[speech recognition] [bug] Dockerfile.gpu fails to build

The reference/speech_recognition/pytorch/docker/Dockerfile.gpu fails to build with Docker.
How to reproduce:
$ mv Dockerfile.gpu Dockerfile
$ sudo docker build -t test .

Expected behavior:
The image builds successfully.
Actual behavior:
The warp-ctc portion of the build fails when generating build/warpctc_pytorch/_warp_ctc/__warp_ctc.c.
generating build/warpctc_pytorch/_warp_ctc/__warp_ctc.c
running install
running bdist_egg
running egg_info
creating warpctc_pytorch.egg-info
writing warpctc_pytorch.egg-info/PKG-INFO
writing top-level names to warpctc_pytorch.egg-info/top_level.txt
writing dependency_links to warpctc_pytorch.egg-info/dependency_links.txt
writing manifest file 'warpctc_pytorch.egg-info/SOURCES.txt'
reading manifest file 'warpctc_pytorch.egg-info/SOURCES.txt'
writing manifest file 'warpctc_pytorch.egg-info/SOURCES.txt'
installing library code to build/bdist.linux-x86_64/egg
running install_lib
running build_py
creating build/lib.linux-x86_64-2.7
creating build/lib.linux-x86_64-2.7/warpctc_pytorch
copying warpctc_pytorch/__init__.py -> build/lib.linux-x86_64-2.7/warpctc_pytorch
creating build/lib.linux-x86_64-2.7/warpctc_pytorch/_warp_ctc
copying warpctc_pytorch/_warp_ctc/__init__.py -> build/lib.linux-x86_64-2.7/warpctc_pytorch/_warp_ctc
running build_ext
building 'warpctc_pytorch._warp_ctc.__warp_ctc' extension
creating build/temp.linux-x86_64-2.7
creating build/temp.linux-x86_64-2.7/build
creating build/temp.linux-x86_64-2.7/build/warpctc_pytorch
creating build/temp.linux-x86_64-2.7/build/warpctc_pytorch/_warp_ctc
creating build/temp.linux-x86_64-2.7/tmp
creating build/temp.linux-x86_64-2.7/tmp/warp-ctc
creating build/temp.linux-x86_64-2.7/tmp/warp-ctc/pytorch_binding
creating build/temp.linux-x86_64-2.7/tmp/warp-ctc/pytorch_binding/src
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/tmp/warp-ctc/include -I/usr/include/python2.7 -c build/warpctc_pytorch/_warp_ctc/__warp_ctc.c -o build/temp.linux-x86_64-2.7/build/warpctc_pytorch/_warp_ctc/__warp_ctc.o -std=c++11 -fPIC -std=c99 -DWARPCTC_ENABLE_GPU
cc1: warning: command line option '-std=c++11' is valid for C++/ObjC++ but not for C
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/tmp/warp-ctc/include -I/usr/include/python2.7 -c /tmp/warp-ctc/pytorch_binding/src/binding.cpp -o build/temp.linux-x86_64-2.7/tmp/warp-ctc/pytorch_binding/src/binding.o -std=c++11 -fPIC -std=c99 -DWARPCTC_ENABLE_GPU
cc1plus: warning: command line option '-Wstrict-prototypes' is valid for C/ObjC but not for C++
cc1plus: warning: command line option '-std=c99' is valid for C/ObjC but not for C++
/tmp/warp-ctc/pytorch_binding/src/binding.cpp: In function 'int gpu_ctc(THCudaTensor*, THCudaTensor*, THIntTensor*, THIntTensor*, THIntTensor*, int, THFloatTensor*, int)':
/tmp/warp-ctc/pytorch_binding/src/binding.cpp:92:49: error: cannot convert 'THCudaTensor*' to 'const THFloatTensor*' for argument '1' to 'long int THFloatTensor_size(const THFloatTensor*, int)'
     int probs_size = THFloatTensor_size(probs, 2);
                                                 ^
/tmp/warp-ctc/pytorch_binding/src/binding.cpp:105:61: error: invalid conversion from 'size_t {aka long unsigned int}' to 'void**' [-fpermissive]
     void* gpu_workspace = THCudaMalloc(state, gpu_size_bytes);
                                                             ^
/tmp/warp-ctc/pytorch_binding/src/binding.cpp:105:61: error: too few arguments to function 'cudaError_t THCudaMalloc(THCState*, void**, size_t)'
In file included from /usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC/THC.h:4:0,
                 from /tmp/warp-ctc/pytorch_binding/src/binding.cpp:9:
/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC/THCGeneral.h:205:21: note: declared here
 THC_API cudaError_t THCudaMalloc(THCState *state, void **ptr, size_t size);
                     ^
error: command 'x86_64-linux-gnu-gcc' failed with exit status 1
The command '/bin/sh -c git clone https://github.com/SeanNaren/warp-ctc.git &&     cd warp-ctc &&     mkdir -p build && cd build && cmake .. && make &&     cd ../pytorch_binding && python setup.py install' returned a non-zero code: 1

 Full output

Sending build context to Docker daemon  3.584kB
Step 1/14 : FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04
 ---> fde2f471fd51
Step 2/14 : WORKDIR /tmp
 ---> Using cache
 ---> 47a70b55047b
Step 3/14 : RUN apt-get update && apt-get install -y   python   python-pip   sox   libsox-dev   libsox-fmt-all   git   cmake   tree   htop   bmon   iotop   tmux   vim   apt-utils
 ---> Using cache
 ---> 4314697c214a
Step 4/14 : RUN pip install --upgrade pip
 ---> Using cache
 ---> 66f4b32b54c7
Step 5/14 : RUN pip install h5py                 hickle                 matplotlib                 tqdm                 http://download.pytorch.org/whl/cu80/torch-0.2.0.post3-cp27-cp27mu-manylinux1_x86_64.whl                 torchvision                 cffi                 python-Levenshtein                 librosa                 wget                 tensorboardX
 ---> Using cache
 ---> 9fda8ded8156
Step 6/14 : RUN apt-get update && apt-get install --yes --no-install-recommends cmake                                                                     sudo
 ---> Using cache
 ---> 0687cf159462
Step 7/14 : ENV CUDA_HOME "/usr/local/cuda"
 ---> Using cache
 ---><PHONE_NUMBER>2b
Step 8/14 : RUN git clone https://github.com/SeanNaren/warp-ctc.git &&     cd warp-ctc &&     mkdir -p build && cd build && cmake .. && make &&     cd ../pytorch_binding && python setup.py install
 ---> Running in e0e66d4c03ed
Cloning into 'warp-ctc'...
-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - not found
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE
-- Found CUDA: /usr/local/cuda (found suitable version "9.0", minimum required is "6.5")
-- cuda found TRUE
-- Building shared library with GPU support
-- Configuring done
-- Generating done
-- Build files have been written to: /tmp/warp-ctc/build
[ 11%] Building NVCC (Device) object CMakeFiles/warpctc.dir/src/warpctc_generated_reduce.cu.o
/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is not valid on compute_70 and above, and should be replaced with __shfl_down_sync().To continue using __shfl_down(), specify virtual architecture compute_60 when targeting sm_70 and above, for example, using the pair of compiler options: -arch=compute_60 -code=sm_70.")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(149): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is not valid on compute_70 and above, and should be replaced with __shfl_down_sync().To continue using __shfl_down(), specify virtual architecture compute_60 when targeting sm_70 and above, for example, using the pair of compiler options: -arch=compute_60 -code=sm_70.")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(157): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(149): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(157): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(149): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(157): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(149): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(157): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(149): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(157): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(149): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(157): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(149): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(157): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(149): here

