f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(579): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=int16_t]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(580): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=int]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(581): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=int64_t]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(582): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=c10::Half]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(583): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=float]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(584): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=double]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(585): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=c10::ComplexHalf]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(586): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::complex]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(587): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::complex]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(590): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::string]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(591): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=__nv_bool]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(592): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=uint16_t]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(593): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=char]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(594): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::unique_ptr<std::mutex, std::default_deletestd::mutex>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(595): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::unique_ptr<std::atomic<__nv_bool>, std::default_delete<std::atomic<__nv_bool>>>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(596): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::vector<int32_t, std::allocator>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(597): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::vector<int64_t, std::allocator<int64_t>>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(598): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::vector<unsigned long, std::allocator>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(599): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=__nv_bool *]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(600): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=char *]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(601): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=int *]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(621): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=caffe2::detail::_guard_long_unique]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(622): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=caffe2::detail::_guard_long_unique<std::vector<long, std::allocator>>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(626): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=c10::qint8]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(628): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=caffe2::_CaffeHighestPreallocatedTypeId]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/intrusive_ptr.h(58): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/intrusive_ptr.h(59): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/Storage.h(181): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/logging_is_not_google_glog.h(47): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(193): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(1466): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(1476): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(1477): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(1499): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/core/Tensor.h(773): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/core/Tensor.h(801): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(151): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(152): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(153): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(157): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(158): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(159): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/TensorGeometry.h(56): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/TensorGeometry.h(57): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(54): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(55): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(56): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(57): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(58): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(59): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/Exception.h(27): warning: base class dllexport/dllimport specification differs from that of the derived class
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/Exception.h(28): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/Exception.h(29): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/Exception.h(34): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/Exception.h(35): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/Allocator.h(21): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/Allocator.h(183): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorTypeIdRegistration.h(32): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorTypeIdRegistration.h(45): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorTypeIdRegistration.h(46): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(456): warning: dllexport/dllimport conflict with "caffe2::TypeMeta::_typeMetaDataInstance [with T=caffe2::detail::_Uninitialized]"
(452): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(577): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=uint8_t]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(578): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=int8_t]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(579): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=int16_t]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(580): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=int]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(581): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=int64_t]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(582): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=c10::Half]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(583): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=float]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(584): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=double]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(585): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=c10::ComplexHalf]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(586): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::complex]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(587): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::complex]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(590): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::string]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(591): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=bool]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(592): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=uint16_t]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(593): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=char]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(594): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::unique_ptr<std::mutex, std::default_deletestd::mutex>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(595): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::unique_ptr<std::atomic, std::default_delete<std::atomic>>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(596): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::vector<int32_t, std::allocator>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(597): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::vector<int64_t, std::allocator<int64_t>>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(598): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=std::vector<unsigned long, std::allocator>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(599): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=bool *]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(600): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=char *]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(601): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=int *]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(621): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=caffe2::detail::_guard_long_unique]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(622): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=caffe2::detail::_guard_long_unique<std::vector<long, std::allocator>>]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(626): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=c10::qint8]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/typeid.h(628): warning: dllexport/dllimport conflict with "caffe2::TypeIdentifier::Get [with T=caffe2::_CaffeHighestPreallocatedTypeId]"
