Installation Failure

My environment: centos7, GCC 5.4, nvidia driver 470.82.01, cuda: 11.4, anaconda, python 3.9.13 pytorch 1.10.1, pyg 2.0.4
Install from source, with pip install -e .

Could you help me install this package? Thanks!

Thanks for the issue. Is it possible to share the full log with me?

The stdout shows:

Obtaining file:///home/jones.wz/pyg_autoscale
Preparing metadata (setup.py): started
Preparing metadata (setup.py): finished with status 'done'
Requirement already satisfied: ogb in /home/jones.wz/myogb (from torch-geometric-autoscale==0.0.0) (1.3.4)
Requirement already satisfied: hydra-core in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from torch-geometric-autoscale==0.0.0) (1.2.0)
Requirement already satisfied: antlr4-python3-runtime==4.9.* in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from hydra-core->torch-geometric-autoscale==0.0.0) (4.9.3)
Requirement already satisfied: omegaconf~=2.2 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from hydra-core->torch-geometric-autoscale==0.0.0) (2.2.3)
Requirement already satisfied: packaging in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from hydra-core->torch-geometric-autoscale==0.0.0) (21.3)
Requirement already satisfied: torch>=1.6.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from ogb->torch-geometric-autoscale==0.0.0) (1.10.1)
Requirement already satisfied: numpy>=1.16.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from ogb->torch-geometric-autoscale==0.0.0) (1.22.4)
Requirement already satisfied: tqdm>=4.29.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from ogb->torch-geometric-autoscale==0.0.0) (4.64.0)
Requirement already satisfied: scikit-learn>=0.20.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from ogb->torch-geometric-autoscale==0.0.0) (1.1.1)
Requirement already satisfied: pandas>=0.24.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from ogb->torch-geometric-autoscale==0.0.0) (1.4.4)
Requirement already satisfied: six>=1.12.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from ogb->torch-geometric-autoscale==0.0.0) (1.16.0)
Requirement already satisfied: urllib3>=1.24.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from ogb->torch-geometric-autoscale==0.0.0) (1.26.12)
Requirement already satisfied: outdated>=0.2.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from ogb->torch-geometric-autoscale==0.0.0) (0.2.1)
Requirement already satisfied: PyYAML>=5.1.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from omegaconf~=2.2->hydra-core->torch-geometric-autoscale==0.0.0) (6.0)
Requirement already satisfied: littleutils in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from outdated>=0.2.0->ogb->torch-geometric-autoscale==0.0.0) (0.2.2)
Requirement already satisfied: requests in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from outdated>=0.2.0->ogb->torch-geometric-autoscale==0.0.0) (2.28.1)
Requirement already satisfied: python-dateutil>=2.8.1 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from pandas>=0.24.0->ogb->torch-geometric-autoscale==0.0.0) (2.8.2)
Requirement already satisfied: pytz>=2020.1 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from pandas>=0.24.0->ogb->torch-geometric-autoscale==0.0.0) (2022.2.1)
Requirement already satisfied: joblib>=1.0.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from scikit-learn>=0.20.0->ogb->torch-geometric-autoscale==0.0.0) (1.1.0)
Requirement already satisfied: threadpoolctl>=2.0.0 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from scikit-learn>=0.20.0->ogb->torch-geometric-autoscale==0.0.0) (3.1.0)
Requirement already satisfied: scipy>=1.3.2 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from scikit-learn>=0.20.0->ogb->torch-geometric-autoscale==0.0.0) (1.8.0)
Requirement already satisfied: typing_extensions in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from torch>=1.6.0->ogb->torch-geometric-autoscale==0.0.0) (4.3.0)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from packaging->hydra-core->torch-geometric-autoscale==0.0.0) (3.0.9)
Requirement already satisfied: certifi>=2017.4.17 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from requests->outdated>=0.2.0->ogb->torch-geometric-autoscale==0.0.0) (2022.6.15)
Requirement already satisfied: charset-normalizer<3,>=2 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from requests->outdated>=0.2.0->ogb->torch-geometric-autoscale==0.0.0) (2.1.1)
Requirement already satisfied: idna<4,>=2.5 in /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages (from requests->outdated>=0.2.0->ogb->torch-geometric-autoscale==0.0.0) (3.3)
Installing collected packages: torch-geometric-autoscale
Running setup.py develop for torch-geometric-autoscale