/tmp/warp-ctc/src/reduce.cu(44): warning: function "__shfl_down(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(278): here was declared deprecated ("__shfl_down() is deprecated in favor of __shfl_down_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")
          detected during:
            instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]"
(76): here
            instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]"
(124): here
            instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(139): here
            instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(157): here

[ 22%] Building NVCC (Device) object CMakeFiles/warpctc.dir/src/warpctc_generated_ctc_entrypoint.cu.o
/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(115): warning: function "__shfl_up(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(261): here was declared deprecated ("__shfl_up() is not valid on compute_70 and above, and should be replaced with __shfl_up_sync().To continue using __shfl_up(), specify virtual architecture compute_60 when targeting sm_70 and above, for example, using the pair of compiler options: -arch=compute_60 -code=sm_70.")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(125): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is not valid on compute_70 and above, and should be replaced with __shfl_up_sync().To continue using __shfl_up(), specify virtual architecture compute_60 when targeting sm_70 and above, for example, using the pair of compiler options: -arch=compute_60 -code=sm_70.")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(126): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is not valid on compute_70 and above, and should be replaced with __shfl_up_sync().To continue using __shfl_up(), specify virtual architecture compute_60 when targeting sm_70 and above, for example, using the pair of compiler options: -arch=compute_60 -code=sm_70.")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(115): warning: function "__shfl_up(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(261): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(125): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(126): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(115): warning: function "__shfl_up(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(261): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(125): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(126): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(115): warning: function "__shfl_up(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(261): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(125): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(126): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(115): warning: function "__shfl_up(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(261): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(125): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(126): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(115): warning: function "__shfl_up(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(261): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(125): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(126): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(115): warning: function "__shfl_up(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(261): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(125): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(126): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(115): warning: function "__shfl_up(float, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(261): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(125): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

/tmp/warp-ctc/include/contrib/moderngpu/include/device/intrinsics.cuh(126): warning: function "__shfl_up(int, unsigned int, int)"
/usr/local/cuda/include/sm_30_intrinsics.hpp(175): here was declared deprecated ("__shfl_up() is deprecated in favor of __shfl_up_sync() and may be removed in a future release (Use -Wno-deprecated-declarations to suppress this warning).")

Scanning dependencies of target warpctc
[ 33%] Linking CXX shared library libwarpctc.so
[ 33%] Built target warpctc
Scanning dependencies of target test_cpu
[ 44%] Building CXX object CMakeFiles/test_cpu.dir/tests/test_cpu.cpp.o
[ 55%] Building CXX object CMakeFiles/test_cpu.dir/tests/random.cpp.o
[ 66%] Linking CXX executable test_cpu
[ 66%] Built target test_cpu
[ 77%] Building NVCC (Device) object CMakeFiles/test_gpu.dir/tests/test_gpu_generated_test_gpu.cu.o
Scanning dependencies of target test_gpu
[ 88%] Building CXX object CMakeFiles/test_gpu.dir/tests/random.cpp.o
[100%] Linking CXX executable test_gpu
[100%] Built target test_gpu
regenerated: 'build/warpctc_pytorch/_warp_ctc/__warp_ctc.c'
generating build/warpctc_pytorch/_warp_ctc/__warp_ctc.c
running install
running bdist_egg
running egg_info
creating warpctc_pytorch.egg-info
writing warpctc_pytorch.egg-info/PKG-INFO
writing top-level names to warpctc_pytorch.egg-info/top_level.txt
writing dependency_links to warpctc_pytorch.egg-info/dependency_links.txt
writing manifest file 'warpctc_pytorch.egg-info/SOURCES.txt'
reading manifest file 'warpctc_pytorch.egg-info/SOURCES.txt'
writing manifest file 'warpctc_pytorch.egg-info/SOURCES.txt'
installing library code to build/bdist.linux-x86_64/egg
running install_lib
running build_py
creating build/lib.linux-x86_64-2.7
creating build/lib.linux-x86_64-2.7/warpctc_pytorch
copying warpctc_pytorch/__init__.py -> build/lib.linux-x86_64-2.7/warpctc_pytorch
creating build/lib.linux-x86_64-2.7/warpctc_pytorch/_warp_ctc
copying warpctc_pytorch/_warp_ctc/__init__.py -> build/lib.linux-x86_64-2.7/warpctc_pytorch/_warp_ctc
running build_ext
building 'warpctc_pytorch._warp_ctc.__warp_ctc' extension
creating build/temp.linux-x86_64-2.7
creating build/temp.linux-x86_64-2.7/build
creating build/temp.linux-x86_64-2.7/build/warpctc_pytorch
creating build/temp.linux-x86_64-2.7/build/warpctc_pytorch/_warp_ctc
creating build/temp.linux-x86_64-2.7/tmp
creating build/temp.linux-x86_64-2.7/tmp/warp-ctc
creating build/temp.linux-x86_64-2.7/tmp/warp-ctc/pytorch_binding
creating build/temp.linux-x86_64-2.7/tmp/warp-ctc/pytorch_binding/src
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/tmp/warp-ctc/include -I/usr/include/python2.7 -c build/warpctc_pytorch/_warp_ctc/__warp_ctc.c -o build/temp.linux-x86_64-2.7/build/warpctc_pytorch/_warp_ctc/__warp_ctc.o -std=c++11 -fPIC -std=c99 -DWARPCTC_ENABLE_GPU
cc1: warning: command line option '-std=c++11' is valid for C++/ObjC++ but not for C
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/TH -I/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC -I/usr/local/cuda/include -I/tmp/warp-ctc/include -I/usr/include/python2.7 -c /tmp/warp-ctc/pytorch_binding/src/binding.cpp -o build/temp.linux-x86_64-2.7/tmp/warp-ctc/pytorch_binding/src/binding.o -std=c++11 -fPIC -std=c99 -DWARPCTC_ENABLE_GPU
cc1plus: warning: command line option '-Wstrict-prototypes' is valid for C/ObjC but not for C++
cc1plus: warning: command line option '-std=c99' is valid for C/ObjC but not for C++
/tmp/warp-ctc/pytorch_binding/src/binding.cpp: In function 'int gpu_ctc(THCudaTensor*, THCudaTensor*, THIntTensor*, THIntTensor*, THIntTensor*, int, THFloatTensor*, int)':
/tmp/warp-ctc/pytorch_binding/src/binding.cpp:92:49: error: cannot convert 'THCudaTensor*' to 'const THFloatTensor*' for argument '1' to 'long int THFloatTensor_size(const THFloatTensor*, int)'
     int probs_size = THFloatTensor_size(probs, 2);
                                                 ^
/tmp/warp-ctc/pytorch_binding/src/binding.cpp:105:61: error: invalid conversion from 'size_t {aka long unsigned int}' to 'void**' [-fpermissive]
     void* gpu_workspace = THCudaMalloc(state, gpu_size_bytes);
                                                             ^
/tmp/warp-ctc/pytorch_binding/src/binding.cpp:105:61: error: too few arguments to function 'cudaError_t THCudaMalloc(THCState*, void**, size_t)'
In file included from /usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC/THC.h:4:0,
                 from /tmp/warp-ctc/pytorch_binding/src/binding.cpp:9:
/usr/local/lib/python2.7/dist-packages/torch/utils/ffi/../../lib/include/THC/THCGeneral.h:205:21: note: declared here
 THC_API cudaError_t THCudaMalloc(THCState *state, void **ptr, size_t size);
                     ^
error: command 'x86_64-linux-gnu-gcc' failed with exit status 1
The command '/bin/sh -c git clone https://github.com/SeanNaren/warp-ctc.git &&     cd warp-ctc &&     mkdir -p build && cd build && cmake .. && make &&     cd ../pytorch_binding && python setup.py install' returned a non-zero code: 1