(81): here; dllexport assumed
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/intrusive_ptr.h(58): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/intrusive_ptr.h(59): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/Storage.h(181): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/util/logging_is_not_google_glog.h(47): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(193): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(1466): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(1476): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(1477): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/TensorImpl.h(1499): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/core/Tensor.h(773): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/core/Tensor.h(801): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(151): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(152): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(153): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(157): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(158): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/Context.h(159): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/TensorGeometry.h(56): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\ATen/TensorGeometry.h(57): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(54): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(55): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(56): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(57): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(58): warning: field of class type without a DLL interface used in a class with a DLL interface
f:/anaconda/envs/torch36/lib/site-packages/torch/include\c10/core/thread_pool.h(59): warning: field of class type without a DLL interface used in a class with a DLL interface
scatter_kernel.cu
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\BIN\x86_amd64\link.exe /nologo /INCREMENTAL:NO /LTCG /DLL /MANIFEST:EMBED,ID=2 /MANIFESTUAC:NO /LIBPATH:f:\anaconda\envs\torch36\lib\site-packages\torch\lib "/LIBPATH:C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\lib/x64" /LIBPATH:f:\anaconda\envs\torch36\libs /LIBPATH:f:\anaconda\envs\torch36\PCbuild\amd64 "/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\LIB\amd64" "/LIBPATH:C:\Program Files (x86)\Windows Kits\10\lib\10.0.10240.0\ucrt\x64" "/LIBPATH:C:\Program Files (x86)\Windows Kits\8.1\lib\winv6.3\um\x64" cudart.lib c10.lib c10_cuda.lib caffe2.lib torch.lib torch_python.lib caffe2_gpu.lib C.lib /EXPORT:PyInit_scatter_cuda build\temp.win-amd64-3.6\Release\cuda/scatter.obj build\temp.win-amd64-3.6\Release\cuda/scatter_kernel.obj /OUT:build\lib.win-amd64-3.6\torch_scatter\scatter_cuda.cp36-win_amd64.pyd /IMPLIB:build\temp.win-amd64-3.6\Release\cuda\scatter_cuda.cp36-win_amd64.lib
scatter.obj : warning LNK4197: export 'PyInit_scatter_cuda' specified multiple times; using first specification
Creating library build\temp.win-amd64-3.6\Release\cuda\scatter_cuda.cp36-win_amd64.lib and object build\temp.win-amd64-3.6\Release\cuda\scatter_cuda.cp36-win_amd64.exp
Generating code
Finished generating code
installing to build\bdist.win-amd64\wheel
running install
running install_lib
creating build\bdist.win-amd64
creating build\bdist.win-amd64\wheel
creating build\bdist.win-amd64\wheel\test
copying build\lib.win-amd64-3.6\test\test_backward.py -> build\bdist.win-amd64\wheel.\test
copying build\lib.win-amd64-3.6\test\test_forward.py -> build\bdist.win-amd64\wheel.\test
copying build\lib.win-amd64-3.6\test\test_max_min.py -> build\bdist.win-amd64\wheel.\test
copying build\lib.win-amd64-3.6\test\test_multi_gpu.py -> build\bdist.win-amd64\wheel.\test
copying build\lib.win-amd64-3.6\test\test_std.py -> build\bdist.win-amd64\wheel.\test
copying build\lib.win-amd64-3.6\test\utils.py -> build\bdist.win-amd64\wheel.\test
copying build\lib.win-amd64-3.6\test_init.py -> build\bdist.win-amd64\wheel.\test
creating build\bdist.win-amd64\wheel\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\add.py -> build\bdist.win-amd64\wheel.\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\div.py -> build\bdist.win-amd64\wheel.\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\max.py -> build\bdist.win-amd64\wheel.\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\mean.py -> build\bdist.win-amd64\wheel.\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\min.py -> build\bdist.win-amd64\wheel.\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\mul.py -> build\bdist.win-amd64\wheel.\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\scatter_cpu.cp36-win_amd64.pyd -> build\bdist.win-amd64\wheel.\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\scatter_cuda.cp36-win_amd64.pyd -> build\bdist.win-amd64\wheel.\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\std.py -> build\bdist.win-amd64\wheel.\torch_scatter
copying build\lib.win-amd64-3.6\torch_scatter\sub.py -> build\bdist.win-amd64\wheel.\torch_scatter
creating build\bdist.win-amd64\wheel\torch_scatter\utils
copying build\lib.win-amd64-3.6\torch_scatter\utils\ext.py -> build\bdist.win-amd64\wheel.\torch_scatter\utils
copying build\lib.win-amd64-3.6\torch_scatter\utils\gen.py -> build\bdist.win-amd64\wheel.\torch_scatter\utils
copying build\lib.win-amd64-3.6\torch_scatter\utils_init_.py -> build\bdist.win-amd64\wheel.\torch_scatter\utils
copying build\lib.win-amd64-3.6\torch_scatter_init_.py -> build\bdist.win-amd64\wheel.\torch_scatter
running install_egg_info
running egg_info
writing torch_scatter.egg-info\PKG-INFO
writing dependency_links to torch_scatter.egg-info\dependency_links.txt
writing top-level names to torch_scatter.egg-info\top_level.txt
reading manifest file 'torch_scatter.egg-info\SOURCES.txt'
reading manifest template 'MANIFEST.in'
writing manifest file 'torch_scatter.egg-info\SOURCES.txt'
Copying torch_scatter.egg-info to build\bdist.win-amd64\wheel.\torch_scatter-1.3.1-py3.6.egg-info
running install_scripts
f:\anaconda\envs\torch36\lib\site-packages\wheel\pep425tags.py:83: RuntimeWarning: Config variable 'Py_DEBUG' is unset, Python ABI tag may be incorrect
warn=(impl == 'cp')):
f:\anaconda\envs\torch36\lib\site-packages\wheel\pep425tags.py:88: RuntimeWarning: Config variable 'WITH_PYMALLOC' is unset, Python ABI tag may be incorrect
sys.version_info < (3, 8)))
adding license file "LICENSE" (matched pattern "LICEN[CS]E*")
creating build\bdist.win-amd64\wheel\torch_scatter-1.3.1.dist-info\WHEEL
creating 'C:\Users\Wjk\AppData\Local\Temp\pip-wheel-1zjbjdwq\torch_scatter-1.3.1-cp36-cp36m-win_amd64.whl' and adding 'build\bdist.win-amd64\wheel' to it
adding 'test/init.py'
adding 'test/test_backward.py'
adding 'test/test_forward.py'
adding 'test/test_max_min.py'
adding 'test/test_multi_gpu.py'
adding 'test/test_std.py'
adding 'test/utils.py'
adding 'torch_scatter/init.py'
adding 'torch_scatter/add.py'
adding 'torch_scatter/div.py'
adding 'torch_scatter/max.py'
adding 'torch_scatter/mean.py'
adding 'torch_scatter/min.py'
adding 'torch_scatter/mul.py'
adding 'torch_scatter/scatter_cpu.cp36-win_amd64.pyd'
adding 'torch_scatter/scatter_cuda.cp36-win_amd64.pyd'
adding 'torch_scatter/std.py'
adding 'torch_scatter/sub.py'
adding 'torch_scatter/utils/init.py'
adding 'torch_scatter/utils/ext.py'
adding 'torch_scatter/utils/gen.py'
adding 'torch_scatter-1.3.1.dist-info/LICENSE'
adding 'torch_scatter-1.3.1.dist-info/METADATA'
adding 'torch_scatter-1.3.1.dist-info/WHEEL'
adding 'torch_scatter-1.3.1.dist-info/top_level.txt'
adding 'torch_scatter-1.3.1.dist-info/RECORD'
removing build\bdist.win-amd64\wheel
done
Created wheel for torch-scatter: filename=torch_scatter-1.3.1-cp36-cp36m-win_amd64.whl size=451809 sha256=59d9e669f7a55b55ef09b9399a399cab07474f1df4420f353e30c839976e14b9
Stored in directory: C:\Users\Wjk\AppData\Local\Temp\pip-ephem-wheel-cache-9ft7f1d_\wheels\7f\21\0b\c42fa9353ceec5e87464599e470a03e4250ec667b4a392fa7d
Removing source in C:\Users\Wjk\AppData\Local\Temp\pip-install-zmfwnc03\torch-scatter
Successfully built torch-scatter
Installing collected packages: torch-scatter
Successfully installed torch-scatter-1.3.1
Cleaning up...
Removed build tracker 'C:\Users\Wjk\AppData\Local\Temp\pip-req-tracker-9li3ynr9'
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Given no hashes to check 127 links for project 'pip': discarding no candidates
`

