Can not build lite/delegate/gpu on Raspberry Pi

System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux (Raspbian)
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: -
TensorFlow installed from (source or binary): source
TensorFlow version: 1bf6646b871d0ce601715f8ed2f50430ca504da7
Python version: -
Installed using virtualenv? pip? conda?: -
Bazel version (if compiling from source): -
GCC/Compiler version (if compiling from source):  gcc version 6.3.0 20170516 (Raspbian 6.3.0-18+rpi1+deb9u1)
CUDA/cuDNN version: -
GPU model and memory: -

Describe the problem
Probably, version of gcc is older on Raspbian OS. I attached log on this issue (see bottom line of this description).
Provide the exact sequence of commands / steps that you executed before running into the problem
Sorry, I didn't use bazel since bazel take huge CPU/Memory resources for Raspberry Pi. I tried to build gpu with following Makefile. I put this Makefile on lite/delegate/gpu. However, this is not a matter for this error may be.
https://gist.github.com/mattn/0dfdee17e025066e4a2386ee3a6af3b0
Any other info / logs

g++ -std=c++14 -c -DTF_COMPILE_LIBRARY -DGL_GLEXT_PROTOTYPES -I/mnt/usbdisk2/tensorflow -I/mnt/usbdisk2/tensorflow/tensorflow/lite/tools/make/downloads/flatbuffers/include -I/mnt/usbdisk2/tensorflow/tensorflow/lite/tools/make/downloads/absl -I/mnt/usbdisk2/tensorflow/tensorflow/lite/tools/make/downloads/fp16/include -I. gl/api.cc -o gl/api.o
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/object_manager.h:27:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:29,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h: In constructor ‘tflite::gpu::gl::gl_buffer_internal::BufferId::BufferId()’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:154:10: error: request for member ‘IgnoreError’ in ‘tflite::gpu::gl::gl_call_internal::CallAndCheckError(std::__cxx11::basic_string(((const char*)"glGenBuffers in /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:153"), std::allocator()), glGenBuffers, tflite::gpu::gl::GetOpenGlErrors, 1, (&((tflite::gpu::gl::gl_buffer_internal::BufferId*)this)->tflite::gpu::gl::gl_buffer_internal::BufferId::id_))’, which is of non-class type ‘int’
         .IgnoreError();
          ^~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h: In destructor ‘tflite::gpu::gl::gl_buffer_internal::BufferId::~BufferId()’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:162:52: error: request for member ‘IgnoreError’ in ‘tflite::gpu::gl::gl_call_internal::CallAndCheckError(std::__cxx11::basic_string(((const char*)"glDeleteBuffers in /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:162"), std::allocator()), glDeleteBuffers, tflite::gpu::gl::GetOpenGlErrors, 1, (&((tflite::gpu::gl::gl_buffer_internal::BufferId*)this)->tflite::gpu::gl::gl_buffer_internal::BufferId::id_))’, which is of non-class type ‘int’
       TFLITE_GPU_CALL_GL(glDeleteBuffers, 1, &id_).IgnoreError();
                                                    ^~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h: In constructor ‘tflite::gpu::gl::gl_buffer_internal::BufferBinder::BufferBinder(GLenum, GLuint)’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:182:51: error: request for member ‘IgnoreError’ in ‘tflite::gpu::gl::gl_call_internal::CallAndCheckError(std::__cxx11::basic_string(((const char*)"glBindBuffer in /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:182"), std::allocator()), glBindBuffer, tflite::gpu::gl::GetOpenGlErrors, ((tflite::gpu::gl::gl_buffer_internal::BufferBinder*)this)->tflite::gpu::gl::gl_buffer_internal::BufferBinder::target_, id)’, which is of non-class type ‘int’
     TFLITE_GPU_CALL_GL(glBindBuffer, target_, id).IgnoreError();
                                                   ^~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h: In destructor ‘tflite::gpu::gl::gl_buffer_internal::BufferBinder::~BufferBinder()’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:186:50: error: request for member ‘IgnoreError’ in ‘tflite::gpu::gl::gl_call_internal::CallAndCheckError(std::__cxx11::basic_string(((const char*)"glBindBuffer in /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:186"), std::allocator()), glBindBuffer, tflite::gpu::gl::GetOpenGlErrors, ((tflite::gpu::gl::gl_buffer_internal::BufferBinder*)this)->tflite::gpu::gl::gl_buffer_internal::BufferBinder::target_, 0)’, which is of non-class type ‘int’
     TFLITE_GPU_CALL_GL(glBindBuffer, target_, 0).IgnoreError();
                                                  ^~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h: In destructor ‘tflite::gpu::gl::gl_buffer_internal::BufferMapper::~BufferMapper()’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:200:64: error: request for member ‘IgnoreError’ in ‘tflite::gpu::gl::gl_call_internal::CallAndCheckError(std::__cxx11::basic_string(((const char*)"glUnmapBuffer in /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:200"), std::allocator()), glUnmapBuffer, tflite::gpu::gl::GetOpenGlErrors, ((tflite::gpu::gl::gl_buffer_internal::BufferMapper*)this)->tflite::gpu::gl::gl_buffer_internal::BufferMapper::target_)’, which is of non-class type ‘int’
   ~BufferMapper() { TFLITE_GPU_CALL_GL(glUnmapBuffer, target_).IgnoreError(); }