@j-ogas,  I think this is related to this issue https://github.com/SeanNaren/warp-ctc/issues/76#issue-347690774 with PyTorch bindings for Warp-ctc. At least, the source code change suggested by @jielingTang with Pytorch version 0.4 seems that it fixed the problem for me.

I am facing the same issue. Were you able to resolve it?

The docker images build successfully once you make the changes.
https://github.com/mlperf/reference/pull/131/commits/5c8d11fd275d8c219607f436774252bab08a84b7
On Tue, 28 Aug 2018 at 01:09 Vyas Bhagwat<EMAIL_ADDRESS>wrote:

I am facing the same issue. Were you able to resolve it?
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/mlperf/reference/issues/113#issuecomment-416397978,
or mute the thread
https://github.com/notifications/unsubscribe-auth/ANR0FJrCRqptzY-M0d7qg2apHaM9jewCks5uVHxCgaJpZM4VuHNB
.

I had tried the same thing and I was using Anaconda with Python 2.7 as my environment. Making those changes allows warp-ctc to build properly but it gave me an error while running the run_and_time.sh.
I shifted to a new environment with Python 3.6 and not only did warp-ctc build properly even without the modification, it also got past the CUDA error I faced.


Document lint rule set configuration.

From @pq on October 13, 2015 15:33
Lint rules can be enabled via .analysis_options and the syntax needs to be documented.
linter:
  rules:
    - camel_case_types
    - empty_constructor_bodies
    - library_names
    - super_goes_last

Copied from original issue: dart-lang/analyzer_cli#70

From @zoechi on October 13, 2015 19:22
And the list of lint rule names. Looks like #69 is about this, right?


Separate projects by host

Instead of storing projects at ~/Projects/cdr/code-server, we should also separate them by host like ~/Projects/github.com/cdr/code-server so multiple projects don't overlap

@ammario  if you use github.com and internal git hosting, and there may be conflicts with same namespace and repo name.  Another consideration is separation, and I don't want internal kubernetes applications under github.com kubernetes namespace, and it's confused.

@linux-china To be fair, it's currently possible to use multiple hosts since sail run will accept a host
sail run my.private-git.com/user/repo
The only time we will run into issues is if two git hosts share the same user/repo name

We want the Sail project folder to be structured as closely as a dev would normally structure their projects folder. I don't know any devs (except Go ones, by force) which have their Git host in their project path.
A possible solution is changing project_path to be a mapping of regex to project directories. Then, one could easily redirect all projects related to a particular Git host or organization to a folder.

I generally include github.com, gitlab.com in the project's path.


TMDb Importing

Add support for importing from TMDb watched list csv export.
Related #214
Closes #215

Nice one, you found a much cleaner solution than what I could do :) . I do have a couple questions though, when I try to import, it doesn't keep the ratings, is it a bug or intended?

Nice one, you found a much cleaner solution than what I could do :) . I do have a couple questions though, when I try to import, it doesn't keep the ratings, is it a bug or intended?

Oh I didnt implement saving ratings.
When I was testing creating a list on tmdb, for some reason when I gave something a rating it would be removed from my list.
I see now that your example data (https://github.com/sbondCo/Watcharr/issues/130#issuecomment-1795856431) has a YourRating.
I think I saw you could add notes to movies too, but that seems to be on custom lists you cant export on tmdb. So I guess we cant do that to save thoughts too.
I'll have a look at adding the ratings, should be an ezpz fix (hopefully).

Also, the data includes the date of the rating, I think it would be cool not to lose that as well.

Also, the data includes the date of the rating, I think it would be cool not to lose that as well.

Hey, just released v1.25.0 with this functionality.
Changing the date of an activity is a planned feature so I was able to get some of that work done in the backend for saving the original rating date.
It'll look something like this after importing (bottom activity says "Original Rating on TMDb" - my screenshot tool buggy :disappointed:):


add threads-extras, clock-extras, and next-ref to stackage

add threads-extras, clock-extras and next-ref to build-constraints.yaml.

Thanks!


I am a teacher, now i know why my students get his assignments down so fast.

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
Describe the solution you'd like
A clear and concise description of what you want to happen.
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Add any other context or screenshots about the feature request here.

Oh nooo D:
You can use this to complete your assignments too :3

Lol 😂😂

LMAO :rofl: :rofl: :rofl:

We always find hacks to skip school...

This is when we say "Lazy people do their tasks in an easier and more creative way!"😄.
To all the teachers seeing this: Take it easy on your students, they should use their brain, no matter what tool they use.


Upgrade for 1.6 release

This PR is still WIP - the container is running and charm gets active, but the dashboard can't be accessed.
TODO: Review upstream changes from 4 Jun 2020 (release date of the previous image) to 5 Oct 2021.

Thanks @natalian98! I believe this changes do not apply anymore. I am closing this issue as we are upgrading soon. Please re-open if needed.


logic login app information page

Description
After the  user is navigated to the Login app information screen. het gets the app information displayed and he is able to logout from tonomy SSO website
DOD:

[ ] the app information gets fetched from the blockchain and displayed
[ ] app information page listens for messages from mobile and if it recieves a message that user has finished login consent then they are sent back to the external website callback page
[ ] if the user clicks on logout button they user gets logged out from the app

https://www.figma.com/file/cvV48t0f7O2znT6QBxK0Zj/Tonomy-ID?node-id=2445%3A13059&t=mUw0jMkjRvkyvnvO-4


disconnectRequest never called

VSCode Version: 1.2.0
OS Version: Mac OS X 10.11.5

Steps to Reproduce:

Generated project based on mock debug adapter
Added disconnectRequest implementation to class derived from DebugSession
Start the debugger (in server or local mode) then stop with the stop button.
Result: disconnectRequest is not called
Expected: disconnectRequest called

I was mistaken. disconnectRequest is being called in server mode (probably in local mode, too, but I can't tell.) Closing this.