ohoh!!! I found I have install the torch_scatter successfully！ Thank you so much！！！

ohoh!!! I found I have install the torch_scatter successfully！ Thank you so much！！！
I had the same problem. How did  you tackle the problem? please give me some suggestions!


Data lost when pause and resume changefeed while executing drop table DDL.

What did you do?
All steps are in this integration case: https://github.com/pingcap/tiflow/blob/master/tests/integration_tests/batch_update_to_no_batch/run.sh

create changefeed c1.
drop table t1 in upstream
recover table t1 in upstream
insert a row r1 into t1
pause c1
resume c1

What did you expect to see?
row r1 can be replicated to downstream
What did you see instead?
there is no r1 in downstream
Versions of the cluster
Upstream TiDB cluster version (execute SELECT tidb_version(); in a MySQL client):
(paste TiDB cluster version here)

Upstream TiKV version (execute tikv-server --version):
(paste TiKV version here)

TiCDC version (execute cdc version):
master

When a changefeed is paused while there is a DDL executing, DDL's executing would be cancel, and ddlEventCache  would not be clean. While changefeed resume in auto retring, the DDL in ddlEventCache will be sent to downstream directly but not be applied to the schem of the changefeed.
So, changefeed will loss the tables, which lead to data lost.


Hostname for OTA

I like using the hostname for OTA, otherwise in the Arduino IDE port menu it shows up as a ESP8266xxxx....
In the Setup(), I added the line:
ArduinoOTA.setHostname((const char *)hostname.c_str());// added line
ArduinoOTA(begin);// original line
In the Arduino port menu it now shows "Octomon at xxx.xxx.xxx.xxx" or whatever the hostname is set to. Handy in the event you have a workshop full of ESP8266's...:-)
Mel

Thanks, I will add this.  This will be nice for the OTA people out there.  :)

I have added it to the branch 1.4 -- it will be the next release.   Thanks.  I will close this item.


Trignometry section missing calculator

Is your feature request related to a problem? Please describe.

Trignometry section missing the sin x,cos x,etc. calculator

Describe the solution you'd like

A calculator for providing instant calculated value for angle in radians and degrees. This can be achieved by using Math functions in js

Kindly assign this issue to me @sairish2001

I have raised to issue to address angles both in radians and degree

This is already implemented in Calculator.
it gives output for both radians and degrees


Huge delay in the video stream

**cordova-plugin-streaming-media version 1.0.2
**Cordova android version 6.2.3
**I am noticing a huge delay in the video stream. Comparing the results to the same stream being played on VLC, the delay between the VLC stream and the one in the app is around 3-4 seconds. Both are running on the same local network. Note that the native player on the mobile will keep loading for a few seconds before it begins to show the delayed video.
** Is there a way to reduce this delay? Usually in RTSP streams there is a way to define the delay time from the live video. Can that option be set anywhere?

**cordova-plugin-streaming-media version 1.0.2

You are using an outdated version of the plugin and cordova. Consider upgrading and see if the issue persists.
In order to receive an enhancement, you would need to update regardless.

I am closing this for now. The code plays the video as soon as it's available using Android's lifecycle methods


Grant access to mschell

We will begin updating some of the metadata here again.  First up is a data release with linked metadata for planimetrics 2022.

@mlipper granted me admin access.


Multiple Slides at once

How can i modify this to have say 3 items in the carousel at once? then cycle + or - one item when i click prev / next?

Could you please clarify your issue? What do you mean by "at once"? You can specify multiple slides, see Demo.

Sorry for the confusion. I am trying to show multiple items at once.
I am trying to show 3 slides at once on the page and cycle back and forth by one slide at a time instead of just cycling and displaying one slide at a time.

I think I know what you mean. A possible workaround is by adjusting the CSS I think


fix broken link for cli installation in mac instructions

@markusthoemmes want to patch and merge? Carlos is away.

merged 3f14be04835b7727355ec06e801b8e49ad54193f


majestic failed after attempt to connect from Onvifer

camera: IVG85HG50PYA-S
openipc.hi3516ev300-br.tgz
Commit: d9d0626
Branch: master
Tag: latest
Clean install by this man: https://github.com/OpenIPC/openipc-2.1/wiki/install_hisi
default /etc/majestic.yaml
steps to reproduce:

open in browser http://ip:8888/
video runs good
open stream
$ mpv rtsp://ip:554/stream=0
video runs good
open same rtsp://ip:554/stream=0 in android app Onvifer 15.27 (manual settings with transport protocol: TCP)
Fail

what happened:
majestic gone away (pid=781)
# cat /dev/kmsg
3,181,132920576,-;mmz_userdev:mmz_userdev_release:
0,182,132920598,-;MMB LEAK(pid=781): 0x45B80000, 249856 bytes, 'AENC(0)StrmBuf'
4,183,132920604,-;mmz_userdev:mmz_userdev_release:
0,184,132920609,-;mmb<0x45b80000> mapped to userspace 0xb5d32000 will be unmaped!
3,185,132920667,-;mmz_userdev:mmz_userdev_release:
0,186,132920673,-;MMB LEAK(pid=781): 0x420D4000, 16384 bytes, 'AENC(0) CirBuf'
4,187,132920675,-;mmz_userdev:mmz_userdev_release:
0,188,132920679,-;mmb<0x420d4000> mapped to userspace 0xb5d2e000 will be unmaped!