The stderr shows:
error: subprocess-exited-with-error
× python setup.py develop did not run successfully.
│ exit code: 1
╰─> [185 lines of output]
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/setuptools/dist.py:771: UserWarning: Usage of dash-separated 'description-file' will not be supported in future versions. Please use the underscore name 'description_file' instead
      warnings.warn(
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/setuptools/installer.py:27: SetuptoolsDeprecationWarning: setuptools.installer is deprecated. Requirements should be satisfied by a PEP 517 installer.
      warnings.warn(
    running develop
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/setuptools/command/easy_install.py:144: EasyInstallDeprecationWarning: easy_install command is deprecated. Use build and pip and other standards-based tools.
      warnings.warn(
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/setuptools/command/install.py:34: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.
      warnings.warn(
    running egg_info
    writing torch_geometric_autoscale.egg-info/PKG-INFO
    writing dependency_links to torch_geometric_autoscale.egg-info/dependency_links.txt
    writing requirements to torch_geometric_autoscale.egg-info/requires.txt
    writing top-level names to torch_geometric_autoscale.egg-info/top_level.txt
    reading manifest file 'torch_geometric_autoscale.egg-info/SOURCES.txt'
    adding license file 'LICENSE'
    writing manifest file 'torch_geometric_autoscale.egg-info/SOURCES.txt'
    running build_ext
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/utils/cpp_extension.py:782: UserWarning: The detected CUDA version (11.4) has a minor version mismatch with the version that was used to compile PyTorch (11.3). Most likely this shouldn't be a problem.
      warnings.warn(CUDA_MISMATCH_WARN.format(cuda_str_version, torch.version.cuda))
    building 'torch_geometric_autoscale._async' extension
    gcc -pthread -B /home/jones.wz/anaconda3/envs/fs/compiler_compat -Wno-unused-result -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /home/jones.wz/anaconda3/envs/fs/include -I/home/jones.wz/anaconda3/envs/fs/include -fPIC -O2 -isystem /home/jones.wz/anaconda3/envs/fs/include -fPIC -DWITH_CUDA -Icsrc -I/home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include -I/home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include -I/home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/TH -I/home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/THC -I/usr/local/cuda-11.4/include -I/home/jones.wz/anaconda3/envs/fs/include/python3.9 -c csrc/async.cpp -o build/temp.linux-x86_64-cpython-39/csrc/async.o -DAT_PARALLEL_OPENMP -fopenmp -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_async -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
    /usr/local/cuda-11.4/bin/nvcc -DWITH_CUDA -Icsrc -I/home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include -I/home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include -I/home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/TH -I/home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/THC -I/usr/local/cuda-11.4/include -I/home/jones.wz/anaconda3/envs/fs/include/python3.9 -c csrc/cuda/async_cuda.cu -o build/temp.linux-x86_64-cpython-39/csrc/cuda/async_cuda.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' -arch=sm_35 --expt-relaxed-constexpr -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_async -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
    nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::CrossMapLRN2dImpl]’:
    /tmp/tmpxft_0000d27f_00000000-6_async_cuda.cudafe1.stub.c:15:27:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::EmbeddingBagImpl]’:
    /tmp/tmpxft_0000d27f_00000000-6_async_cuda.cudafe1.stub.c:15:27:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::EmbeddingImpl]’:
    /tmp/tmpxft_0000d27f_00000000-6_async_cuda.cudafe1.stub.c:15:27:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::ParameterDictImpl]’:
    /tmp/tmpxft_0000d27f_00000000-6_async_cuda.cudafe1.stub.c:15:27:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::SequentialImpl]’:
    /tmp/tmpxft_0000d27f_00000000-6_async_cuda.cudafe1.stub.c:15:27:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::ModuleListImpl]’:
    /tmp/tmpxft_0000d27f_00000000-6_async_cuda.cudafe1.stub.c:15:27:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::ModuleDictImpl]’:
    /tmp/tmpxft_0000d27f_00000000-6_async_cuda.cudafe1.stub.c:15:27:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::TransformerDecoderImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::TransformerEncoderImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::TransformerDecoderLayerImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::TransformerEncoderLayerImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::GroupNormImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::LocalResponseNormImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::LayerNormImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::MultiheadAttentionImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::ThresholdImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::LogSoftmaxImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::SoftminImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::SoftmaxImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::GRUCellImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::LSTMCellImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::RNNCellImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::GRUImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::LSTMImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::RNNImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::FractionalMaxPool3dImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::FractionalMaxPool2dImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::ZeroPad2dImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::UnfoldImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::FoldImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::ConvTranspose3dImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::ConvTranspose2dImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::ConvTranspose1dImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::Conv3dImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::Conv2dImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::Conv1dImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::AdaptiveLogSoftmaxWithLossImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::BilinearImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::UnflattenImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h: In instantiation of ‘std::shared_ptr<torch::nn::Module> torch::nn::Cloneable<Derived>::clone(const c10::optional<c10::Device>&) const [with Derived = torch::nn::LinearImpl]’:
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/optim/sgd.h:49:48:   required from here
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:57:59: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’
    /home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:69:61: error: invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >’ to type ‘torch::OrderedDict<std::basic_string<char>, std::shared_ptr<torch::nn::Module> >&’
    error: command '/usr/local/cuda-11.4/bin/nvcc' failed with exit code 1
    [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
╰─> [185 lines of output]
/home/jones.wz/anaconda3/envs/fs/lib/python3.9/site-packages/setuptools/dist.py:771: UserWarning: Usage of dash-separated 'description-file' will not be supported in future versions. Please use the underscore name 'description_file' instead
warnings.warn(
and it repeats again

The error seems to be invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’. A similar issue is reported in https://github.com/NVIDIA/apex/issues/1268. Hopefully, updating GCC to a later version will fix this problem.

The error seems to be invalid static_cast from type ‘const torch::OrderedDict<std::basic_string<char>, at::Tensor>’ to type ‘torch::OrderedDict<std::basic_string<char>, at::Tensor>&’. A similar issue is reported in NVIDIA/apex#1268. Hopefully, updating GCC to a later version will fix this problem.

I updated gcc to version 7.3.1. It works! Thanks!


Trying to find various Myenergi values in Node Red

I am using the Node Red Myenergi palette to get data from my Zappie, Eddie and Harvi into Node Red. I have found the values for power going into those in the data coming from the getZappiAll node and the getEddieAll nodes.
I am looking for the following (if it exists)
Is the car connected to the Zappi
How many kWh has Zappi charged in this session (or today)
How many kWh has Harvi diverted today
This is shown on the website, (see screenshot above) so I hope this data is available
Adn how can I set the Minimum green level for the Zappi from Node Red ?

I'm not sure about some of your questions, but I submitted a PR here...
https://github.com/brookesdjb/node-red-contrib-myenergi/pull/1
...to addd MGL etc to the node red zappi nodes. Might be worth chasing @brookesdjb to get my PR merged.


Regression from 0.10.10 to 0.10.11: Main window not rendered

Describe the bug
I see a black main window:

To Reproduce
Prerequisite: Installed Avalonia templates (dotnet new -i Avalonia.Templates)

mkdir TestAvaloniaApp && cd TestAvaloniaApp
dotnet new avalonia.mvvm
Upgrade Avalonia packages from version 0.10.10 to 0.10.11

With dotnet-oudated:

dotnet tool install -g dotnet-outdated-tool
dotnet outdated -u

Manually

Open the TestAvaloniaApp.csproj and change all references from version 0.10.10 to 0.10.11

dotnet run
Window isn't rendered

Expected behavior
A rendered window showing the following:

Screenshots
If applicable, add screenshots to help explain your problem.
Desktop (please complete the following information):

OS: Ubuntu 21.10, Wayland, NVidia
Version 0.10.11

Additional context
It seems that it's a regression in 0.10.11, because rendering works in 0.10.10.
The debug output shows:
[Visual] Exception in render loop: 'System.ArgumentException: Invalid create info - no Canvas provided (Parameter 'createInfo')
   at Avalonia.Skia.DrawingContextImpl..ctor(CreateInfo createInfo, IDisposable[] disposables) in /_/src/Skia/Avalonia.Skia/DrawingContextImpl.cs:line 108
   at Avalonia.Skia.SkiaGpuRenderTarget.CreateDrawingContext(IVisualBrushRenderer visualBrushRenderer) in /_/src/Skia/Avalonia.Skia/Gpu/SkiaGpuRenderTarget.cs:line 40
   at Avalonia.Rendering.DeferredRenderer.EnsureDrawingContext(IDrawingContextImpl& context) in /_/src/Avalonia.Visuals/Rendering/DeferredRenderer.cs:line 617
   at Avalonia.Rendering.DeferredRenderer.UpdateRenderLayersAndConsumeSceneIfNeeded(IDrawingContextImpl& context, Boolean recursiveCall) in /_/src/Avalonia.Visuals/Rendering/DeferredRenderer.cs:line 374
   at Avalonia.Rendering.DeferredRenderer.Render(Boolean forceComposite) in /_/src/Avalonia.Visuals/Rendering/DeferredRenderer.cs:line 323
   at Avalonia.Rendering.DeferredRenderer.Avalonia.Rendering.IRenderLoopTask.Render() in /_/src/Avalonia.Visuals/Rendering/DeferredRenderer.cs:line 275
   at Avalonia.Rendering.RenderLoop.TimerTick(TimeSpan time) in /_/src/Avalonia.Visuals/Rendering/RenderLoop.cs:line 147' (RenderLoop #52307948)

@danwalmsley it looks like that Skia 2.88 is not that stable after all.