                                                                ^~~~~~~~~~~
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/model.h:29:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:24,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h: In function ‘int tflite::gpu::gl::CreateReadWriteShaderStorageBuffer(uint32_t, tflite::gpu::gl::GlBuffer*)’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:217:3: note: in expansion of macro ‘RETURN_IF_ERROR’
   RETURN_IF_ERROR(TFLITE_GPU_CALL_GL(glBufferData, GL_SHADER_STORAGE_BUFFER,
   ^~~~~~~~~~~~~~~
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/object_manager.h:28:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:29,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h: In constructor ‘tflite::gpu::gl::gl_texture_internal::TextureId::TextureId()’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h:165:10: error: request for member ‘IgnoreError’ in ‘tflite::gpu::gl::gl_call_internal::CallAndCheckError(std::__cxx11::basic_string(((const char*)"glGenTextures in /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h:164"), std::allocator()), glGenTextures, tflite::gpu::gl::GetOpenGlErrors, 1, (&((tflite::gpu::gl::gl_texture_internal::TextureId*)this)->tflite::gpu::gl::gl_texture_internal::TextureId::id_))’, which is of non-class type ‘int’
         .IgnoreError();
          ^~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h: In destructor ‘tflite::gpu::gl::gl_texture_internal::TextureId::~TextureId()’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h:172:53: error: request for member ‘IgnoreError’ in ‘tflite::gpu::gl::gl_call_internal::CallAndCheckError(std::__cxx11::basic_string(((const char*)"glDeleteTextures in /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h:172"), std::allocator()), glDeleteTextures, tflite::gpu::gl::GetOpenGlErrors, 1, (&((tflite::gpu::gl::gl_texture_internal::TextureId*)this)->tflite::gpu::gl::gl_texture_internal::TextureId::id_))’, which is of non-class type ‘int’
       TFLITE_GPU_CALL_GL(glDeleteTextures, 1, &id_).IgnoreError();
                                                     ^~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h: In constructor ‘tflite::gpu::gl::gl_texture_internal::TextureBinder::TextureBinder(GLenum, GLuint)’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h:192:52: error: request for member ‘IgnoreError’ in ‘tflite::gpu::gl::gl_call_internal::CallAndCheckError(std::__cxx11::basic_string(((const char*)"glBindTexture in /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h:192"), std::allocator()), glBindTexture, tflite::gpu::gl::GetOpenGlErrors, ((tflite::gpu::gl::gl_texture_internal::TextureBinder*)this)->tflite::gpu::gl::gl_texture_internal::TextureBinder::target_, id)’, which is of non-class type ‘int’
     TFLITE_GPU_CALL_GL(glBindTexture, target_, id).IgnoreError();
                                                    ^~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h: In destructor ‘tflite::gpu::gl::gl_texture_internal::TextureBinder::~TextureBinder()’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h:196:51: error: request for member ‘IgnoreError’ in ‘tflite::gpu::gl::gl_call_internal::CallAndCheckError(std::__cxx11::basic_string(((const char*)"glBindTexture in /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_texture.h:196"), std::allocator()), glBindTexture, tflite::gpu::gl::GetOpenGlErrors, ((tflite::gpu::gl::gl_texture_internal::TextureBinder*)this)->tflite::gpu::gl::gl_texture_internal::TextureBinder::target_, 0)’, which is of non-class type ‘int’
     TFLITE_GPU_CALL_GL(glBindTexture, target_, 0).IgnoreError();
                                                   ^~~~~~~~~~~
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/model.h:29:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:24,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/runtime/shared_buffer.h: In member function ‘int tflite::gpu::gl::SharedBufferData::CreateSharedGlBuffer(tflite::gpu::gl::GlBuffer*)’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/runtime/shared_buffer.h:62:5: note: in expansion of macro ‘RETURN_IF_ERROR’
     RETURN_IF_ERROR(TFLITE_GPU_CALL_GL(glBufferData, GL_SHADER_STORAGE_BUFFER,
     ^~~~~~~~~~~~~~~
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/runtime.h:30:0,
                 from gl/api.cc:35:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/runtime/shared_buffer.h:67:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
gl/api.cc: In member function ‘virtual int tflite::gpu::gl::{anonymous}::InferenceContextImpl::Execute()’:
gl/api.cc:61:69: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
       return FailedPreconditionError("InferenceContext is not reset");
                                                                     ^
gl/api.cc: In member function ‘virtual int tflite::gpu::gl::{anonymous}::InferenceContextImpl::Reset()’:
gl/api.cc:71:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
gl/api.cc: In member function ‘virtual int tflite::gpu::gl::{anonymous}::InferenceContextWithBatchImpl::Execute()’:
gl/api.cc:97:69: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
       return FailedPreconditionError("InferenceContext is not reset");