Expectation:
WDT should up majestic.
During boot it was initialized, but seems don't work.
Hisilicon Watchdog Timer: 0.01 initialized. default_margin=60 sec (nodeamon= 0)

Reboot helps until Onvifer 15.27 will be launched.
Also, after reboot majestic comes up and running and after single connection from Onvifer 15.27 same gone away.

Please also show free on your system

# free
              total        used        free      shared  buff/cache   available
Mem:         124224       85692       28600          96        9932       36980
Swap:             0           0           0

root@ipcam:~# killall majestic
root@ipcam:~# ulimit -c unlimited
root@ipcam:~# echo /tmp/%e.%p.%s.%t.core > /proc/sys/kernel/core_pattern
root@ipcam:~# majestic
17:37:03 [    main] main@143                     Majestic version master+5b7fec4, built on 2021-04-27
17:37:03 [app_conf] load_config@152              Using /etc/majestic.yaml as main configuration
17:37:03 [app_conf] parse_app_config@237         Autodetected sensor as 'imx335_i2c'
17:37:03 [app_conf] find_sensor_config@115       matched sensor config: imx335_i2c_4M_line.ini
17:37:03 [app_conf] find_sensor_config@125       Using /etc/sensors/imx335_i2c_4M_line.ini as sensor configuration
17:37:03 [  config] parse_int64@416              Can't parse param 'volume' value 'auto'. Is not a integer (dec or hex) number.
17:37:03 [    main] main@160                     app_config.max_pool_cnt 128
17:37:03 [    main] main@161                     app_config.blk_cnt 4
17:37:03 [   hisdk] start_sdk@1546               App was built with MPP version: Hi3516EV200_MPP_V<IP_ADDRESS>.B030 Release
17:37:03 [   hisdk] start_sdk@1549               Current MPP version: HI_VERSION=Hi3516EV200_MPP_V<IP_ADDRESS> B030 Release
17:37:03 [   hisdk] start_sdk@1559               chipid 3516E300
17:37:03 [   hisdk] start_sdk@1567               sensor_config.sensor_type stSnsImx335Obj
17:37:03 [   hisdk] start_sdk@1568               sensor_config.dll_file /usr/lib/sensors/libsns_imx335.so
17:37:03 [   hisdk] start_sdk@1569               sensor_config.dev_attr 2
17:37:03 [   hisdk] start_sdk@1571               sensor_config.vichn.pix_format 26
17:37:03 [   hisdk] start_sdk@1573               sensor_config.input_mode 0
17:37:03 [   hisdk] start_sdk@1574               sensor_config.mode 0
17:37:03 [   hisdk] start_sdk@1577               sensor_config.isp.isp_x 0
17:37:03 [   hisdk] start_sdk@1578               sensor_config.isp.isp_y 0
17:37:03 [   hisdk] start_sdk@1579               sensor_config.isp.isp_w 2592
17:37:03 [   hisdk] start_sdk@1580               sensor_config.isp.isp_h 1520
17:37:03 [   hisdk] start_sdk@1583               sensor_config.isp.isp_frame_rate 30
17:37:03 [   hisdk] start_sdk@1584               sensor_config.isp.isp_bayer 0
17:37:03 [  sensor] tryLoadLibrary@23            try to load: /usr/lib/sensors/libsns_imx335.so
17:37:03 [  sensor] tryLoadLibrary@25            libsns_so 0x00000000B6D24880
17:37:03 [   hisdk] free_mem@779                 Free MMZ mem before allocation: 98272KB
17:37:03 [   hisdk] init_mem@1676                u32AlignWidth: 64
17:37:03 [   hisdk] dump_vb_configuration@1651   VB configuration:
17:37:03 [   hisdk] dump_vb_configuration@1661     [0]: 5982720 x 7
17:37:03 [   hisdk] dump_vb_configuration@1661     [1]: 8375807 x 1
17:37:03 [   hisdk] dump_vb_configuration@1661     [4]: 345600 x 1
17:37:03 [   hisdk] free_mem@779                 Free MMZ mem after allocation: 48840KB
17:37:03 [   hisdk] init_sensor@1846             Sensor driver has been loaded
linear mode
binit false IMX335 i2c init
-------Sony IMX335_init_5M_2592x1944_12bit_linear30 Initial OK!-------
17:37:03 [   hisdk] init_vpss@2287               HI_MPI_SYS_Bind: VIU(0)->VPSS(grp 0)
17:37:03 [   hisdk] log_venc_chn@885             H.265 vpss_chn(0)->venc_chn(0)   2592x1520 25fps 4096Kbit
17:37:03 [   hisdk] create_vpss_chn@586            new venc: 0   vpss_grp: 0,   vpss_chn: 0
17:37:03 [   hisdk] create_vpss_chn@665            create_venc_chn  VPSS(0)->VENC(0)
17:37:03 [   hisdk] start_video@1272               venc took 15304KB of MMZ [2885]
17:37:03 [   hisdk] start_jpeg@794               JPEG snapshot venc_chn 1  2592x1520
17:37:03 [   hisdk] bind_vpss_venc@698             bind_vpss_venc  VPSS(0)->VENC(1)
17:37:03 [   hisdk] start_jpeg@876                 jpeg_enc took 3856KB of MMZ [3847]
17:37:03 [   audio] init_audio_in@592            Ai(0,0) bind to AencChn:0 ok!
17:37:03 [   hisdk] start_sdk@1636                 Audio took 512KB of MMZ
17:37:03 [   hisdk] start_sdk@1643               HiSilicon SDK has been started.
17:37:03 [   hisdk] free_mem@779                 Free MMZ mem finally: 22868KB
17:37:03 [image_pa] image_params_tuning@45       Image tuning thread has been started
17:37:03 [  evhttp] start_web_server@134         Using LAME v3.100
17:37:03 [  evhttp] start_web_server@194         HTTP server has been started on <IP_ADDRESS>:8888.
17:37:03 [    rtsp] rtsp_init@143                RTSP server started on port 554
17:37:07 [   hisdk] set_contrast@2667            Autoadjust image param cscAttrContrField from 50 to 90
╮                                     ╭╮
│                                     │╰╮
│                                    ╭╯ │
│                                   ╭╯  ╰╮
│                                ╭──╯    │
│                                │       ╰╮
│                             ╭─╮│        ╰╮
│                             │ ╰╯         │
│                            ╭╯            │
│                            │             │
│                           ╭╯             │
│                        ╭──╯              │
│                        │                 │
│                        │                 ╰╮
│                       ╭╯        ╭─╮ ╭╮    ╰╮ ╭──╮  ╭─╮
│           ╭╮         ╭╯  ╭╮    ╭╯ ╰─╯│╭╮   ╰─╯  ╰╮ │ │
│           ││        ╭─╮ ╭╯╰────╯     ╰╯│         ╰─╯ │
│           ││      ╭─╯╯╰─╯              ╰╮            │
│          ╭╯│    ╭─╯─╯                   ╰╮           ╰╮
│         ╭╯╭─────╯╭╯                      ╰╮╭╮         ╰───╮ ╭─╮╮
│       ╭╮│╭╯ │    │                        ╰╯╰───────────────╯ ╰╮╮
│    ╭──╯╰─╯  ╰────╯                                             ╰╮╮           ╭──╮
╰────╯    │                                                       ╰────────────╯  ╰──
──────────╯                                                          ╰───────────────