shortDescription causing bug on prototype list

Ran into this running the tutorial. It's likely related to 4233bcc5ad8470165edcaf0f08f99835ae702502
cc @abiogenesis-now
➜  guestbook git:(k8s-version) ✗ ../ks pkg install incubator/redis@master
INFO  Retrieved 8 files
➜  guestbook git:(k8s-version) ✗ ../ks pkg list
NAME      REGISTRY  INSTALLED
====      ========  =========
postgres  incubator
tomcat    incubator
apache    incubator
efk       incubator
mariadb   incubator
memcached incubator
nginx     incubator
node      incubator
mongodb   incubator
mysql     incubator
redis     incubator *
➜  guestbook git:(k8s-version) ✗ ../ks prototype list
ERROR Line in prototype heading comment is formatted incorrectly; '@shortDescription' is not
recognized as a tag. Only tags can begin lines, and text that is wrapped must
be indented. For example:
  // @description This is a long description
  //   that we are wrapping on two lines

False alarm... Didn't pull master


WS-Federation OnRemoteFailure - is this the best way to challenge for authentication again

ASP.NET Core 2.1
My app has remote authentication configured with WS-Fed. I don't want any part of the app to be accessible to an unauthenticated user.
services
    .AddAuthentication(o =>
    {
        o.DefaultScheme = CookieAuthenticationDefaults.AuthenticationScheme;
        o.DefaultSignInScheme = CookieAuthenticationDefaults.AuthenticationScheme;
        o.DefaultChallengeScheme = WsFederationDefaults.AuthenticationScheme;
    })
    .AddWsFederation(o =>
    {
        o.Wtrealm = "urn:sp.ProspectPortal";
        o.MetadataAddress = "https://localhost:44311/metadata.xml";
        o.Events.OnRedirectToIdentityProvider = ctx =>
        {
            ctx.ProtocolMessage.Wct = DateTimeOffset.UtcNow.ToString();
            return Task.CompletedTask;
        };
    })
    .AddCookie();

If the user cancels the authentication, then the remote authenticator redirects to the default WsFederationOptions.CallbackPath, which is /signin-wsfed. It displays the following exception
System.Exception: An error was encountered while handling the remote login. ---> System.Exception: No message.
   --- End of inner exception stack trace ---
   at Microsoft.AspNetCore.Authentication.RemoteAuthenticationHandler`1.HandleRequestAsync()
   at Microsoft.AspNetCore.Authentication.AuthenticationMiddleware.Invoke(HttpContext context)
   at Microsoft.AspNetCore.StaticFiles.StaticFileMiddleware.Invoke(HttpContext context)
   at Microsoft.AspNetCore.Diagnostics.DeveloperExceptionPageMiddleware.Invoke(HttpContext context)

I know an issue with my IdP is causing this exception.
For now, in order to automatically challenge the user for authentication again and to not show the exception, I added this to the ws-fed configuration.
o.Events.OnRemoteFailure = ctx =>
{
    ctx.Response.Redirect("/Index");  //requires authentication
    ctx.HandleResponse();
    return Task.CompletedTask;
};

Is this the best way to redirect on failure? Is this the best way to challenge authentication again? See any issues with this?

That works but is likely to cause an infinite loop. We have a similar discussion going on at https://github.com/aspnet/Security/pull/1887 where the recommendation is to redirect the user to an Access Denied page and give them the option to retry from there.


Does not work on Mac OS (SocketException)

Hello, I just tried your library on a simple test program, but it does not seem to work on Mac OS.
TcpConnection seems to set SendBufferSize to 0, which throws a SocketException on Mac OS.
Here is the stacktrace :
System.Net.Sockets.SocketException (22): Invalid argument
   at System.Net.Sockets.Socket.UpdateStatusAfterSocketErrorAndThrowException(SocketError error, String callerName)
   at System.Net.Sockets.Socket.SetSocketOption(SocketOptionLevel optionLevel, SocketOptionName optionName, Int32 optionValue, Boolean silent)
   at System.Net.Sockets.Socket.SetSocketOption(SocketOptionLevel optionLevel, SocketOptionName optionName, Int32 optionValue)
   at System.Net.Sockets.Socket.set_SendBufferSize(Int32 value)
   at AlterNats.Internal.TcpConnection..ctor()
   at AlterNats.NatsConnection.InitialConnectAsync()

thanks for reporting, I'll check soon.

https://github.com/dotnet/corefx/pull/17853#issuecomment-291371266

OSX doesn't support setting the buffer size to 0. Windows and Linux do. So the OSX behavior is going to be different if you try to set the buffer size to 0 -- either it's an error, or it gets mapped to something else (like a very small buffer size) or ... something else, maybe? Making this an error seems like the best option to me.

I'll add platform check like  if (!RuntimeInformation.IsOSPlatform(OSPlatform.OSX))

Ok thank you.
Is there any useful reason to set the buffer sizes to 0?
From what i seen, even if on linux it doesn't throw an error, linux ignores the setting to 0 (they made a max of the value to the SOCK_MIN_SNDBUF value).
I put the link where i saw that : https://stackoverflow.com/questions/67113706/why-does-setting-so-sndbuf-and-so-rcvbuf-destroy-performance


Design web presence for RMS Annex

The RMS Annex currently has one data set.  It would be good for this data set to lead to the rest of our website, and it would be good for the rest of our website to lead to this data set.
This action item is to have a conversation about how to design this web content.  Once we have agreed upon a design, a smaller group (probably @dstopp) will implement.

Did you mean to assign this to Debbie?

From: Matthew Tiscareno @.>
Sent: Wednesday, September 18, 2024 12:38 PM
To: SETI/rms-website @.>
Cc: Joe Spitale @.>; Assign @.>
Subject: Re: [SETI/rms-website] Design web presence for RMS Annex (Issue #214)
Assigned #214https://github.com/SETI/rms-website/issues/214 to @jnspitalehttps://github.com/jnspitale.
—
Reply to this email directly, view it on GitHubhttps://github.com/SETI/rms-website/issues/214#event-14312772765, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AB6OEVBPV3FZDF2MVZVSFV3ZXHJEJAVCNFSM6AAAAABOOMVVHGVHI2DSMVQWIX3LMV45UABCJFZXG5LFIV3GK3TUJZXXI2LGNFRWC5DJN5XDWMJUGMYTENZXGI3TMNI.
You are receiving this because you were assigned.Message ID: @.***>

Did you mean to assign this to Debbie?

@dstopp is included because she might want to give input in the design stage.

Sounds good.

From: Matthew Tiscareno @.>
Sent: Wednesday, September 18, 2024 1:20 PM
To: SETI/rms-website @.>
Cc: Joe Spitale @.>; Mention @.>
Subject: Re: [SETI/rms-website] Design web presence for RMS Annex (Issue #214)
Did you mean to assign this to Debbie?
@dstopphttps://github.com/dstopp is included because she might want to give input in the design stage.
—
Reply to this email directly, view it on GitHubhttps://github.com/SETI/rms-website/issues/214#issuecomment-2359332792, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AB6OEVDIAHQEOPYKI6IUSJ3ZXHOANAVCNFSM6AAAAABOOMVVHGVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGNJZGMZTENZZGI.
You are receiving this because you were mentioned.Message ID: @.***>

I have no idea what this is. Why is it assigned to every member of the team?

I have no idea what this is. Why is it assigned to every member of the team?

I wanted to give everyone a chance to participate in the design discussion.  It's about web design for data, so both web people and data people could be interested.