@fubar-coder which nvidia driver are you using?

I'm using nvidia-driver-495

Unfortunately I can't repro with Xorg+Bumblebee-based setup. Setting up 21.10 with Wayland will take some time.

@kekekeks It's not critical (yet), because 0.10.10 works well enough for my use case.

I can reproduce this on Fedora 36. This still happens all the way on 0.10.18

I have the same issue on Fedora Silverblue/kinoite with a wayland session. See https://github.com/Revolutionary-Games/Thrive-Launcher/issues/180 :)
I am using the proprietary nvidia drivers here from the rpm fusion repos.

We have a PR for wayland support open. Probably you want to test it out and give some feedback if you find anything not working as expected. See #8352

I was same problem in OpenSuse Tumbleweed 15.4, coincidentally I notice some glitchs on VS Code and Chrome.
Then I decided to install proprietary NVIDIA graphical driver folowing this tuto https://www.if-not-true-then-false.com/2022/opensuse-nvidia-guide, this solved the problem.
Avalonia: 0.10.14
OS: OpenSuse Tumbleweed 15.4 Gnome
I left this comment to help others in future.

not

Hey,
any news here?


Planet.isLoaded() always returns undefined

The method Planet.isLoaded() always returns undefined.
It refers to "this.hightDirty", which is an undefined member. But the wrapped object, ccpwgl_int.EvePlanet, contains such a member.
Yet I don't think this is the proper way to check whether the planet is loaded - this member of EvePlanet is reset to false in GetBatches() at the render stage.
Since there is no onLoad parameter for scene.loadPlanet(), for now we have to assume a planet is immediately in "loaded" state after construction.

fixed in 205ce269eb790ef5e1884a6785ee45c62f5f1385


Carl/donet2

There's something I don't understand with Log2SoftwareFallback as it was pushed previously.  I pushed a workaround for now.  All test are passing.

git workflow will soon be modified for .net 4.7.1 support

@CarlVerret Why did you remove the -0 tests? We do want to parse -0 to -0. The platform can do what it likes, but we should check that we do it properly, like .NET 5.
See How does your programming language handle “minus zero” (-0.0)?

Actually I moved it to another test thats doesn't depends on displayed value

Actually I moved it to another test thats doesn't depends on displayed value

Good!


Update intro to Sensitive personal data.

Include links to Word file and SciLifeLab DSW

Inga problem med vad du ändrat men hela intro-stycket ser märkligt ut:
"The following is a list of Ethical, Legal and Social implications (ELSI) are topics (ta bort 'are topics'?) that has to been (felstavning) considered when working with human data. The content on this page is based on a checklist on theses (felstavning) topics that has been (ersätt 'that has been' med ett kommatecken?) developed in the Tryggve project. The checklist can be used as a tool to document these considerations. It is available as: "
Ändrar du eller ska jag?


Test : Refactor:  Move the test definitions to separate files from the test engine.

Currently the tests for lhp_parser.c are all in test_main.c along with the general testing engine.

Move the lhp_parser.c tests to a separate file.
Update the general testing engine to manage setups and sets of test with less code duplication (DRY-principle)
Add flag for verbose output.

Merged to 0.0.3-milestone-branch from pull-request: #44 Separate test definitions from test engine


Gather latest available CentOS 9 stream based on CHECKSUM file content

Since CentOS Stream images are often removed from server, we can retrieve the lastest available image using CHECKSUM file as a reference.

recheck


how to delete Eip when porter-manager has deleted

i can't delelte Eip,  my porter-manager has deleted already.

This issue might help you.

This issue might help you.

i read issue
when i can delete the finalizers field in the yaml with kubectl edit eip xxx
, the command response error ：
error: eips.network.kubesphere.io "porter-layer2-eip" could not be patched: Internal error occurred: failed calling webhook "validate.eip.network.kubesphere.io": Post "https://porter-32gjb1-manager.develops-components.svc:443/validate-network-kubesphere-io-v1alpha2-eip?timeout=10s": service "porter-32gjb1-manager" not found
You can run kubectl replace -f /tmp/kubectl-edit-bg5ql.yaml to try this update again.

How did you  install porter-manager and delete porter-manager?

How did you install porter-manager and delete porter-manager?
install by kubesphere,  uninstall by kubesphere


plugins/artnet: force IPv4 when binding UDP socket

qlcplus on Ubuntu 22.04 right now when configuring ArtNet input on an IPv4 address seems not to receive UDP packets (see  #1588).
Forcing IPv4 when binding UDP socket solves the issue.
Another more complicated approach is to create a socket for each input address and bind it explicitly to the address

Still to be checked, since qlcplus 4.13.1 on Windows 11 and qlcplus 4.12.7 on Mac seem to work out of the box.

@Pac72 thanks for this but I'm afraid it won't work.

The first argument as SpecialAddress has been introduced in Qt 6.2. QLC+ still needs to be compatible with Qt 5.15 for a while.

coverage: 32.034%. remained the same
when pulling fee6d22278f6de43acd9527dcc1a5f108640dd03 on Pac72:art-net-force-ipv4
into c1f5846de11931e43213afbd49b7cbac1031e23d on mcallegari:master.