17:37:58 [    rtsp] listener_cb@118              New RTSP client from: <IP_ADDRESS>:46252
17:37:58 [rtsp_cli] RTSPClient_dispatch@239      RTSP DESCRIBE rtsp://<IP_ADDRESS>:554/stream=0 CSeq=0 from <IP_ADDRESS>:46252
17:37:58 [rtsp_cha] RTSPChannel_describe_sdp_video@263 RTSP chn 0 sps_len 0
17:37:58 [rtsp_cha] RTSPChannel_describe_sdp_video@266 RTSP chn 0 pps_len 0
17:37:58 [rtsp_cha] RTSPChannel_describe_sdp_video@273 RTSP chn 0 profile_level_id 000000
17:37:58 [rtsp_cli] RTSPClient_dispatch@239      RTSP SETUP rtsp://<IP_ADDRESS>:554/stream=0//video CSeq=1 from <IP_ADDRESS>:46252
17:37:58 [rtsp_cha] RTSPChannel_setup@182        TCP RTSP SETUP done, stream_id=0 from <IP_ADDRESS>:46252
17:37:59 [rtsp_cli] RTSPClient_dispatch@239      RTSP PLAY rtsp://<IP_ADDRESS>:554/stream=0 CSeq=2 from <IP_ADDRESS>:46252
Segmentation fault (core dumped)

majestic.806.11.1619707881.zip

camera: IVG85HG50PYA-S
openipc.hi3516ev300-br.tgz
Commit: d9d0626
Branch: master
Tag: latest

I have Onvifer 15.27 and the same problem with performance.
Try disabling the audio section in the configuration file.
And do the testing again. Thanks.

camera: IVG85HG50PYA-S
openipc.hi3516ev300-br.tgz
Commit: d9d0626
Branch: master
Tag: latest

I have Onvifer 15.27 and the same problem with performance.
Try disabling the audio section in the configuration file.
And do the testing again. Thanks.

Confirm, after disabling audio in /etc/majestic.yaml video still works after connect from Onvifer.
Thanks @ZigFisher for quick workaround!

Fixed in version master+1749648, built on 2021-05-13


Cody completion: Add initial tree-sitter utils

This is an early draft of tree-sitter adoption. This PR doesn't change anything about the current logic but tries to add some initial parsers API for our post-text procession flow.
Todo

[x] Add initial logic
[x] Add custom wasm loader script
[ ] Replace detectMultiline and multiline truncation logic with tree-sitter API (behind feature flag)

Note that we have to use wasm modules for tree sitter logic, and this adds some complexity, in case if you
have a better idea of how we can bring parsers into VSCode runtime, let me know, please 😉
Test plan

CI is green

Spent almost a whole day compiling wasm modules for JSX and TSX files (finally got them working properly). Just a note for me in future: If we want to make new wasm modules with the most updated parsers we need to solve the problem with tree-sitter CLI, at the moment it seems like it's broken when you try to compile the wasm module on Mac, (by default they try to compile everything in docker but it fails because of host OS). I did it manually this time but this flow isn't sustainable.

Spent almost a whole day compiling wasm modules for JSX and TSX files (finally got them working properly). Just a note for me in future: If we want to make new wasm modules with the most updated parsers we need to solve the problem with tree-sitter CLI, at the moment it seems like it's broken when you try to compile the wasm module on Mac, (by default they try to compile everything in docker but it fails because of host OS). I did it manually this time but this flow isn't sustainable.

This is awesome! Do you mind writing up your lessons learned into a small docs page for the contributing docs? 🙂

Just adding myself as a reviewer as I'm interested in this for some of the fixup work and will check this out later - not blocking!