Discussion is currently happening on #rms-website.  Feel free to participate there, and we can also bring it up at our next team meeting on Tuesday 9/24.

After discussion during today's team meeting, @mit3ch will write content specifically for the Dick French data set and @matthewtiscareno will write content for a general RMS Annex entry page.  Then @dstopp will implement.

My bad, forgot to make an entry here. I sent the Dick French 'blurb' to Debby on 9/25.


Typo in Readme

change "List of trasnformers" to "List of transformers"

Ok done but typically you can make a pull request with the suggested fix


Right-clicking moving targets is awful

I think ideally dynamic entities would use a larger bounds like 1x1, or maybe just moving entities, and static entities use a separate smaller bound.

Bonus points for if you right-click examine on a wall but it fails the raycast even for stuff on your edge.

Corrosive acid not showing up may just be an RMC14 issue.

i am purely guessing but it could be related to fixtures, acid is basically fake it just has a sprite and no fixture

I'm also having the same issue with cameras upstream, I think client just needs to do a spritesystem check instead of entitylookup.

Examine uses sprites now to largely fix this problem and if I get moving target issues again I'll just bump lookup size.


Found Pock unloaded each time after return from sleep

Pock 0.8.1-5
System Version:	macOS 10.14.6 (18G4032)
Kernel Version:	Darwin 18.7.0

I am having same issue, attached is my crash log
Pock_2021-02-24-171227_Dales-MacBook-Pro.crash.zip

Same issue

Same issue here!

Same here

Same issue on Big Sur (M1).

Same issue here on MacBook Pro 16"

Same here on MacBook Pro 16" Catalina 10.15.7

Same issue, same setup as idolize.

Same issue on Big Sur (M1).

Same for me.

Same here — not EVERY sleep, but easily more than half of them.

Same here.

same for me

Same here
Version info:
Mac OS: 11.0.1 (20B29)
Pock version: 0.8.1-5
MacBook Pro (13-inch, 2019, Four Thunderbolt 3 ports)

Same here (not all sleeps, but many/most).
MacOS Big Sur (11.2.3)
1.4 GHz Quad-Core Intel Core i5
MacBookPro15,4
Pock version: 0.8.1-5

Same here. It only started doing this after an update a few months ago.
macOS 10.15.7
MacBook Pro (16-inch, 2019)
Pock version: 0.8.1-5

Same issue

Is this caused by this line: https://github.com/pock/pock/blob/054225c1fe381f248c0af6f4cb6ceca5df9addeb/Pock/AppDelegate.swift#L256
?


GitHub Actions: Fix Update Pipfile.lock workflow

Small patch after #1542.
Weekly run ran, but didn't update the Pipfile.lock and therefore didn't open an PR.
Since we don't use a requirements.txt the --requirements can be dropped. It also modifies the workflow to run when changing the Update Pipfile.lock workflow.
The PR from github-actions now merged into this branch will be opened next week against the master branch.

Can you revert the changes to Pipfile.lock?

Done!

Thanks, I'll change it to 8:00 pacific so we can test it out today.

Now an PR is also opened when the update-pipfile.yml is changed, see #1563


Added additional html parsing for the Runner and Unknown runner regex…

… to cope with latest parkrun website changes

I took your change and make it more flexible by also allowing for the old format (without the "groups" field); added another test-data file ("uk-gateshead-566.gz") that uses the new format.

Thanks for your efforts though.


Add Injectable IConfigurationService

Closes #40

IConfigurationService is an injectable class which provides an interface which can be used to read from the loaded configuration
The default implementation provided uses ConfigService from Nest which reads values from configuration.ts

Coverage increased (+0.3%) to 87.601% when pulling 601bb261e9a531b4850174fe5ec93c28f567ef2a on configuration-module-interface into 8ed7293361b4340fec9a1db9450b8d699a3f5705 on main.


Is this better than jacobSingh/tabwrangler? If so, how?

https://github.com/jacobSingh/tabwrangler

I wouldn't necessarily say "better."  They both work, and they both accomplish the same task in very similar manners.  Tab Shepherd has a different tab closing engine which is more reactive, where as Tab Wrangler uses a time-based approach.  The reactive approach tends to have a lot less bugs that appear because of lag in Chrome itself and things feel more responsive, but both work.
Tab Wrangler has also been updated more recently to have some newer features, however I should have an update out to Tab Shepherd soon.  This update will have all of the missing features, along with a few new features that aren't available in Tab Wrangler.
When I was using Tab Wrangler over 2 years ago, there were a number of bugs.  I rewrote a bunch of it to get rid of those bugs, but was not able to get the developer to pull my merge requests, so I created a new version of the app.  Hopefully someday we'll be able to merge the two together so we don't have to keep duplicating the work.

What do you mean by "time-based approach" and "more reactive approach"?
Thanks for detailing the history and your motivations behind tabshepherd! Do you think you could include this or something similar in the readme? I think others might be confused too when they stumble upon these extensions.

Tab Wrangler's approach to closing tabs uses a timer which fires every 5 seconds to check if any tabs need to be closed.  That means even if the user isn't actively using Chrome, it will still use processing resources every 5 seconds to perform it's check.  This is what I mean by a time-based approach.  It is a simpler algorithm to implement, however it uses a lot of unnecessary CPU time, and there are a number of weird synchronization bugs that can occur if it takes longer than 5 seconds to run it's tab closing process (which I observed happen when I was watching movies).  I also find it very difficult to add new features to Tab Wrangler's tab closing process.
Tab Shepherd uses an approach where things can only happen when a user performs an action.  For example, whenever a new tab is opened, a routine is run to see if max tabs is exceeded.  If it is, then it will schedule the oldest tab to be closed in the future. If the user remains idle and that time expires, then an event will fire which will close the tab.  If the user intervenes, for example by closing a tab, then the tab will be unscheduled.  This approach is more reactive because nothing happens until a user performs an action.  This type of approach does not have any synchronization issues, and it has proven to be easy to maintain.
I'll try to add something to the readme later, along with a feature comparison list.

I see what you mean now. Thanks!


update main0.1 branch to have version 0.1.29

Platforms Impacted

[x] iOS
[x] macOS

Description of changes
update main_0.1 to have 0.1.29 version
Verification
Pull request checklist
This PR has considered:

[ ] Light and Dark appearances
[ ] VoiceOver and Keyboard Accessibility
[ ] Internationalization and Right to Left layouts
[ ] Different resolutions (1x, 2x, 3x)
[ ] Size classes and window sizes (iPhone vs iPad, notched devices, multitasking, different window sizes, etc)

Microsoft Reviewers: Open in CodeFlow

What's the difference between the 0.1.x versions and the 0.2.x versions? The latter is both Appkit/UIKit and SwiftUI, or only SwiftUI?

What's the difference between the 0.1.x versions and the 0.2.x versions? The latter is both Appkit/UIKit and SwiftUI, or only SwiftUI?

0.1.XX has the minimum requirement of iOS 11 (deployment target) while 0.2.XX requires iOS 13.
Vnext (which includes the SwiftUI code will likely be 0.3.XX.