@mcallegari I was puzzled, since I built against 5.15.2 and, as you say, the bind(QHostAddress::SpecialAddress addr,...) is not defined.
Then I realized that there is a constructor

QHostAddress(SpecialAddress address)

so the call

udpSocket->bind(QHostAddress::SpecialAddress::AnyIPv4, ARTNET_PORT, QUdpSocket::ShareAddress | QUdpSocket::ReuseAddressHint)

is using

bool bind(const QHostAddress &address, quint16 port = 0, BindMode mode = DefaultForPlatform);

Anyway, this patch is not relevant anymore, since, until now, I haven't been able to reproduce the issue #1588 I opened.
Either it was some network sillyness (likely) or some strange linking issue (unlikely).
I'm giving it a last try, then I'll close the issue as PEBKAC


Cherry-Pick of Filtering only to .pdb files while indexing sources (#5126)

Excluding non-pdb files while indexing sources

Updating TestCases

@arunkm,
Thanks for your contribution as a Microsoft full-time employee or intern. You do not need to sign a CLA.
Thanks,
Microsoft Pull Request Bot


[C++] Fix GCC compilation failure caused by warning macro

Motivation
When I tried to build the C++ client with GCC 7.3 and when warnings are
printed (because BOOST_ARCH_X86_64 is not defined), the compilation
failed with:
#warning “BOOST_ARCH_X86_64 is not defined, CRC32C SSE4.2 will be disabled”
  ^~~~~~~
cc1plus: error: unrecognized command line option '-Wno-stringop-truncation' [-Werror]
cc1plus: all warnings being treated as errors

It seems to be a bug before GCC 8.1. I added
-DCMAKE_VERBOSE_MAKEFILE=ON to CMake command and see the full compile
command:
-Wno-error -Wall -Wformat-security -Wvla -Werror -Wno-sign-compare -Wno-deprecated-declarations -Wno-error=cpp -Wno-stringop-truncation

See
https://github.com/apache/pulsar/blob/b829a4ce121268f55748bbdd6f19ac36129e7dab/pulsar-client-cpp/CMakeLists.txt#L105-L106
For GCC > 4.9, -Wno-stringop-truncation option was added. However,
when a message was printed by #warning macro, it would fail with the
strange error message.
The simplest way to reproduce the bug is compiling following code:
#warnings "hello"

int main() {}

You can paste the code above to https://godbolt.org/, select any GCC
compiler whose version is lower than 8.0, then add the following
options:
-Werror -Wno-error=cpp -Wno-stringop-truncation

The compilation failed for x86-64 gcc 7.5 while it succeeded for 8.1.
Modifications
Only add the -Wno-stringop-truncation option for GCC >= 8.1.

Without the #warning macro, even GCC 7.5 works well. So I suspect it's a bug of GCC < 8.


Bug OCPBUGS-3667: FIX CLOCK REALTIME status is locked when physical interface is down

Signed-off-by: Aneesh Puttur<EMAIL_ADDRESS>This PR sets CLOCK_REALTIME to FREERUN when master is in HOLDOVER OR AT FAULT

/jira refresh

/cherry-pick release-4.12


issue on IE browser rendr app    : Undefined modelName for model

I have used rendr app . But it is not working IE browser as i include
<!--[if lte IE 9]>

 <script src="http://code.jquery.com/jquery-1.9.0.js"></script>
  <script src="http://code.jquery.com/jquery-migrate-1.2.1.js"></script>

<![endif]-->

<!--[if !IE]> -->

<script src="http://ajax.googleapis.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>

as well as this one also
https://github.com/es-shims/es5-shim
And I am facing following issue IE browser
: Undefined modelName for model
here is code  for issue is coming up .
ModelStore.prototype = Object.create(Super.prototype);
ModelStore.prototype.constructor = ModelStore;
ModelStore.prototype.set = function(model) {
var existingAttrs, id, key, modelName, newAttrs;
id = model.get(model.idAttribute);
modelName = this.modelUtils.modelName(model.constructor);
if (modelName == null) {
throw new Error('Undefined modelName for model');
}

modelUtils.modelName is below.
ModelUtils.prototype.modelName = function(modelOrCollectionClass) {
  return this.underscorize(modelOrCollectionClass.id || modelOrCollectionClass.name);
};

But Function.prototype.name is unsupported by IE. (ES2015 standard), should be fixed.


Adds support for Duplicate mode on the Tenlog D3 Pro

This is accomplished by adding an M605 S2 to the start GCode, reducing the x printable area to 150mm, and making sure the same settings are operating across both print heads.
To use, add this as a new printer by copying to your Prusa "printers" subdirectory.

Thanks for the addition, @waleedkadous ! I'm giving it a test now.


Replaced "did you meant" with "did you mean".

The current version reads "Did you meant" in a bunch of places, which isn't proper English and makes Code Contracts look like a work in progress :)
The phrase "Did you mean indexing with x instead of y" still sounds odd, though. Maybe "Did you mean to index with" or "Did you mean index" would work better?

There are several more occurrences of "Did you meant" in .txt files in the Documentation\Papers\OOPSLA2012 folder...

@davidhesselbom For second comment: I'm not sure exactly, but maybe it was just a copy-paste.
Thanks for the fix.


Fix: volumemounts

Fix:

Attach volume created by VolumeClaimTemplate in StatefulSet spec
Add default fsGroup so volume can be accessed by clickhouse user
Scripts used in Makefile had wrong chart directory

Docs:

Update README.md by running make

@zumic96 thanks for your contribution, we will review this ASAP.

Thanks for the improvements @zumic96 ! Approved!


-s=ALL now getting "Source DoSI is unknown"

-s=ALL now getting "Source DoSI is unknown"
Have the latest dataset from 5eTools and DOSI definately exists in there - Any ideas please?
R.

Fancy a quick PR to add here: https://github.com/ebullient/json5e-convert-cli/blob/f47292d0e8c5bb733736dfdb361dceef4a99a9c8/src/main/java/dev/ebullient/json5e/tools5e/CompendiumSources.java#L149 ?

Also: things should still render, but DoSI won't be expanded to a nice name.

Thanks, yes confirmed that content showing up just that annoying error lol.
On Wed, 12 Oct 2022, 17:07 Erin Schnabel, @.***> wrote:

Also: things should still render, but DoSI won't be expanded to a nice
name.
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It may be annoying.. but it let me know that I have missing sources to go fix. ;)

Fab tool by the way, especially the templates.
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It may be annoying.. but it let me know that I have missing sources to go
fix. ;)
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Also I found a couple of spells that don't export correctly, best to log as
an issue?
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It may be annoying.. but it let me know that I have missing sources to go
fix. ;)
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yes, please!


[6.x] Fix Str::snake to handle wider range of input strings

Fixes problems with kebab-case to snake_case (and vice-versa) conversions.
Provides test for handling identifiers with numbers to establish the convention (see #28709 #28710).
Provides two new functions snakeIdent()/kebabIdent() which replace all non-alnum characters with '_'/'-'.
Multiple consecutive spaces are treated as single delimiter. Trailing spaces trim()med.
Handle unicode strings, including multibyte MixedCase like 'małaŻołtaŁódka'.

Yup. I think, it's ready. Stopping updating this PR here, for now.


rpm: build a repo and use it

Using a repository improves testing of podman installation instead of
using the bare rpm install method by using the likely installation
method used on production.