@vovakulikov Makes sense! Is this PR ready for review (it's still in draft mode)

Ok,  It looks like all infra problems were solved. I'm going to merge this one and will follow up on improvements in further PRs. If you think that you need more info about the code that we're trying to complete, try to use parsers and let me know if there are some missing things in API.


Store main docstrings in the manifest

Refs

https://github.com/fractal-analytics-platform/fractal-common/issues/90
https://github.com/fractal-analytics-platform/fractal-server/issues/549
https://github.com/fractal-analytics-platform/fractal/issues/531

There need to exist new functions/scripts in in the dev subpackage, that implement the addition of docs_link and docs_info fields into each task of the manifest. I propose to follow the same logic that we use for parameters JSON Schemas:

A function that extracts the appropriate docstring (probably this can be a small modification of something that we already have)
A new_docs_info.py script (similar to new_args_schemas.py) that loops over all tasks from an existing manifest and updates the docs_info and docs_link entries in the corresponding manifest item. At the end of this script, the manifest is updated (on-disk), and it must be added/committed. This is the way to update the manifest when we update a given docstring or when we want to change docs_link.
A check_docs_info.py (similar to check_args_schemas.py) which has the same structure but only checks that the current on-disk manifest is up-to-date, rather than overwriting. This can be included in the GitHub action which currently runs check_args_schemas.py, to make sure we do not merge a PR with an out-of-sync manifest.

What should actually be written in the manifest?
link
docs_link: either a link the the docs homepage, or to the specific function. Note: docs are not version-specific, so that they will be out-of-sync in the future. I'd rather include a generic homepage link.
docstring
-- STOPPING HERE FOR THE MOMENT, WILL CONTINUE LATER --

In principle we can avoid new files creation because we can extend the function create_schema_for_single_task in fractal_tasks_core/dev/lib_args_schemas.py with an auxiliary function that put into the manifest docs_info and docs_link.
Is necessary another check?  Does the function _compare_dicts in fractal_tasks_core/dev/check_args_schemas.py already checks for missing keys in task args?

In principle we can avoid new files creation because we can extend the function create_schema_for_single_task in fractal_tasks_core/dev/lib_args_schemas.py with an auxiliary function that put into the manifest docs_info and docs_link.
Is necessary another check? Does the function _compare_dicts in fractal_tasks_core/dev/check_args_schemas.py already checks for missing keys in task args?

See https://github.com/fractal-analytics-platform/fractal-tasks-core/pull/486#issuecomment-1685779622. The two files are actually needed (or a single file, but with two different features).


README updates

Make description more descriptive
Add Spanner to supported list of datastores (marked as in beta)
Add "Have questions" section

Updated


unable to list/enumarate network interfaces through any means

There seems to be no way to enumerate networking interfaces. While I understand we can not and shouldn't be accessing raw sockets, it is nonetheless a common task to explore, via bash, what interfaces you have.  So, in addition to standard command line utils not working (ifconfig , "netstat" , "ip link") the real concern is that most python scripts that relay on this ability will fail.  This python code for example:
import netifaces
netifaces.interfaces()
Fails. This is going to nullify a lot of scripts out there who need to iterate through available interfaces.  Again, this is not to do anything low level, but it is a common procedure that a ton of legacy relies on.  Hopefully this will be added?

what's the error? probably a duplicate of https://github.com/Microsoft/BashOnWindows/issues/118

Yes, this looks like #118, #69 and few other network related posts. We are aware of the lack of support for NETLINK sockets and are looking into it, based on the feedback provided through the wpdev portal. Please provide your feedback\up vote feature requests @ https://wpdev.uservoice.com/forums/266908-command-prompt-console-bash-on-ubuntu-on-windo

I think it likely resolve to the same thing.  "Error 22, invalid argument."   As it is with issue 118, the python is really just calling into a shared library that is querying the network layer...so our failures are probably from the same source, which is also why netstat and "ifconfig" fail as well.
The error number probably comes from the failure of the underlying .so to return a python list but am not certain.  at the CC level I sure we just have a failure on the function that queries the network layer.  For completeness, here is the .C code for hat netifaces in python is calling into:
static PyObject *
interfaces (PyObject *self)
{
PyObject *result;
#if defined(WIN32)
PIP_ADAPTER_ADDRESSES pAdapterAddresses = NULL, pInfo = NULL;
ULONG ulBufferLength = 0;
DWORD dwRet;
/* First, retrieve the adapter information */
do {
dwRet = GetAdaptersAddresses(AF_UNSPEC, 0, NULL,
pAdapterAddresses, &ulBufferLength);
if (dwRet == ERROR_BUFFER_OVERFLOW) {
  if (pAdapterAddresses)
    free (pAdapterAddresses);
  pAdapterAddresses = (PIP_ADAPTER_ADDRESSES)malloc (ulBufferLength);

  if (!pAdapterAddresses) {
    PyErr_SetString (PyExc_MemoryError, "Not enough memory");
    return NULL;
  }
}

} while (dwRet == ERROR_BUFFER_OVERFLOW);
/* If we failed, then fail in Python too */
if (dwRet != ERROR_SUCCESS && dwRet != ERROR_NO_DATA) {
if (pAdapterAddresses)
free (pAdapterAddresses);
PyErr_SetString (PyExc_OSError,
                 "Unable to obtain adapter information.");
return NULL;

}
result = PyList_New(0);
if (dwRet == ERROR_NO_DATA) {
free (pAdapterAddresses);
return result;
}
for (pInfo = pAdapterAddresses; pInfo; pInfo = pInfo->Next) {
PyObject *ifname = (PyObject *)PyString_FromString (pInfo->AdapterName);
PyList_Append (result, ifname);
Py_DECREF (ifname);