Giving clear hint of the renaming

Is your feature request related to a problem? Please describe.
Yes it is a problem. I was installing cormen-lib today and found my code not working at all. The import cormen_lib statement threw an ModuleNotFoundError to me which led me to troubleshoot on my Python installation. After 20 minutes of configuring and reinstalling cormen-lib and Python and even my IDE back and forth, I finally saw your PyPI page and realized that the project was renamed.
Describe the solution you'd like
Giving clear hints of the renaming is much better, instead of removing all the code under the name cormen_lib and throwing ModuleNotFoundError. We could have a print statement in cormen_lib.py: print('cormen_lib is renamed to dalpy. See https://github.com/DALPy-Developers/DALPy for detail'), as well as all the names of the classes in the library. When users try to import something from cormen_lib (e.g. running their previous homework), they would know what to do to solve it.

Thank you for opening the bug report! This issue has been resolved. You should uninstall the cormen-lib version you have just previously installed (1.1.2), and reinstall the current version (1.1.3). You should now be able to still use existing code using the cormen-lib module.

pip uninstall cormen-lib
pip install cormen-lib


improvement: ZENKO-760 prepare setup to work without cluster

Description
improvement: ZENKO-760 prepare setup to work without cluster
Motivation and context
To be inline with Kubernetes pods sentiment of running one process per pod, the cluster
module usage is removed when workers are configured to be 1. Another change is to move
the metadata setup to make sure connection to MongoDB is in place before accepting any
requests

Hello rahulreddy,
My role is to assist you with the merge of this
pull request. Please type @bert-e help to get
information on this process.
Status report is not available.

Integration data created
I have created the integration data for the additional destination branches.

this pull request will merge improvement/ZENKO-760-no-cluster into
development/8.0
w/8.1/improvement/ZENKO-760-no-cluster will be merged into development/8.1 (pull request #1405)

The following branches will NOT be impacted:

development/6.4
development/7.4

Follow integration pull requests if you would like to be notified of
build statuses by email.

Waiting for approval
The following approvals are needed before I can proceed with the merge:

2 peers

Peer approvals must include at least 1 approval from the following list:

@rahulreddy

@RachedBenMustapha

@dora-korpar

History mismatch
Merge commit #ba610c4af8eeac5aa0a4a42fceaaa9fd73d54c4c on the integration branch
w/8.1/improvement/ZENKO-760-no-cluster is merging a branch which is neither the current
branch improvement/ZENKO-760-no-cluster nor the development branch
development/8.1.
It is likely due to a rebase of the branch improvement/ZENKO-760-no-cluster and the
merge is not possible until all related w/* branches are deleted or updated.
Please use the reset command to have me reinitialize these branches.

@bert-e reset

Reset complete
I have successfully deleted this pull request's integration branches.

Integration data created
I have created the integration data for the additional destination branches.

this pull request will merge improvement/ZENKO-760-no-cluster into
development/8.0
w/8.1/improvement/ZENKO-760-no-cluster will be merged into development/8.1 (pull request #1406)

The following branches will NOT be impacted:

development/6.4
development/7.4

Follow integration pull requests if you would like to be notified of
build statuses by email.

Waiting for approval
The following approvals are needed before I can proceed with the merge:

2 peers

Peer approvals must include at least 1 approval from the following list:

@rahulreddy

@RachedBenMustapha

@dora-korpar

Build failed
The build for commit did not succeed in branch improvement/ZENKO-760-no-cluster.

History mismatch
Merge commit #3f75bda11bca4aa4e71028730fe40d62b930c155 on the integration branch
w/8.1/improvement/ZENKO-760-no-cluster is merging a branch which is neither the current
branch improvement/ZENKO-760-no-cluster nor the development branch
development/8.1.
It is likely due to a rebase of the branch improvement/ZENKO-760-no-cluster and the
merge is not possible until all related w/* branches are deleted or updated.
Please use the reset command to have me reinitialize these branches.

@bert-e wait

@bert-e reset

Reset complete
I have successfully deleted this pull request's integration branches.

Integration data created
I have created the integration data for the additional destination branches.

this pull request will merge improvement/ZENKO-760-no-cluster into
development/8.0
w/8.1/improvement/ZENKO-760-no-cluster will be merged into development/8.1 (pull request #1419)

The following branches will NOT be impacted:

development/6.4
development/7.4

Follow integration pull requests if you would like to be notified of
build statuses by email.

Queue out of order
The changeset has received all authorizations to enter the merge queue,
however the merge queue is currently in an incoherent state. In order
to protect this pull-request, I have have not added the changeset to the
queue.
Please contact a member of release engineering.

@bert-e wait

Known issue:
Stats not being pushed

History mismatch
Merge commit #935aae89a702535a21516672ad7c19cfa803d601 on the integration branch
w/8.1/improvement/ZENKO-760-no-cluster is merging a branch which is neither the current
branch improvement/ZENKO-760-no-cluster nor the development branch
development/8.1.
It is likely due to a rebase of the branch improvement/ZENKO-760-no-cluster and the
merge is not possible until all related w/* branches are deleted or updated.
Please use the reset command to have me reinitialize these branches.

@bert-e reset

Reset complete
I have successfully deleted this pull request's integration branches.

Integration data created
I have created the integration data for the additional destination branches.

this pull request will merge improvement/ZENKO-760-no-cluster into
development/8.0
w/8.1/improvement/ZENKO-760-no-cluster will be merged into development/8.1 (pull request #1426)

The following branches will NOT be impacted:

development/6.4
development/7.4

Follow integration pull requests if you would like to be notified of
build statuses by email.

In the queue
The changeset has received all authorizations and has been added to the
relevant queue(s). The queue(s) will be merged in the target development
branch(es) as soon as builds have passed.
The changeset will be merged in:

:heavy_check_mark: development/8.0

:heavy_check_mark: development/8.1

The following branches will NOT be impacted:

development/6.4
development/7.4

There is no action required on your side. You will be notified here once
the changeset has been merged. In the unlikely event that the changeset
fails permanently on the queue, a member of Release Engineering will
contact you to help resolve the matter.
IMPORTANT
Please do not attempt to modify this pull request.

Any commit you add on the source branch will trigger a new cycle after the
current queue is merged.
Any commit you add on one of the integration branches will be lost.

If you need this pull request to be removed from the queue, please contact a
member of Release Engineering now.

I have successfully merged the changeset of this pull request
into targetted development branches:

:heavy_check_mark: development/8.0

:heavy_check_mark: development/8.1

The following branches have NOT changed:

development/6.4
development/7.4

Please check the status of the associated issue ZENKO-760.
Goodbye rahulreddy.


Alignment issue in Carousel View

Have use a stack layout with Labels in Carousel View, but for some labels text starting from start, even if Horizontal Text Alignment is in center
please help

Use HorizontalOptions = CenterAndExpand


Polish enableShellIntegration setting wording

https://github.com/microsoft/vscode/blob/7c7103c130f63dc090b1a5342878d0dc2e3604f2/src/vs/workbench/contrib/terminal/common/terminalConfiguration.ts#L518-L523

First pass is done, we can tweak this as shells are added, the docs page is up, etc.