                                                                     ^
gl/api.cc:113:78: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
             "Object ", id, " does not match expected byte size: ", byte_size));
                                                                              ^
gl/api.cc:122:35: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
               " vs ", num_batches));
                                   ^
gl/api.cc:137:67: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
                 absl::StrCat("Reference to ", id, " is not found"));
                                                                   ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/model.h:29:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:24,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:139:11: note: in expansion of macro ‘RETURN_IF_ERROR’
           RETURN_IF_ERROR(buffer->MakeView(b * byte_size, byte_size, ref));
           ^~~~~~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:142:7: note: in expansion of macro ‘RETURN_IF_ERROR’
       RETURN_IF_ERROR(runtime_->Execute());
       ^~~~~~~~~~~~~~~
gl/api.cc:144:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
gl/api.cc: In member function ‘virtual int tflite::gpu::gl::{anonymous}::InferenceContextWithBatchImpl::Reset()’:
gl/api.cc:151:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/model.h:29:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:24,
                 from gl/api.cc:16:
gl/api.cc: In member function ‘int tflite::gpu::gl::{anonymous}::CompiledModelImpl::Add(const tflite::gpu::gl::WorkgroupsCalculator&, tflite::gpu::gl::ShaderCode)’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:212:5: note: in expansion of macro ‘RETURN_IF_ERROR’
     RETURN_IF_ERROR(
     ^~~~~~~~~~~~~~~
gl/api.cc:221:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/model.h:29:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:24,
                 from gl/api.cc:16:
gl/api.cc: In member function ‘int tflite::gpu::gl::{anonymous}::CompiledModelImpl::AddFullShader(const string&, const uint3&, size_t*)’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:232:7: note: in expansion of macro ‘RETURN_IF_ERROR’
       RETURN_IF_ERROR(
       ^~~~~~~~~~~~~~~
gl/api.cc:240:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/model.h:29:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:24,
                 from gl/api.cc:16:
gl/api.cc: In member function ‘virtual int tflite::gpu::gl::{anonymous}::CompiledModelImpl::NewRun(const tflite::gpu::gl::RuntimeOptions&, const tflite::gpu::gl::ObjectManager*, tflite::gpu::gl::CommandQueue*, std::unique_ptr*) const’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:256:9: note: in expansion of macro ‘RETURN_IF_ERROR’
         RETURN_IF_ERROR(buffer->MakeView(0, s.second, &ref));
         ^~~~~~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:257:9: note: in expansion of macro ‘RETURN_IF_ERROR’
         RETURN_IF_ERROR(refs->RegisterBuffer(s.first, std::move(ref)));
         ^~~~~~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:263:7: note: in expansion of macro ‘RETURN_IF_ERROR’
       RETURN_IF_ERROR(runtime->AddProgram(shaders_[c.shader_idx], c.parameters,
       ^~~~~~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:266:5: note: in expansion of macro ‘RETURN_IF_ERROR’
     RETURN_IF_ERROR(runtime->PrepareForExecution());
     ^~~~~~~~~~~~~~~
gl/api.cc:274:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/model.h:29:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:24,
                 from gl/api.cc:16:
gl/api.cc: In member function ‘virtual int tflite::gpu::gl::{anonymous}::CompiledModelImpl::OnProgram(const std::vector&, const std::vector&, const uint3&, const uint3&, size_t)’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:290:5: note: in expansion of macro ‘RETURN_IF_ERROR’
     RETURN_IF_ERROR(AddFullShader(partial_shaders_[partial_shader_index],
     ^~~~~~~~~~~~~~~
gl/api.cc:299:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
gl/api.cc: In member function ‘virtual int tflite::gpu::gl::{anonymous}::CompiledModelImpl::Serialize(std::vector*) const’:
gl/api.cc:339:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
gl/api.cc: In member function ‘virtual int tflite::gpu::gl::{anonymous}::CompiledModelImpl::OnShader(absl::Span)’:
gl/api.cc:345:21: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return OkStatus();
                     ^
gl/api.cc: In function ‘int tflite::gpu::gl::Compile(const tflite::gpu::gl::CompilationOptions&, const GraphFloat32&, const tflite::gpu::gl::NodeShader&, const tflite::gpu::gl::WorkgroupsCalculator&, std::unique_ptr*)’:
gl/api.cc:389:78: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     return InvalidArgumentError("Only identical batch dimension is supported");
                                                                              ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/model.h:29:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:24,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:392:3: note: in expansion of macro ‘RETURN_IF_ERROR’
   RETURN_IF_ERROR(RequestGpuInfo(&gpu_info));
