (if android)
No response
Android AAR (if android)
None
OpenCV version (if running on desktop)
No response
Describe the problem
bazel run --define MEDIAPIPE_DISABLE_GPU=1 \
    mediapipe/examples/desktop/hello_world:hello_world

Complete Logs
INFO: Options provided by the client:
  Inherited 'common' options: --isatty=1 --terminal_columns=190
INFO: Reading rc options for 'run' from /Users/kou/0722/mediapipe/.bazelrc:
  Inherited 'common' options: --experimental_repo_remote_exec
ERROR: Unrecognized option: --experimental_repo_remote_exec
INFO: Writing tracer profile to '/private/var/tmp/_bazel_kou/dc26a0ac637f6cad0ee0f4d1b6b9b377/command.profile.gz'

memo: Bazelik version is 1.17.0

@koko-cg,
Could you please run the below command and let us know if this works for you.
bazelisk run --define MEDIAPIPE_DISABLE_GPU=1 mediapipe/examples/desktop/hello_world:hello_world
Thank you!

Thank you !
I tried the command you taught me, and there were no errors! However, this is what happened with the last part

@koko-cg,
Thank you for the confirmation, Can we mark issue resolved and close the status if now this issue is no longer issue from your end.

Yes, it really helped me out. Thank you from the bottom of my heart!

authors: koko-cg kuaashish


text:
Request for maintaining a Changelog!

Request for maintaining a changelog!
I'm checking this repository after a long time. I had last used v0.7.0, I would like to know what new functionalities have been added!

@KingYapster We actually do keep a changelog in the "releases" section of our Github project: https://github.com/google/model-viewer/releases
Please let me know if that's what you were hoping to find!

Thanks! @cdata

authors: KingYapster cdata

repo: google/model-viewer


text:
Update install.md

This change is

Update the name of the gradle task to stage Beam pipelines manually.

Friendly ping.

repo: google/nomulus


text:
warning:"The model has been changed since the solution was last computed"

What version of OR-Tools and what language are you using?
Version: master
Language: Python
Which solver are you using (e.g. CP-SAT, Routing Solver, GLOP, BOP, Gurobi)
SCIP
What operating system (Linux, Windows, ...) and version?
macOS
10.13
What did you do?
when i run the following code, it shows that:
Total cost =  0.0
WARNING: Logging before InitGoogleLogging() is written to STDERR
E0528 05:12:36.826904     1 linear_solver.cc:1699] The model has been changed since the solution was last computed.
MPSolverInterface::sync_status_ = 0

from openpyxl import load_workbook
from sklearn.ensemble import IsolationForest
import itertools
import calDistance
from ortools.linear_solver import pywraplp

wb = load_workbook("orderLists.xlsx")
ws = wb["result_collect"]

max_row = ws.max_row
points = []
for row in range(1, max_row + 1):
    point = [ws.cell(row, 4).value, ws.cell(row, 5).value]
    points.append(point)

point_number = len(points)

model = IsolationForest(n_estimators=point_number)
prediction = model.fit_predict(points)

isolation_points_index = []
for i in range(point_number):
    if prediction[i] == -1:
        isolation_points_index.append(i)

no_isolated_points_index = []
for i in range(point_number):
    if i not in isolation_points_index:
        no_isolated_points_index.append(i)
no_isolated_points = len(no_isolated_points_index)

route_list = []
for item in itertools.product(no_isolated_points_index, no_isolated_points_index):
    route_list.append(list(item))

route_number = len(route_list)

for i in range(route_number):
    item = route_list[i]
    item.append(-1)

vehicle_cost = [3.5, 6, 9]
vehicle_load = [12000, 60000, 85000]

fixed_point = [113.233, 23.166]

route_vehicle_cost = []
for route in route_list:
    temp = []
    distance = 0
    for i in range(len(route)):
        if i < len(route) - 1:
            if route[i + 1] == -1:
                distance += calDistance.geo_distance(points[route[i]], fixed_point)
            else:
                distance += calDistance.geo_distance(points[route[i]], points[route[i + 1]])

    for i in range(len(vehicle_cost)):
        temp.append(vehicle_cost[i] * distance)
    route_vehicle_cost.append(temp)

weight_per_point = []
ws = wb["result_collect"]
for row in range(1, 61 + 1):
    weight_per_point.append(ws.cell(row, 2).value)

solver = pywraplp.Solver.CreateSolver("SCIP")
infinity = solver.infinity()

x = {}
for i in range(route_number):
    for j in range(3):
        x[(i, j)] = solver.IntVar(0.0, infinity, "x_{}_{}".format(i, j))

supply = {}
for i in range(point_number):
    supply[i] = solver.NumVar(0.0, infinity, "supply_{}".format(i))

for index in range(route_number):
    route = route_list[index]
    for i in range(3):
        supply[route[0]] += 0.5 * x[(index, i)]
        supply[route[1]] += 0.5 * x[(index, i)]

for index in no_isolated_points_index:
    solver.Add(supply[index] >= weight_per_point[index])

solver.Minimize(solver.Sum(x[(i, j)] * route_vehicle_cost[i][j] for i in range(route_number) for j in range(3)))
print('Total cost = ', solver.Objective().Value())

is this warning cause by
      supply[route[1]] += 0.5 * x[(index, i)]

?
what i want to do is to set an intermediate variable supply

# 建立约束条件 for index in no_isolated_points_index:     solver.Add(supply[index] >= weight_per_point[index])

You have not called Solve().

authors: lperron whoknowsname

repo: google/or-tools


text:
Configure TrackEvent in UI

It would be helpful to be able to configure one or more TrackEvent data sources in the Perfetto UI.  Ideally the UI would have the option to query the current set of Producers to get a list of available processes, categories, and tags, and an easy way to filter accordingly.
Currently to use TrackEvent data sources, the trace must be executed outside of the UI in order to supply a handwritten TraceConfig.

Agree, this should definitely be on our radar :) Technically, the querying described by @rickvanprim should be possible after @octaviantu's improvements. We can already query the track event data source descriptor with available categories from the service. We'd probably want to extend it such that it also specifies available tags.

Would be great having the ability to configure track events from the UI. Currently we are forced to write the config separately and invoke from the terminal.

@primiano maybe you can fix this as part of your look again into recording?

authors: LalitMaganti betasheet rickvanprim santisan

repo: google/perfetto