"Test deployment" failing

What here?

sorry, still busy with other tasks.
maybe will just pass it to Vadim, as he will be doing a lot of work tomorrow

Message ID: <LLazyEmail/awesome-email-marketing/issues/134/1206801064@
github.com>

started to review it

will be fixed today. closing it


[Docs]: Add solution for JS error - Failed to execute postMessage...... could not be cloned

Is there an existing issue for this?

[X] I have searched the existing issues

Documentation Link
https://docs.appsmith.com/help-and-support/troubleshooting-guide/js-errors
Discord/slack/intercom Link
No response
GitBook Insights searchTerms or link
na
Google Analytics - search terms or a link
na
Describe the problem
https://app.intercom.com/a/apps/y10e7138/inbox/inbox/conversation/164629100101847#part_id=comment-164629100101847-15331420809
Describe the improvement
na
Why do you think this change is needed?
na

@satbir121 Would you able to give us more info on this error and if we should document it under Troubleshooting

@satbir121 ICYMI ^
We should also add a linting error to prevent users from running into this state. Slack conversation


Cannot find module 'node:path'

Hi I'm using this plugin in a newly created project wit svelte and typescript however I'm getting this error:
failed to load config from D:\Documentos\GitHub\piare\vite.config.ts
error when starting dev server:
Error: Cannot find module 'node:path'
Require stack:
- D:\Documentos\GitHub\piare\node_modules\vite\dist\node-cjs\publicUtils.cjs
- D:\Documentos\GitHub\piare\node_modules\vite\index.cjs
- D:\Documentos\GitHub\piare\node_modules\vite-plugin-glsl\dist\index.js
    at Function.Module._resolveFilename (internal/modules/cjs/loader.js:889:15)

Checking if the is anybody that can help me? 👀
🔗  Link of my repo with issues in case someone wants to test
The project is basically what you get when running:

npm create vite@latest

and filling for svelte and typescript
Node version v14.17.5  in a Windows 10 machine.
I did see #13 another issue with similar conditions ( svelte and node v14.17)
however the error is different and already try removing the

"type": "module"

from the packaje json. Also Package.json
"devDependencies": {
    "@sveltejs/vite-plugin-svelte": "^1.0.1",
    "@tsconfig/svelte": "^3.0.0",
    "@types/node": "^18.0.4",
    "svelte": "^3.49.0",
    "svelte-check": "^2.8.0",
    "svelte-preprocess": "^4.10.7",
    "tslib": "^2.4.0",
    "typescript": "^4.6.4",
    "vite": "^3.0.0",
    "vite-plugin-glsl": "^0.2.2"
  }

import { defineConfig } from 'vite'
import glsl from 'vite-plugin-glsl';
import { svelte } from '@sveltejs/vite-plugin-svelte'

// https://vitejs.dev/config/
export default defineConfig({
  plugins: [svelte()]
})

event when not adding glsl  to the plugin array still show the same issue.
also try to change the tsconfig.json
from
"module": "ESNext",

to
"module": "CommonJS",

but the same issue appears. Sorry for the long text but I tried to provide as much details as possible 😥

Hi @ShulkMaster and thanks for opening this issue. Unfortunately though, I'm afraid it's not related to this plugin since as you've said:

even when not adding glsl to the plugin array still show the same issue.

I think it's more similar to one of these:

https://github.com/vitejs/vite/issues/9113
https://github.com/gregnb/filemanager-webpack-plugin/issues/101#issuecomment-867859903

Anyway, I've tested your repo and it works for me (also Windows 10, but node v16.15.1).
If you don't want to upgrade node, I think you can firstly try to rename svelte.config.js to svelte.config.mjs, and then add "moduleResolution": "node" to the compilerOptions in your tsconfig.json. I was facing another error (may be related to yours?) when running yarn dev, but these 2 small updates fixed that.
As described in here, you can use "type": "module" in you package.json, but in that case, you'll also need to update vite.config.ts in this way:
import { defineConfig } from 'vite'
import glsl from 'vite-plugin-glsl';
import { svelte } from '@sveltejs/vite-plugin-svelte'

export default defineConfig({
  plugins: [svelte(), glsl.default()]
});

I hope that helps you.
Please let me know if you've had any progress with this and thanks for your ⭐!
Cheers!

Hi. thank you very much for taking the time and help me. 😊 I really appreciate it.
I was triying to keep the same version of node if possible so I try your suggestions about using svelte.config.mjs and "moduleResolution": "node" as well a a few other tricks but as you point out  this it's not related to this plugin. In fact it is an issue whit vite itselft since Vite version 3 uses node: import which is supported in v16.0.0+ and v14.18.0+
I update to node 16+ so now it work fine.
Here is the comment where I found exactly what was happening
liana-p coment
In case somebody else has this issue and needs to keep on node 14.x probably they what to stick with node v14.18.0 instead of 16 as I did.
Now I can continue in my journey with svelte and WebGL thank a lot.

Yeah, exactly. I've also noticed (just a few hours ago) that vite v3.0.0 was release and this is a breaking change. Just wanted to let you know I'm working on a new version to handle this update properly.


Comodo has re-branded as Sectigo

Since Comodo has re-branded as Sectigo (https://sectigo.com/resource-library/comodo-ca-rebrands-as-sectigo), will certificate from Sectigo CA also supported to be used as SBC certificate? If yes, please update the docs to include Sectigo CA on these docs. If not, please also mention that Sectigo CA is not supported.
Thanks & regards.

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

ID: e26faf8c-529e-b317-5934-cd41cfe8fa24
Version Independent ID: 3ddd5d0a-6dbb-4940-1814-8346e293701b
Content: Plan Direct Routing - Microsoft Teams
Content Source: Teams/direct-routing-plan.md
Service: msteams
GitHub Login: @CarolynRowe
Microsoft Alias: crowe

Sectigo is working with Direct Routing, should indeed be good to update if this is also officially supported by Microsoft.

@erwinbierens Thank you for submitting feedback and contributing to the docs. We are currently investigating this.

@imamadi Hi. Thank you for reaching out to improve MS Docs. Please let me know if this helps - https://techcommunity.microsoft.com/t5/microsoft-teams/comodo-sectigo-certificate-for-ms-teams-direct-routing/m-p/1267664 and see related issue - https://github.com/MicrosoftDocs/OfficeDocs-SkypeForBusiness/issues/5148

@erwinbierens Thank you for submitting feedback. We understand that this issue has been resolved.
Please feel free to re-open this issue if there is a specific area of the docs that we can improve or make better. Thank you.


Packaging: Prunes and moves

Move all our /usr/share/misc files into /usr/share/rpi-sb-provisioner, and prune the target support directory that was unreferenced.

systemd file-hierarchy (https://www.freedesktop.org/software/systemd/man/latest/file-hierarchy.html) suggests that /var/lib/ should be used for "Persistent private data of the package".
Their documentation suggests that /usr/share is for resources with shared ownership without any primary owner.
Going forward, we should consider reading a lot of these pre-canned files from /etc with versions in /var/lib/ being the fallback if no override is configured.

@roliver-rpi I think this should be more in line with the file-hierarchy spec, let me know your thoughts.