   ^~~~~~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:396:3: note: in expansion of macro ‘RETURN_IF_ERROR’
   RETURN_IF_ERROR(compiler->Compile(model, [&](ShaderCode code) -> Status {
   ^~~~~~~~~~~~~~~
gl/api.cc:400:19: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
   return OkStatus();
                   ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/model.h:29:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:24,
                 from gl/api.cc:16:
gl/api.cc: In function ‘int tflite::gpu::gl::ReadSerializedModel(const std::vector&, std::unique_ptr*)’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:407:3: note: in expansion of macro ‘RETURN_IF_ERROR’
   RETURN_IF_ERROR(RequestGpuInfo(&gpu_info));
   ^~~~~~~~~~~~~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/common/status.h:68:18: error: request for member ‘ok’ in ‘status2’, which is of non-class type ‘const int’
     if (!status2.ok()) return status2; \
                  ^
gl/api.cc:409:3: note: in expansion of macro ‘RETURN_IF_ERROR’
   RETURN_IF_ERROR(DeserializeCompiledModel(
   ^~~~~~~~~~~~~~~
gl/api.cc:412:19: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
   return OkStatus();
                   ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:25:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/object_manager.h:27,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:29,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h: In instantiation of ‘int tflite::gpu::gl::gl_call_internal::Caller::operator()(const string&, F, ErrorF, Params&& ...) [with F = void (*)(int, unsigned int*); ErrorF = int (*)(); Params = {int, unsigned int*}; std::__cxx11::string = std::__cxx11::basic_string]’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:88:24:   required from ‘int tflite::gpu::gl::gl_call_internal::CallAndCheckError(const string&, F, ErrorF, Params&& ...) [with F = void (*)(int, unsigned int*); ErrorF = int (*)(); Params = {int, unsigned int*}; std::__cxx11::string = std::__cxx11::basic_string]’
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:153:5:   required from here
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:16: error: request for member ‘ok’ in ‘status’, which is of non-class type ‘const int’
     if (status.ok()) return OkStatus();
         ~~~~~~~^~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:38: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     if (status.ok()) return OkStatus();
                                      ^
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:26: error: request for member ‘code’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                   ~~~~~~~^~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:41: error: request for member ‘error_message’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                                  ~~~~~~~^~~~~~~~~~~~~
In file included from /usr/include/EGL/eglplatform.h:119:0,
                 from /usr/include/EGL/egl.h:39,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/portable_gl31.h:21,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_shader.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_program.h:24,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/command_queue.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:26,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:12: error: expression list treated as compound expression in functional cast [-fpermissive]
     return Status(status.code(), status.error_message() + ": " + context);
            ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:25:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/object_manager.h:27,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:29,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h: In instantiation of ‘int tflite::gpu::gl::gl_call_internal::Caller::operator()(const string&, F, ErrorF, Params&& ...) [with F = void (*)(int, const unsigned int*); ErrorF = int (*)(); Params = {int, unsigned int*}; std::__cxx11::string = std::__cxx11::basic_string]’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:88:24:   required from ‘int tflite::gpu::gl::gl_call_internal::CallAndCheckError(const string&, F, ErrorF, Params&& ...) [with F = void (*)(int, const unsigned int*); ErrorF = int (*)(); Params = {int, unsigned int*}; std::__cxx11::string = std::__cxx11::basic_string]’
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:162:7:   required from here
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:16: error: request for member ‘ok’ in ‘status’, which is of non-class type ‘const int’
     if (status.ok()) return OkStatus();
         ~~~~~~~^~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:38: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     if (status.ok()) return OkStatus();
                                      ^
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:26: error: request for member ‘code’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                   ~~~~~~~^~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:41: error: request for member ‘error_message’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                                  ~~~~~~~^~~~~~~~~~~~~
In file included from /usr/include/EGL/eglplatform.h:119:0,