}
free (pAdapterAddresses);
#elif HAVE_GETIFADDRS
const char *prev_name = NULL;
struct ifaddrs *addrs = NULL;
struct ifaddrs *addr = NULL;
result = PyList_New (0);
if (getifaddrs (&addrs) < 0) {
Py_DECREF (result);
PyErr_SetFromErrno (PyExc_OSError);
return NULL;
}
for (addr = addrs; addr; addr = addr->ifa_next) {
if (!prev_name || strncmp (addr->ifa_name, prev_name, IFNAMSIZ) != 0) {
PyObject *ifname = PyString_FromString (addr->ifa_name);
  if (!PySequence_Contains (result, ifname))
    PyList_Append (result, ifname);
  Py_DECREF (ifname);
  prev_name = addr->ifa_name;
}

}
freeifaddrs (addrs);
#elif HAVE_SIOCGIFCONF
const char *prev_name = NULL;
int fd = socket (AF_INET, SOCK_DGRAM, 0);
struct CNAME(ifconf) ifc;
int len = -1;
if (fd < 0) {
PyErr_SetFromErrno (PyExc_OSError);
return NULL;
}
// Try to find out how much space we need
#if HAVE_SIOCGSIZIFCONF
if (ioctl (fd, SIOCGSIZIFCONF, &len) < 0)
len = -1;
#elif HAVE_SIOCGLIFNUM
{ struct lifnum lifn;
lifn.lifn_family = AF_UNSPEC;
lifn.lifn_flags = LIFC_NOXMIT | LIFC_TEMPORARY | LIFC_ALLZONES;
ifc.lifc_family = AF_UNSPEC;
ifc.lifc_flags = LIFC_NOXMIT | LIFC_TEMPORARY | LIFC_ALLZONES;
if (ioctl (fd, SIOCGLIFNUM, (char *)&lifn) < 0)
len = -1;
else
len = lifn.lifn_count;
}
#endif
// As a last resort, guess
if (len < 0)
len = 64;
ifc.CNAME(ifc_len) = (int)(len * sizeof (struct CNAME(ifreq)));
ifc.CNAME(ifc_buf) = malloc (ifc.CNAME(ifc_len));
if (!ifc.CNAME(ifc_buf)) {
PyErr_SetString (PyExc_MemoryError, "Not enough memory");
close (fd);
return NULL;
}
#if HAVE_SIOCGLIFNUM
if (ioctl (fd, SIOCGLIFCONF, &ifc) < 0) {
#else
if (ioctl (fd, SIOCGIFCONF, &ifc) < 0) {
#endif
free (ifc.CNAME(ifc_req));
PyErr_SetFromErrno (PyExc_OSError);
close (fd);
return NULL;
}
result = PyList_New (0);
struct CNAME(ifreq) *pfreq = ifc.CNAME(ifc_req);
struct CNAME(ifreq) *pfreqend = (struct CNAME(ifreq) *)((char *)pfreq
+ ifc.CNAME(ifc_len));
while (pfreq < pfreqend) {
if (!prev_name || strncmp (prev_name, pfreq->CNAME(ifr_name), IFNAMSIZ) != 0) {
PyObject *name = PyString_FromString (pfreq->CNAME(ifr_name));
  if (!PySequence_Contains (result, name))
    PyList_Append (result, name);
  Py_XDECREF (name);

  prev_name = pfreq->CNAME(ifr_name);
}

#if !HAVE_SOCKADDR_SA_LEN
++pfreq;
#else
/* On some platforms, the ifreq struct can grow(!) if the socket address
is very long.  Mac OS X is such a platform. */
{
size_t len = sizeof (struct CNAME(ifreq));
if (pfreq->ifr_addr.sa_len > sizeof (struct sockaddr))
len = len - sizeof (struct sockaddr) + pfreq->ifr_addr.sa_len;
pfreq = (struct CNAME(ifreq) *)((char *)pfreq + len);
}
#endif
}
free (ifc.CNAME(ifc_buf));
close (fd);
#endif /* HAVE_SIOCGIFCONF */
return result;
}

Looks like there is already a post in wpdev tracking this. Feel free to add your vote there:
https://wpdev.uservoice.com/forums/266908-command-prompt-console-bash-on-ubuntu-on-windo/suggestions/13383789-enable-network-interface-enumeraration


[UI Issue] Option to collaps left side bar pages by default

We have a table with a lot of pages sorted into categories. When opening the public link all those categories are expanded by default, making it hard to navigate.

Would be nice to have an option for collapsed by default (see screenshot). If there is such an option, sorry I wasn't able to find it.

PS this doc is still under construction, please don't share far and wide yet

I understand the request, and it makes sense. Similar ideas have come up before with variations, e.g. in this request in the Community Forum: https://community.getgrist.com/t/remember-collapsed-navigation-items-and-favorites/1443.
We'd welcome a proposal for how it could work to satisfy these overlapping needs.

I'd +1 this request - adding lots of tables begins creating a lot of visual noise, especially when they're functional tables that aren't really used by users directly but are used by multiwidget pages. I can reduce the noise by hiding various tables inside parent tables, but only if they stay collapsed by default.
For conceptual implementation, one option is to store state for the arrow for returning viewers. But then you have to store state for each parent table, for each user.
A simpler approach that would require only one stored variable per document would be an checkbox option in Document Settings to "Default collapse nested tables for all users". This would work in the opposite way it does now: the state of collapse isn't remembered upon reload, but it defaults to collapsed. Users can expand categories if they wish. That seems like it would cover most users' needs who have lots of tables.
I would agree with the other poster in the community forum that it would be nice to have category headers that are not tables and serve only as section headers to categorize other tables, but that's a separate issue (though it'd work nicely with "Default collapsed").