Saving frames to bag files in python

Required Info

Camera Model
L515

Firmware Version
<IP_ADDRESS>

Operating System & Version
Win 10

Platform
PC

SDK Version
2

Language
python }

Issue Description
As a part of an experiment I want to save different frame of the camera as bag file, in few different bag files in the same pipeline.  witch function can make that happen and how to control the output bag file name and location?

Hi @guyfilo ,
For a general overview you can reference the example here:
https://github.com/IntelRealSense/librealsense/tree/master/examples/record-playback
While there isn't an exactly similar Python example there should be enough corresponding functions in the wrapper to accomplish the same thing. As a starting point there is this example thought:
https://github.com/IntelRealSense/librealsense/blob/master/wrappers/python/examples/read_bag_example.py
Thanks

@guyfilo
Is there anything else needed on this thread?
*If we don’t hear from you in 7 days, this issue will be closed.


[TF 2.0] Cannot load Keras Sequential model witn InputLayer from h5.

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): YES
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Debian Stable
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: N/A
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): CPU, both TF-2.0.0a0 and tf-nightly-2.0-preview-2.0.0.dev20190315
Python version: 3.5.3
Bazel version (if compiling from source): N/A
GCC/Compiler version (if compiling from source): N/A
CUDA/cuDNN version: N/A
GPU model and memory: N/A

Describe the current behavior
When a Sequential Keras model contains InputLayer and it is saved, it cannot be loaded and fails with a message
ValueError: You are trying to load a weight file containing 1 layers into a model with 0 layers.

Describe the expected behavior
The model can be loaded correctly.
Code to reproduce the issue
import numpy as np
import tensorflow as tf

inputs = np.arange(10)
outputs = 2 * inputs

model = tf.keras.Sequential([
    tf.keras.layers.InputLayer(input_shape=[1]),
    tf.keras.layers.Dense(1),
])
model.compile(
    optimizer=tf.keras.optimizers.Adam(),
    loss=tf.keras.losses.MeanSquaredError(),
    metrics=[tf.keras.metrics.MeanSquaredError()]
)
model.fit(inputs, outputs)
model.save("model.h5")

loaded_model = tf.keras.models.load_model("model.h5")

Other info / logs
The problem is in the fact that Sequential.layers does not return the InputLayer. To quote comments from the method:
  def layers(self):
    # Historically, `sequential.layers` only returns layers that were added
    # via `add`, and omits the auto-generated `InputLayer` that comes at the
    # bottom of the stack.
    # `Trackable` manages the `_layers` attributes and does filtering
    # over it.

The problem is that if InputLayer was added manually with a specified input_shape, then it is an error not to serialize it -- because then the following layers do not know what the input shape is.
Workarounds:

if instead of InputLayer you add input_shape to the Dense layer, it works. However, input dtype cannot be specified in this way and when you pass tf.int32 on input, using an InputLayer is required
in Functional API the tf.keras.layers.Input is serialized in the model (and, funnily, as a InputLayer).

Solutions:

when serializing a Sequential model, all layers need to be serialized (and no filtering of InputLayer performed).

This happens also if not using Input and specifying input_shape, but instead combining models.
https://github.com/tensorflow/tensorflow/issues/28668#issuecomment-508593307

I ran into the same issue as well. I don't understand why the InputLayer is being filtered out while serializing the model. A work around which I found online is to add the batch input shape parameter to the first layer in the model file.
import json
import h5py

def fix_layer0(filename, batch_input_shape, dtype):
    with h5py.File(filename, 'r+') as f:
        model_config = json.loads(f.attrs['model_config'].decode('utf-8'))
        layer0 = model_config['config']['layers'][0]['config']
        layer0['batch_input_shape'] = batch_input_shape
        layer0['dtype'] = dtype
        f.attrs['model_config'] = json.dumps(model_config).encode('utf-8')

fix_layer0('test.h5', [None, *input_shape], 'float32')

This is fixed in latest TF 2.0 nightly build '2.0.0-dev20190718'
Thanks!


added bubblesort

Pull Request Type
[X] Bugfix
What is the current behavior?
The current behavior of the script is that it lacks a proper implementation of the bubble sort algorithm, resulting in an indentation error due to the absence of the required code block.
What is the new behavior?
The new behavior is introducing a correct implementation of the bubble sort algorithm. The script can now successfully sort arrays using bubble sort.

Merged

This is an automated message from Fork, Commit, Merge [BOT].

Thank you for your contribution! Your pull request has been merged. The files have been reset for the next contributor.
What's next?
If you're looking for more ways to contribute, I invite you to check out our forkcommitmerge.io website repository. The repository contain real issues that you can help to resolve or create some of your own if you see any bugs or want to add new features to the site, etc. You can also check out the Influences section in the README to find more projects similar to this one.
Also please leave a star to this project if you feel it helped you, i would really appreciate it.
I look forward to seeing your contributions!


chore: Improve 'reinstall_cluster' playbook

The playbook 'reinstall_cluster' will fail when the KVM host ssh-key has changed. Therefore, we exchange now the ssh-keys on each execution.

Hi @smolin-de, I saw for tags e.g. this:
- name: copy SSH key to third KVM host, if cluster is to be highly available.
  tags: ssh_copy_id, ssh
  import_role:
    name: ssh_copy_id
  when: env.z.lpar3.hostname is defined

but you you have already tags defined (tags: ssh, ssh_copy_id, section_1, kvm_host_3). What is the benefit to have another tags defined on tasks level?

Hi @smolin-de, I saw for tags e.g. this:
- name: copy SSH key to third KVM host, if cluster is to be highly available.
  tags: ssh_copy_id, ssh
  import_role:
    name: ssh_copy_id
  when: env.z.lpar3.hostname is defined

but you you have already tags defined (tags: ssh, ssh_copy_id, section_1, kvm_host_3). What is the benefit to have another tags defined on tasks level?

I just 'copy and paste' the code from "3_setup_kvm_host".
We can delete the tags.

Yes ... I would suggest to remove the tags to reduce the lines of code.

Yes ... I would suggest to remove the tags to reduce the lines of code.

Tags are removed.

:tada: This PR is included in version 1.1.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


added windows 11

after reading this article, i confirmed windows 11 is supported

Learn Build status updates of commit f355c14:
:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

windows/security/threat-protection/security-policy-settings/user-account-control-only-elevate-executables-that-are-signed-and-validated.md
:white_check_mark:Succeeded

For more details, please refer to the build report.
Note: Broken links written as relative paths are included in the above build report. For broken links written as absolute paths or external URLs, see the broken link report.
For any questions, please:Try searching the learn.microsoft.com contributor guidesPost your question in the Learn support channel


refactor: update footer

Update footer

Background

The footer has been redesigned as a part of search v2

Description

Build new footer

Acceptance Criteria

Run app.
Navigate to any route.
In src/demo/App.vue, update the values of the :fundraising-data prop to check different UI states.

This looks very nice! How about below the 1024 breakpoint, making it no longer fixed? Sorry, I was not very explicit about this.

No worries, @josh-chamberlain that's updated!


Fix test case for min & max operators

Fix min_test.onnx generation as well as add a proper check to the parse program vs the expect program.
Adding this in to fix test converge for the min case.
Regenerated the min_test.onnx as well and re -ran tests to verify everything should be working as intended.

Found issue with max operator too and added fix to this PR as changes are small/minimal