                 from /usr/include/EGL/egl.h:39,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/portable_gl31.h:21,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_shader.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_program.h:24,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/command_queue.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:26,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:12: error: expression list treated as compound expression in functional cast [-fpermissive]
     return Status(status.code(), status.error_message() + ": " + context);
            ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:25:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/object_manager.h:27,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:29,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h: In instantiation of ‘int tflite::gpu::gl::gl_call_internal::Caller::operator()(const string&, F, ErrorF, Params&& ...) [with F = void (*)(unsigned int, unsigned int); ErrorF = int (*)(); Params = {const unsigned int&, unsigned int&}; std::__cxx11::string = std::__cxx11::basic_string]’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:88:24:   required from ‘int tflite::gpu::gl::gl_call_internal::CallAndCheckError(const string&, F, ErrorF, Params&& ...) [with F = void (*)(unsigned int, unsigned int); ErrorF = int (*)(); Params = {const unsigned int&, unsigned int&}; std::__cxx11::string = std::__cxx11::basic_string]’
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:182:5:   required from here
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:16: error: request for member ‘ok’ in ‘status’, which is of non-class type ‘const int’
     if (status.ok()) return OkStatus();
         ~~~~~~~^~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:38: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     if (status.ok()) return OkStatus();
                                      ^
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:26: error: request for member ‘code’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                   ~~~~~~~^~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:41: error: request for member ‘error_message’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                                  ~~~~~~~^~~~~~~~~~~~~
In file included from /usr/include/EGL/eglplatform.h:119:0,
                 from /usr/include/EGL/egl.h:39,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/portable_gl31.h:21,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_shader.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_program.h:24,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/command_queue.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:26,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:12: error: expression list treated as compound expression in functional cast [-fpermissive]
     return Status(status.code(), status.error_message() + ": " + context);
            ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:25:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/object_manager.h:27,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:29,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h: In instantiation of ‘int tflite::gpu::gl::gl_call_internal::Caller::operator()(const string&, F, ErrorF, Params&& ...) [with F = void (*)(unsigned int, unsigned int); ErrorF = int (*)(); Params = {const unsigned int&, int}; std::__cxx11::string = std::__cxx11::basic_string]’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:88:24:   required from ‘int tflite::gpu::gl::gl_call_internal::CallAndCheckError(const string&, F, ErrorF, Params&& ...) [with F = void (*)(unsigned int, unsigned int); ErrorF = int (*)(); Params = {const unsigned int&, int}; std::__cxx11::string = std::__cxx11::basic_string]’
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:186:5:   required from here
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:16: error: request for member ‘ok’ in ‘status’, which is of non-class type ‘const int’
     if (status.ok()) return OkStatus();
         ~~~~~~~^~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:38: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     if (status.ok()) return OkStatus();
                                      ^
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:26: error: request for member ‘code’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                   ~~~~~~~^~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:41: error: request for member ‘error_message’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                                  ~~~~~~~^~~~~~~~~~~~~
In file included from /usr/include/EGL/eglplatform.h:119:0,
                 from /usr/include/EGL/egl.h:39,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/portable_gl31.h:21,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_shader.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_program.h:24,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/command_queue.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:26,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:12: error: expression list treated as compound expression in functional cast [-fpermissive]