@edsantiago @NevilleC @cevich -- interestingly this uncovers a bug related to centos-8 where rhel8 where yum decides to install the distro version instead of our code. The same bug does not happen with centos-7 and fedora-30.
This makes me believe we have another spec issue. Advise would be welcomed.

If I may ask everyone to take a step back for a moment: what problem are we trying to solve?
Podman is an open-source project, not a Fedora-RHEL one. The little I understand of this PR is that it's intended for a narrow niche testing environment. Does this code really belong in the podman repo? Might there be a better place for it, more tightly integrated with the niche environment it's intended for?

@edsantiago @rhatdan @cevich I guess none of you tried to run even the most based sudo make help, which produces somethink like:
 sudo make help
<EMAIL_ADDRESS>Permission denied (publickey).
fatal: Could not read from remote repository.

Please make sure you have the correct access rights
and the repository exists.
<EMAIL_ADDRESS>Permission denied (publickey).
fatal: Could not read from remote repository.

Please make sure you have the correct access rights
and the repository exists.
Usage: make <target>

Based on this I would say that other things need to be addressed before we can remove sudo from inside the makefile.

@ssbarnea Still working on this?

Friendly ping.

Going to close. Please reopen if the PR is still desired.


Why is this repo using AutoFac instead of .NET's own DI infrastructure?

Why is this repo using AutoFac instead of .NET's own DI infrastructure?
If the repo had a discussion or a question area, I could have asked this question there. Also, I don't think Stackoverflow is the right place to ask this question since it's pretty much directed to the author.

Hi @Tony20221 this is fine to ask here. I'm not turning on Discussions mainly because I don't want one more place to have to check.
To answer your question, and probably this would be a good opportunity to include an ADR, I used Autofac when the .NET DI container was still pretty new and not full-featured. I've used Autofac for longer than .NET Core has existed, and it's a very mature and stable library that has a lot of nice capabilities. Being able to put modules close to the dependencies (in the same project as the implementation classes) is one such capability, though of late it seems the de facto .NET standard is to achieve something similar using extension methods. Autofac also has nicer support for things like decorators, but out of the box I'm not using that capability here.
To be honest I have been considering removing Autofac from this template for a while now. I'm not sure it adds enough to support the extra files and concepts and dependencies it brings. I'm curious to know how others feel about that. Leave a comment or a 👍 or 👎 on this comment to show you prefer Autofac (👍 ) or not (👎 ).

Yeah, the votes are pretty evident here. I'm going to remove Autofac.

Just to add my 2 cents, I agree that an ADR would be good to add for this decisioning and it's important to note that community feedback was considered for the change (especially since it was overwhelmingly weighted to one outcome).


Standardize code block syntax highlighting

What's this PR do?
Switches code blocks on the Specification page from json to javascript to improve the syntax highlighting.
Background context
This is a follow-up to PR #702 and should replace it. The discussion in that PR ended with the consensus to switch the code blocks to javascript, rather than modifying the content to appease the JSON syntax highlighter.
Many of the examples are partial JSON data structures or contain JS-style comments. The JSON syntax highlighter does not handle them very well, often not applying any highlighting at all. The JS highlighter does a better job with these code blocks.
Not all of the code blocks need to be marked as JS; some of them are perfectly valid JSON. It's my opinion that it's best to be consistent so that future contributors don't need to guess at which syntax highlighter to use, so I've marked them all as JS.

@tkellen You requested a FAQ entry for this issue. I haven't added one yet because it seemed a little out of place. The existing entries seem to answer questions about the spec itself, rather than the code used in the website. What do you think?

Haha! I was kidding, I should've left a note saying I was being sarcastic :p

Where's the sarcmark when you need it? :-)

So, I looked into this more today, and marking everything as JS, which I realize I suggested, actually brings its own troubles. The biggest issue is that, when js highlighting is used, the keys and the values in object literals seem to get classified the same way, so there's no way to distinguish them visually (as in the JSON highlighting). That's a big loss imo. Then there were other issues, like: even if we tag all the blocks as JS, the json that's inside http blocks still gets tagged (automatically on the client) as json and so ends up looking inconsistent.
After playing around with this, the only solution that I could get to work was:

Mark all the blocks (even those with comments) as json in the markdown
That'll force highlight.js (which runs on the client and actually does most of the highlighting work, confusingly enough) to treat every block as json, giving us nice key/value distinctions and http block consistency. (We're using highlight.js, I think, since it seems to apply much more informative class names.)
Then, if highlight.js catches a syntax error, assume that that "error" is a comment in json, and style it like a comment.

In the process of playing around with this, I ended up making all of the changes myself in the uniform-syntax-highlighting branch. So this PR isn't really needed anymore (sorry; I know that's annoying), but I'll make a new one for my changes and your feedback/further refinements there would be awesome.


updated Kotlin to 1.6.10, Android target SDK to 31, Android Gradle Plugin to 7.1.0 & dependencies

@nbransby The build seems to be stuck, might wanna re-run this.

@nbransby / @Reedyuk  - Can you guys review/merge this? I have another PR that will add support for other Apple platforms :)

@nbransby 👋

Done!
Hopefully you won't freak out when you'll see the next PR ;)

Compiling this version of the code results in:
> Task :firebase-auth:compileTestDevelopmentExecutableKotlinJsIr
e: Module "dev.gitlive:firebase-auth" has a reference to symbol dev.gitlive.firebase.auth/FirebaseUser.displayName.<get-displayName>|-7122534302014937473[1]. Neither the module itself nor its dependencies contain such declaration.

which seems to caused by https://youtrack.jetbrains.com/issue/KT-48836.
Changing in FirebaseUser:
suspend fun updateProfile(displayName: String? = this.displayName, photoUrl: String? = this.photoURL)

to
suspend fun updateProfile(displayName: String?, photoUrl: String?)

works around the issue.

@nbransby / @rocketraman - I can repro the compilation error & I applied the fix.