Agree with @derekmoeller although instead of only having the collapse toggle in the doc settings.
Perhaps there can be a button in the left tables panel that let's you collapse all and expand all.
The button could be on top of the left panel under the 'Add New' button.

Noticed the new feature of having the emoji not appear twice... Nice!


Share and read config via "superconfig"

This PR takes @jodosha's experiments in https://gist.github.com/jodosha/b1c58a32e984e62df90e174b104de787 and https://gist.github.com/jodosha/b8b6409630db43962c79d1da92474caa and implements a working version of these within dry-configurable.
How I implemented these here is to give config instances an optional superconfig (i.e. the config from the parent configurable class). This gives us the same lookup to the "originals" from @jodosha's original gists.
However, there's one major change required for the implementation: we need to dup mutable config values from the superconfig whenever they are read. This is because we cannot differentiate reading from writing for mutable values. This would have been required in the original gists too, if they were expanded to satisfy all of our integration tests.
So this means that—for mutable values at least—we only really end up with one meaningful difference over the current implementation: whether to dup on inherit (per the main branch, with the work happening in Config#dup_for_settings) or dup on read (this PR, with the work happening in Config#[]).
The end result is that we don't actually net any meaningful memory improvements either.
I tested this with the following memory profiles:

TIMES=100 PROFILE=inherit_only bundle exec ruby benchmarks/memory_profile.rb
TIMES=100 PROFILE=inherit_and_configure bundle exec ruby benchmarks/memory_profile.rb

The results:
Inherit only:
main branch:
             Total allocated: 258091 bytes (1820 objects)
             Total retained:  102968 bytes (666 objects)
This branch:
             Total allocated: 260237 bytes (1853 objects)
             Total retained:  103161 bytes (670 objects)

Inherit and configure:
main branch:
             Total allocated: 299011 bytes (2410 objects)
             Total retained:  120288 bytes (766 objects)
This branch:
             Total allocated: 301197 bytes (2443 objects)
             Total retained:  120521 bytes (770 objects)

My take from this is that this approach would only really yield significant memory improvements in more constrained scenarios, and the implementation that achieves this wouldn't cover all the functionality we need for a fully working dry-configurable.

 One last pass at optimising dry-configurable


Document how to derive data for glyphs not in GlyphInfo

In https://github.com/googlei18n/glyphsLib/issues/88#issuecomment-267144319, @schriftgestalt wrote:

There are some rules that try to find glyph info for glyphs not in GlyphData. That is mostly for glyphs with suffixes and ligatures.

Would you mind documenting these rules, perhaps in README.md? It would help me to implement https://github.com/googlei18n/glyphsLib/issues/88 correctly.

The code it a bit of a mess. Writing the docu would help clean this up but I don't have time for it right now. I’ll see what I can do.

@schriftgestalt Can I help to reengineer a specification? I am interested to have clear specs, which I can implement in Perl, and write extensive test cases. This can also be helpful cleaning up your code and have spec-tests for it.

Sounds good.
Can we talk about that over the phone?

@schriftgestalt Obviously this needs to know the phone number, which I couldn't find.
You can find mine here: http://nomen.at/about/imprint.html


ISPN-5716 Update last-minute changes in Functional docs

To avoid confusion, replace lambda word mentions with functions.
SerializeLambdaWith and MarshallableLambdas were renamed just before
final into SerializeFunctionWith and MarshallableFunctions, so update
documentation.
Finally, added apidocs links for MarshallableFunctions.

Integrated, thanks Galder!


[CONTRACTS] add tests for the registration component

(Will prolly be assigned to @chachaleo)

@0xChqrles please can I work on this


Remove the "UNLICENSED" wording from the UI

Using "UNLICENSED" in the UI is rather confusing as the "UNLICENSE" is a public-domain-like license. I reckon NPM does that, but that's a poor choice of words as an npm license value of UNLICENSED and UNLICENSE would both be valid and mean completely different thing..
I suggest using "not licensed" or "no license stated" or anything else.
FWIW, "Unattributed" also sounds a tad weird: "no copyright statement" ... or something might be better

This has been addressed in #536 and could be closed

I have verified this is fixed in the UI. @pombredanne please reopen if you find that's not the case.


Sample code has a wrap which cause example to fail as presented

There should be 10 lines of code, the last line is wrapped from line 10.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: df8fdc8c-e174-0a4c-44f7-0de94bc31ed4
Version Independent ID: e1bd9924-b106-950b-4408-c62cfe4fd784
Content: Manage Office 365 services using Azure Automation
Content Source: articles/automation/manage-office-365.md
Service: automation
GitHub Login: @MGoedtel
Microsoft Alias: magoedte

@D-Jeffrey Thanks for your comment! We will review and provide an update as appropriate.

@D-Jeffery - I'll bug this and get it fixed today to remove the carriage return and merge the remaining arguments with the command-line.  Thanks for bringing this to my attention.  #please-close


[WIP] [2.4] Support AKS loadBalancerSku

Proposed changes

Support AKS LB Sku
Types of changes

New feature (non-breaking change which adds functionality)

Linked Issues

https://github.com/rancher/rancher/issues/23715
Further comments

Depends on:
https://github.com/rancher/rancher/pull/24308
https://github.com/rancher/kontainer-engine/pull/202

rebased


about page layout

[ ] get about page content from C & K (waiting)
[x] design
[x] implement

Let's keep it very simple and build on existing styles.

design and implementation done in #95


Add variables for carbon-utilization to produce synfuels

Based on an email with suggested variables by @strefler.

Tests currently failing because of https://github.com/iiasa/pysquirrel/issues/38. FYI @dc-almeida