     return Status(status.code(), status.error_message() + ": " + context);
            ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:25:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/object_manager.h:27,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:29,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h: In instantiation of ‘int tflite::gpu::gl::gl_call_internal::Caller::operator()(const string&, F, ErrorF, Params&& ...) [with F = unsigned char (*)(unsigned int); ErrorF = int (*)(); Params = {const unsigned int&}; std::__cxx11::string = std::__cxx11::basic_string]’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:88:24:   required from ‘int tflite::gpu::gl::gl_call_internal::CallAndCheckError(const string&, F, ErrorF, Params&& ...) [with F = unsigned char (*)(unsigned int); ErrorF = int (*)(); Params = {const unsigned int&}; std::__cxx11::string = std::__cxx11::basic_string]’
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:200:21:   required from here
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:16: error: request for member ‘ok’ in ‘status’, which is of non-class type ‘const int’
     if (status.ok()) return OkStatus();
         ~~~~~~~^~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:38: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     if (status.ok()) return OkStatus();
                                      ^
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:26: error: request for member ‘code’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                   ~~~~~~~^~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:41: error: request for member ‘error_message’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                                  ~~~~~~~^~~~~~~~~~~~~
In file included from /usr/include/EGL/eglplatform.h:119:0,
                 from /usr/include/EGL/egl.h:39,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/portable_gl31.h:21,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_shader.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_program.h:24,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/command_queue.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:26,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:12: error: expression list treated as compound expression in functional cast [-fpermissive]
     return Status(status.code(), status.error_message() + ": " + context);
            ^
In file included from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_buffer.h:25:0,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/object_manager.h:27,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:29,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h: In instantiation of ‘int tflite::gpu::gl::gl_call_internal::Caller::operator()(const string&, F, ErrorF, Params&& ...) [with F = void (*)(unsigned int, long int, const void*, unsigned int); ErrorF = int (*)(); Params = {int, unsigned int, unsigned char*, int}; std::__cxx11::string = std::__cxx11::basic_string]’:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:88:24:   required from ‘int tflite::gpu::gl::gl_call_internal::CallAndCheckError(const string&, F, ErrorF, Params&& ...) [with F = void (*)(unsigned int, long int, const void*, unsigned int); ErrorF = int (*)(); Params = {int, unsigned int, unsigned char*, int}; std::__cxx11::string = std::__cxx11::basic_string]’
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/runtime/shared_buffer.h:62:5:   required from here
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:16: error: request for member ‘ok’ in ‘status’, which is of non-class type ‘const int’
     if (status.ok()) return OkStatus();
         ~~~~~~~^~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:73:38: error: cannot convert ‘tflite::gpu::Status’ to ‘int’ in return
     if (status.ok()) return OkStatus();
                                      ^
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:26: error: request for member ‘code’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                   ~~~~~~~^~~~
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:41: error: request for member ‘error_message’ in ‘status’, which is of non-class type ‘const int’
     return Status(status.code(), status.error_message() + ": " + context);
                                  ~~~~~~~^~~~~~~~~~~~~
In file included from /usr/include/EGL/eglplatform.h:119:0,
                 from /usr/include/EGL/egl.h:39,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/portable_gl31.h:21,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_shader.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_program.h:24,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/command_queue.h:23,
                 from /mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/api.h:26,
                 from gl/api.cc:16:
/mnt/usbdisk2/tensorflow/tensorflow/lite/delegates/gpu/gl/gl_call.h:74:12: error: expression list treated as compound expression in functional cast [-fpermissive]
     return Status(status.code(), status.error_message() + ": " + context);
            ^
Makefile:120: ターゲット 'gl/api.o' のレシピで失敗しました
make: *** [gl/api.o] エラー 1