@nbransby everything's ready

@nbransby 👋

jsut waiting on #286 so we can do one more 1.5 based release before upgrading to 1.6

Is there even a issue for it on youtrack?
On Thu, 3 Nov 2022, 23:46 Raman Gupta, @.***> wrote:

@.**** commented on this pull request.
In firebase-auth/src/commonMain/kotlin/dev/gitlive/firebase/auth/user.kt
https://github.com/GitLiveApp/firebase-kotlin-sdk/pull/277#discussion_r1013491650
:

@@ -28,7 +28,7 @@ expect class FirebaseUser {
suspend fun updateEmail(email: String)
suspend fun updatePassword(password: String)
suspend fun updatePhoneNumber(credential: PhoneAuthCredential)

suspend fun updateProfile(displayName: String? = this.displayName, photoUrl: String? = this.photoURL)

suspend fun updateProfile(displayName: String? = null, photoUrl: String? = null)

Have they not fixed the underlying bug in the IR compiler yet?
No they haven't :(
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Is there even a issue for it on youtrack?

https://youtrack.jetbrains.com/issue/KT-48836


Bump tekton version to use 0.8

Feature request
Bump tekton version to use 0.8 - see new release : https://openshift.github.io/pipelines-docs/docs/docs/0.8/index.html

See PR #186


Ability to enumerate registered hooks

Description of the feature, modification, idea or suggestion
I think someone asked about this before in old PH forum, but I would like to have it here again since I feel like there are more capabilities with SystemInformer.
There is no application that I know of that has ability to enumerate and display global hooks. I imagine the reason is that the structure where these hooks are stored is undocumented and probably in kernel memory somewhere, but undocumented things don't stop SystemInformer, do they?
This capability would help to detect keyloggers or applications causing system instability. If one hooks WH_MOUSE_LL and returns from callback function with a delay, user will feel that delay in his cursor movement.
Proposed implementation details (optional)
No response

also related https://learn.microsoft.com/en-us/windows/win32/api/winuser/nf-winuser-registerhotkey , but thats a completely different thing that would require a completely different implementation

Ok nevermind this is where I remember seeing it - https://github.com/tigros/HookTools. I'm just gonna leave the issue in case you want to consider it for integration into SystemInformer


improve unicode-full.yaml

The file has a large number of private space entries that probably came from some old version of MathType where it couldn't write the plane 1 unicode values. I tried a somewhat old version of MathType and it is using mathvariant. The private unicode ones should be flushed as they take up more space and more time to read them in.
Also, in the alphanumeric block, there are a lot of entries like
- "𝚊": [t: a]                                   # 0x1d68a

and
 - "𝙰":                                          # 0x1d670
     - t: ""
     - test:
         if: "($Blind or $Verbosity!='Terse')"
         then: {t: cap}
     - t: a

These should be changed to be more like the entries for the regular letters:
 - "b-z":
    - test:
        if: "$TTS='none'"
        then: [t: "."]
        else: [spell: "."]

 - "B-Z":
    - test:
        if: "$TTS='none'"
        # note: processing of ranges converts '.' into the character, so it needs to be in quotes below
        then: [x: "$CapitalLetters", x: "translate('.', 'BCDEFGHIJKLMNOPQRSTUVWXYZ', 'bcdefghijklmnopqrstuvwxyz')"]
        else: {spell: "."}

These will take advantage of the speech engines appropriately. It will also shorten the file some, but probably not change read time much since the range needs to get expanded. Still probably faster than I/O.
It would be good to do these for the Greek letters also. However, I don't think ranges can be used because each Greek letter needs to be named.  I need to see what the speech engines do if I give them a Greek letter and tell them to interpret-as='characters' (the SSML command). If that works across all the speech engines (including Eloquence), then the range can be used.

This was done several months back. The file shrank by 2/3!  The read time dropped a few milliseconds.


Can we crop PDF Also

How to crop a pdf file like an image.

pdf is not an image file, so it can't be cropped.


Add filter property to clr-tree-node

Summary
Add possibility to filter tree nodes in clarity recursive tree. In simple case I would use *ngIf  in wrapped ng-container directive to filter some tree nodes but in this case it's impossible because nothing is shown.

What is the change?
Add property to clr-tree-node to filter nodes.

Why should it go in Clarity?
Now it is impossible to filter tree nodes in recursive trees in templates.

Does this change impact existing behaviors? If so how?
No, it doesn't.

If this change introduces a new behavior, is this behavior accessible?
Yes.

Use case
I have a tree. I would like to filter it by condition in template without extra fields and methods in component.
Examples
see https://stackoverflow.com/questions/56971793/use-ngif-to-filter-tree-nodes-in-clarity-recursive-tree
Workarounds
Create another field in template (e.g. displayedNodes) and filter existing nodes there.

Related (though no fully equivalent) to https://github.com/vmware/clarity/issues/3603

The feature request here has been captured into our list and we’re going to take it into consideration as we develop Clarity Core capabilities. In an effort to clean up our backlog and focus our attention, I’m going to close this as captured in our feature requests. Please follow our development and releases to see when we release relevant components to make this possible. Future feature requests can be made in our GitHub Discussions.


Swiping a direction="vertical" Scene down only by its header or custom component

Version
Tell us which versions you are using:

react-native-router-flux v3.37.0
react-native v0.40.0

Expected behaviour
There should be a way to turn on the ability to swipe a modal down only by its header or specific custom component while ignoring modal swipe gestures on the content itself. This will be ideal behavior when there is a ScrollView in the Scene, for example.
Actual behaviour
When you are in a modal Scene (direction="vertical") that has a ScrollView, using panHandlers={null} on the Scene allows the ScrollView to be used without bugs, but swiping the header down doesn't do anything.
Alternatively, not using panHandlers={null} on the Scene makes the whole Scene movable, but creates unexpected behavior if there's a ScrollView within the Scene. In this scenario, only moving the ScrollView slowly works. Flicking down the ScrollView dismisses the Scene. Flicking it up just freezes the ScrollView for a second.
Steps to reproduce

Create a second Scene with direction="vertical" and panHandlers={null} and add a ScrollView with a bunch of items to its component.
Go to this scene using Actions.key, for example.
Try to swipe/flick the ScrollView (should work). Swiping the header down won't do anything.
Remove panHandlers={null} from the Scene and go to it again.
You can swipe the modal by its header to dismiss but the ScrollView will be wonky as described above.

this is a huge problem, we should be able to control edgeHitWidth


Database Changes - Setup Instructions

Change:
php artisan love:setup-reacterable --model="App\User"

To:
php artisan love:setup-reacterable --model="App\Models\User"

Models could be anywhere you want. Models directory is a pretty new standard in Laravel, earlier it was in the app root.

@JD456976 Fixed it, thanks!

Very welcome!
Thank you for all your work on your package!

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Closed #213 https://github.com/cybercog/laravel-love/issues/213 as completed.
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Implement nats

Pull request for #19

@nmtien anything left to do here?

Should i merge, nothing left from me.


Feature: Talent Bonuses

Currently, Ability Score Improvements are supported using Talents. And the groundwork is there for building a more complete set of support for talents.
The following types of talents needs design for both data models as well as how to implement using talents.

Weapon Mastery
Armor +1 AC bonus (it now applies a general AC bonus, assuming the player has the mastery armor on)
Hauler (Enable adding CON mon to gear slots)
Advantage to casting a selected spell

The following talents needs to jacked up to the Dice Mechanics:

+1 to melee and ranged attacks
+2 to melee OR ranged attacks (Priest)
+1 to spellcasting checks
+1 damage die on Backstab

Nice to have:

Dialog asking for type of Ability Score Improvement

From Muttley on Discord:

meleeAttackBonus, meleeDamageBonus, rangedAttackBonus, rangedDamageBonus
Talents may have advantage on HP rolls

Hauler can be built as a custom talent, but everything else should have the baseline piping with the PR coming up in a second.

Current version of Hauler is just using a numerical value for add to gearSlots and needs to be fixed.

The backstabBonusDie needs fixing as well.


⚠ T:Riza Docs has degraded performance

In fde43a0, T:Riza Docs (https://docs.triza.dev) experienced degraded performance:

HTTP code: 404
Response time: 5566 ms

Resolved: T:Riza Docs performance has improved in aff43f1.


How can i convert with Buffer

Like this shader https://www.shadertoy.com/view/MscGWX
Im new in shader and dont know how to use your shader converter.
Thank for your tools.

How can i convert with Buf to How can i convert with Buffer

Shader "ShaderToy/BufferTest"
{
	Properties
	{
		iChannel0 ("iChannel1", 2D) = "white" {}
		iChannel1 ("iChannel2", 2D) = "white" {}

	}
	SubShader
	{
		// No culling or depth
		Cull Off ZWrite Off ZTest Always

		Pass
		{
			CGPROGRAM
			#pragma vertex vert
			#pragma fragment frag

			#include "UnityCG.cginc"

			sampler2D iChannel0;
			sampler2D iChannel1;
			sampler2D _MainTex;

			struct appdata
			{
				float4 vertex : POSITION;
				float2 uv : TEXCOORD0;
			};

			struct v2f
			{
				float2 uv : TEXCOORD0;
				float4 vertex : SV_POSITION;
			};

			//Buf A
			float4 BufACalculate(float2 uv){
			float2 px = 4.0/float2(640.0,360.0);
			float4 tex = pow(tex2D(iChannel0,float4(uv,0,0))*1.3,1.8);
			float d = 1.0-smoothstep(0.0,0.08,length(tex));
			//float d = abs(tex.g - newG);
			//tex.g = newG * 0.9;
			if (d > 0.0)
			{
				//px*= sin(iTime+uv.yx*3.0)*.35;
				uv -= 0.5*px;
				float4 tex2 = tex2D(iChannel1,float4(uv,0,0));
				uv += px;
				tex2 += tex2D(iChannel1,float4(uv,0,0));
				uv.x -= px.x -.018 *sin(_Time.y*4.1+tex2.r);
				uv.y += px.y +.015 * cos(_Time.y*4.1+tex2.g);
				tex2 += tex2D(iChannel1,float4(uv,0,0));
				uv.y -= px.y;
				tex2 += tex2D(iChannel1,float4(uv,0,0));
				tex2 /= 4.013;
				tex2 = clamp(tex2*1.02-0.012,0.0,1.0);
				tex = max(clamp(tex*(1.0-d),0.0,1.0),lerp(tex,tex2,smoothstep(-1.3,0.23,d)));
			}
			float4 fragColor = tex;
			return fragColor;
			}

			//Buf B
			float4 BufBCalculate(float2 uv){

				fixed4 col = tex2D(_MainTex, uv);
				float2 px = 2.5 / float2(640.0,360.0);
				float4 tx = tex2D(iChannel1,float4(uv,0,0));
				float dist = distance(tx,tex2D(iChannel1,float4(uv+px,0,0)));
				px.y *= -1.0;
				dist += distance(tx,tex2D(iChannel1,float4(uv+px,0,0)));
				px.x *= -1.0;
				dist += distance(tx,tex2D(iChannel1,float4(uv+px,0,0)));
				px.y *= -1.0;
				dist += distance(tx,tex2D(iChannel1,float4(uv+px,0,0)));
				uv = mul(uv,float2x2(0.999,0.001,-0.001,0.999));
				 float4 fragColor = tex2D(iChannel0,float4(uv*0.995+0.0025,0,0))*float4(0.93,0.91,0.0,0.0)+
					float4(smoothstep(0.05,1.3,dist),smoothstep(0.1,2.8,dist),0.0,1.0)*.245;
			return fragColor;
			}

			v2f vert (appdata v)
			{
				v2f o;
				o.vertex = UnityObjectToClipPos(v.vertex);
				o.uv = v.uv;

				return o;
			}

			//Image
			fixed4 frag (v2f i) : SV_Target
			{

				float4 fragColor = max(BufACalculate(i.uv),BufBCalculate(i.uv));
				return fragColor;
			}
			ENDCG
		}
	}
}

I already have discussed same questions about Buffers maybe useful.

SmkGames<EMAIL_ADDRESS>SmkGames<EMAIL_ADDRESS>Nov 21

SmkGames<EMAIL_ADDRESS>

Hi.
Currently I can translate successfully about 90 percents of Shadertoy shaders to Unity.
My last challenge is trying to translate also shaders where is used self accumulated buffers.
Example:
https://www.shadertoy.com/view/ll2cRG
Accumulation.cs and rend.shader contain partial solution. Image buffer is accumulated, but shader doesn't work as expected (fluids are moved  into left down corner of screen).
For testing purposes, I kept GLSL syntax, so you have to run Unity in OpenGL mode.(run unity with -force-opengl)
Maybe you will have fresh ideas to fix this :)
All the best,
P.Z.

//source: https://www.shadertoy.com/view/ll2cRG
Shader "rend"
{
	Properties
	{
		_MainTex ("Texture Image", 2D) = "black" {}
	}
	SubShader
	{
		Pass
		{
			GLSLPROGRAM

			uniform vec4 _ScreenParams;
			uniform sampler2D _MainTex;

			#ifdef VERTEX
				varying vec2 texcoord;
				void main()
				{
					gl_Position = gl_ModelViewProjectionMatrix * gl_Vertex;
					texcoord = gl_MultiTexCoord0.xy;
				}
			#endif