FYI, I could build gl_delegate.dll on Windows using this Makefile. But currently it does not work on Windows. (but this should be another issue)

Compilation issues aside, gl_delegate uses OpenGLES compute shaders for GPU computations. These require OpenGL ES 3.1, and AFAIK Raspberry Pi supports only OpenGLES 2.0

Ah. Thanks your pointing this.

Without an issue of GLES's version, current implementation of gpu/gl always require gcc8. Older version of gcc(or clang) can not handle Caller<void>(....) and calling with non-void. This is defined in gl/gl_caller.h:88

@mattn
The GPU delegates have only been tested with very specific use cases in mind: on Android and iOS.  For Android, you want the right NDK/SDK versions for it to build, and we haven't made too much effort to "maybe??? work on some other platforms".  Having said that, we heavily rely on the specific NDK/SDK toolchains that can cross compile for Android ARM 64-bit architectures with bazel and that also makes an assumption of the supported GCC, I guess.
You're essentially trying to make it work for an unsupported case and you would be on your own.

Thanks. Yes, I understand that Raspberry Pi does not have enough feature to do this. I'm just thinking whether there are possibilities that can be backported to non-compute-shader.

FYI, yesterday, I could build & run simple app gpu enabled on Linux (not raspberry pi) with #27504.
https://github.com/mattn/tflite-sin
This works without errors. (But I didn't make sure this used GPU for this simple app using sigmoid/sgd)

@mattn
FYI In a previous implementation, we did have a non-compute shader-based implementation for GLES3.  However, on those "phones", the GPU was not powerful enough so that it didn't give a big performance boost either, that we eventually dropped that completely.
Of course, I have no idea about how GLES2 on RPi would perform; that's why I put "phones" in quotes ;)

Hmm, I hope to good to get performance on Raspberry Pi. :/

@mattn
The GPU delegates have only been tested with very specific use cases in mind: on Android and iOS. For Android, you want the right NDK/SDK versions for it to build, and we haven't made too much effort to "maybe??? work on some other platforms". Having said that, we heavily rely on the specific NDK/SDK toolchains that can cross compile for Android ARM 64-bit architectures with bazel and that also makes an assumption of the supported GCC, I guess.
You're essentially trying to make it work for an unsupported case and you would be on your own.

which version of NDK do we need to build libtflite_gpu_gl?

The version we're now recommending is NDK r17c or r18b, with a target NDK API version of 18.

The version we're now recommending is NDK r17c or r18b, with a target NDK API version of 18.

Thanks for the reply, I will try to build with ndk r18b~

I already replied to @mattn in #27504, but in case people are experiencing a similar problem but not aware of that thread:

I ran into this problem of Status conflicting with X11 int when trying to use TFLite GPU on desktop. It turns out EGL/egl.h pulls in EGL/eglplatform.h which pulls in X11/Xlib.h & X11/Xutil.h. To bypass that, I built things with with
-DMESA_EGL_NO_X11_HEADERS
Of course, this may be different on RPi, but I would suggest looking tat the EGL include headers and make things work to exclude X11 includes.

Is there roadmap visibility when Raspberry Pi 4 GPU will be a supported TFLite GPU delegate?

Nothing planned as for now, so no roadmap visibility to share.

It has been confirmed that the videocore gpu on Raspberry Pi 3/4 does not perform well with performance even when enabled.

Thank you for the update. Would you mind publishing your findings so we can
get the Raspberry Pi authors and community to work on improvements?
On Mon, Jul 13, 2020 at 7:39 PM mattn<EMAIL_ADDRESS>wrote:

It has been confirmed that the videocore gpu on Raspberry Pi 3/4 does not
perform well with performance even when enabled.
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You are receiving this because you commented.
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As far as I can tell the primary requirement for GPU accelerated TFlite is an openGLES 3.1 capable GPU with a corresponding API.
The RPi4 VC6 GPU now has OpenGLES 3.1 support using recent Mesa 3D builds.
I haven't got a RPi4 to hand at the moment to try it out, but are there any other roadblocks to successful GPU acceleration, ie will the source compile correctly if OpenGLES 3.1 is supported?
Cheers

@mattn
@JHollandaise
this could be helpful
https://github.com/BenjaminWegener/tensorflow_lite_gpu_python/commit/b1fcd1b51c039fca0408eccf49cea77d3bbee2c5
https://github.com/BenjaminWegener/tensorflow_lite_gpu_python/commit/9721986c8289c3fce9642526ef7bb799ade5466e


GraphRbacManagementClient fails when not setting baseUri explicitly

Package Name: @azure/graph
Package Version: 4.3.0
Operating system:
[x] nodejs

version: 10.15.0

[ ] browser

name/version:

[x] typescript

version: 3.4.5

Is the bug related to documentation in

[ ] README.md
[ ] source code documentation
[ ] SDK API docs on https://docs.microsoft.com

Describe the bug
When using a GraphRbacManagementClient, requests will fail if you do not explicitly set the baseUri to "https://graph.windows.net"
Error: {"odata.error":{"code":"Request_BadRequest","message":{"lang":"en","value":"Invalid domain name in the request url."},"requestId":"566b2d93-3895-4946-9cc8-8799bef068be","date":"2019-05-24T18:08:39"}}

To Reproduce
Steps to reproduce the behavior:

create GraphRbacManagementClient
call client.signedInUser.get()

Expected behavior
Expect to not need to set this explicitly.
Additional context
Add any other context about the problem here.
I believe the issue is the credentials I'm getting does have an environment (azcli based auth), which causes the base class to set the resourceManagerEndpointUrl as the baseUri: https://github.com/Azure/ms-rest-azure-js/blob/master/lib/azureServiceClient.ts#L46-L49
which prevents the Graph specific default from being respected: https://github.com/Azure/azure-sdk-for-js/blob/master/sdk/graphrbac/graph/src/graphRbacManagementClientContext.ts#L50

Thank you for opening this issue! We are routing it to the appropriate team for follow up.