			#ifdef FRAGMENT
				varying vec2 texcoord;

				void main()
				{
					vec2 iResolution = _ScreenParams.xy;
					vec2 f = vec2 (gl_FragCoord.x,gl_FragCoord.y);
					vec2 b = vec2(0.31,0.95);
					vec2 v = vec2(0.0,0.0);
					for(int l=0;l<20;l++)
					{
						if ( dot(b,b) > pow(iResolution.y,2.0) ) break;
						vec2 p = b;
						for(int i=0;i<5;i++)
						{
							vec2 pos = f+p ;
							float rot=0.0;
							for(int i=0;i<5;i++)
							{
								rot+=dot(texture(_MainTex,fract((pos+p)/iResolution.xy)).xy-vec2(0.5),p.yx*vec2(1,-1));
								p=vec2(0.31*p.x+0.95*p.y,-0.95*p.x+0.31*p.y);
							}
							v+=p.yx* rot/5.0/dot(b,b);
							p=vec2(0.31*p.x+0.95*p.y,-0.95*p.x+0.31*p.y);
						}
						b*=2.0;
					}
					vec4 color=texture(_MainTex,fract((f+v*vec2(-2,2))/iResolution.xy));
					vec2 s=(f.xy/iResolution.xy)*2.0-vec2(1.0);
					color.xy += (0.01*s.xy / (dot(s,s)/0.1+0.3));
					gl_FragColor = color;
				}
			#endif

			ENDGLSL
		}
	}
}

accumulation.cs
//Assign script to main camera, then bind material with accumulation.shader
//It draws fullscreen quad. Shader output is set as shader input for next frame.
using UnityEngine;
using System.Collections;

public class accumulation : MonoBehaviour
{
	public Material material;

	void OnPostRender()
	{
		GL.PushMatrix();
		material.SetPass(0);
		GL.LoadOrtho();
		GL.Begin(GL.QUADS);
		GL.TexCoord2(0, 0);
		GL.Vertex3(0.0F, 0.0F, 0);
		GL.TexCoord2(0, 1);
		GL.Vertex3(0.0F, 1.0F, 0);
		GL.TexCoord2(1, 1);
		GL.Vertex3(1.0F, 1.0F, 0);
		GL.TexCoord2(1, 0);
		GL.Vertex3(1.0F, 0.0F, 0);
		GL.End();
		GL.PopMatrix();
		Texture2D buffer = new Texture2D(Screen.width, Screen.height);
		buffer.ReadPixels(new Rect(0, 0, Screen.width, Screen.height), 0, 0);
		buffer.Apply();
		material.mainTexture = buffer;
	}
}

Hi Dear Friend
I'm happy that my project was useful for you.
cool! it worked
I know what is your problem.
you shouldn't use _ScreenParams ... instead of it use uvcoordinate
float2 uv = i.vertex.xy/_ScreenParams.xy; //THIS IS YOUR PROBLEM!!! SPACING VIEW
float2 uv = i.texcoord.xy;

I attach two shader that will help you to understanding you shouldn't use _ScreenParams
this will help you:
https://en.wikibooks.org/wiki/GLSL_Programming/Unity/Minimal_Shader
I know very little about buffers
but i tried to convert

Shader"Zaworski/Fluid"{
Properties{
_MainTex("_MainTex", 2D) = "white"{}
_Distortion("Distortion",Range(0,1)) = 0
}
SubShader{
Pass{
CGPROGRAM
#pragma vertex vert
#pragma fragment frag
#pragma fragmentoption ARB_precision_hint_fastest
#include "UnityCG.cginc"
struct appdata{
float4 vertex : POSITION;
float2 uv : TEXCOORD0;
};

float _Distortion;
sampler2D _MainTex;

struct v2f
{
float2 uv : TEXCOORD0;
float4 vertex : SV_POSITION;
float4 screenCoord : TEXCOORD1;
};

v2f vert(appdata v)
{
v2f o;
o.vertex = UnityObjectToClipPos(v.vertex);
o.uv = v.uv;
return o;
}
fixed4 frag(v2f input) : SV_Target{
{
    fixed2 b = fixed2(0.31,0.95);
    fixed2 v = fixed2(0.0,0.0);
for(int l=0;l<20;l++)
    {
        if ( dot(b,b) > pow(1,2.0) ) break;
        fixed2 p = b;
for(int i=0;i<5;i++)
        {
        	fixed2 pos = input.uv+p ;
        	fixed rot=0.0;
for(int i=0;i<5;i++)
        	{
            	rot+=dot(tex2D(_MainTex,frac((pos+p)/1)).xy-fixed2(0.5,0.5),p.yx*fixed2(1,-1));
            	p=fixed2(0.31*p.x+0.95*p.y,-0.95*p.x+0.31*p.y);
        	}
        	v+=p.yx* rot/5.0/dot(b,b);
        	p=fixed2(0.31*p.x+0.95*p.y,-0.95*p.x+0.31*p.y);
        }
        b*=2.0;
    }
    fixed4 color=tex2D(_MainTex,frac((input.uv+lerp(0,v,_Distortion)*fixed2(-2,2))));
    fixed2 s=(input.uv.xy)*2.0-fixed2(1.0,1.0);
    color.xy += (0.01*s.xy / (dot(s,s)/0.1+0.3));
	return color;
}
}ENDCG
}
}
}

See this topic:
https://forum.unity.com/threads/converting-a-shadertoy-multipass-shader-to-unity-hlsl.418238/
post number #19.

https://forum.unity.com/threads/converting-a-shadertoy-multipass-shader-to-unity-hlsl.418238/
post number #19.

Amazing!!!

Yes, for normal shaders we should use trick with two render textures swapping once again. Now functions:
https://docs.unity3d.com/ScriptReference/Material.SetTexture.html
and
https://docs.unity3d.com/ScriptReference/Graphics.Blit.html
should be helpful.
I will post solution today later, now I have to eat dinner :)

https://docs.unity3d.com/ScriptReference/Material.SetTexture.html
and
https://docs.unity3d.com/ScriptReference/Graphics.Blit.html

that's right but i think using Rendertexture and set it each frame isn't optimal way.
is it possible we do all in shader? storing  one Pass into the Texture and using it instead of Rendertexture

Solution without compute shader:
https://forum.unity.com/threads/converting-a-shadertoy-multipass-shader-to-unity-hlsl.418238/
post number #22.

Now I am working to implement multi buffers shaders, like this one:
https://www.shadertoy.com/view/MssyDf

Graphics.Blit also can have additional parameter where you can set given shader pass only. So it can help with many buffers to improve performance.
public static void Blit(Texture source, RenderTexture dest, Material mat, int pass = -1);

Examples of multibuffer shaders from Shadertoy to Unity:
https://github.com/przemyslawzaworski/Unity3D-CG-programming/tree/master/Multipass

Hi dear przemyslawzaworski what's up
👍 Nice!
[image: image.png]
On Wed, Jul 3, 2019 at 3:05 PM Przemyslaw Zaworski<EMAIL_ADDRESS>wrote:

Examples of multibuffer shaders from Shadertoy to Unity:
https://github.com/przemyslawzaworski/Unity3D-CG-programming/tree/master/Multipass
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