That is true. As a workaround, please pass the baseUri in the options object for now, till we figure out a solution for this.

@willmtemple The latest version 5.0.1 of the @azure/graph package shouldn't have this issue. If so, please close this issue

Yes, the 5.0.1 patch for the AAD Graph SDK @azure/graph fixed this issue. It was a code-generation issue that only manifested in graph when an Azure environment wasn't configured in the credential (as the issue mentioned in the original report). Setting baseUri manually should not be required as of @azure/graph 5.0.1.


Update Composer dependencies (2023-03-27-00-09)

Visual regression test passed!
View the visual regression test report


Suggestion to change the project structure

Hii @jillro,
I would like to suggest a better project structure to organize the codebase efficiently by using a standardized structure followed by a lot of other developers. There is even a somewhat popular template I had come across in Obsidian community few times, which is following the project structure I have proposed : https://github.com/emilio-toledo/obsidian-svelte-plugin
Although I always like to keep the main.ts file, the entry file, in the root of the project. You can find my implemented changes here : https://github.com/tu2-atmanand/obsidian-notes-explorer
I would also like to mention that, I made massive changes in my fork and initially created a huge PR in a hope to first discuss the same in the PR itself. But I understood my mistake and as per your suggestions from the README as well, I would like to first discuss it here, and if you think my changes are a good approach for an elastic project structure, I would like to create a PR for the same. (You can close the old PR)
This will be the first step for me to create more PRs to suggest the various other features I have implemented in my fork. I guess this way I can continue to contribute with the best I can.
Let me know how we can proceed with the same, so the plugin always remains updated which satisfies the need of all its users by integrating all the FRs and fixing all the issues. I would also like to know if I can help in any way to maintain the plugin and keep its development active.

Hi @tu2-atmanand, so what files would end up where - which files would you move, and where to?

Yes, so earlier the structure was :
components folder, settings.ts, view.ts files were in the root folder of the project. But proceeding further with the development, there might be a need to add more files. As I have added few in my fork : https://github.com/tu2-atmanand/obsidian-notes-explorer
So, I would suggest moving the folder and the two mentioned files inside a new directory called src.
Also, as I mentioned earlier, I personally like to keep the main.ts file in the root folder. But a lot of developers also prefer it to be moved inside src folder itself. So, it can be done as well, I am fine with both ways.

Thanks.
Reasons for doing this rearrangement:

it makes it a bit easier to search just the project source code, such as in IDEs
Obsidian policy: these days, when developers submit new plugins, if source files are at the top level, the Obsidian reviewer will ask for them to be moved to a sub-directory, saying something like "for ease of review and future maintenance".
it opens up the possibility of a tests directory in future

Hii @jillro ! Glad to hear from you on my contributions.
I believe you’ve reviewed the initial PR I submitted. The reason for my rather inconsiderate submission was that I thought our timings might not align. Since this is an open-source platform, we can’t always be sure when we’ll be available to contribute effectively. As a result, I jumped straight into implementing the ideas I had in mind rather than focusing on proper documentation of my work through commits and PRs.
I presumed you might had first merged the submitted 45 commits and then fine-tune the code to align with your vision for this plugin, because I think you might not be interested in integrating few of the functionalities of my own I have integrated (although Ill be submitting Issues for the same). Or, I submitted the PR thinking you might refer to my code to expedite the work of implementing the new functionalites. (This is the developer mentallity I had while working in other organizations).
Now, let me get to the main point I want to share. I would like to know your (and also other developers') opinions on the development and contribution workflow I follow. You can read more about it here: https://tu2-atmanand.github.io/task-board-docs/docs/Advanced/HowToJoinDevelopment/.
Using this workflow, you can maintain a specific branch in your repository for contributions from other developers. Where once any developer submits any PR, after reviewing the commits, you can directly merge it into this special branch. Then you can refine the code (add/delete/organize), as needed, and finally merge it into the main branch after thorough testing to release a new version.
This approach allows me to submit a collection of commits at once for a particular functionality I’ve implemented. Sometimes, after integrating a feature, I identify new bugs during testing and fix them, which results in multiple commits.
I would love to hear your and other developers' thoughts on this approach.

That sounds like a different topic to me.
Much better to keep this one focused on changing the project structure, may I suggest.

That sounds like a different topic to me.
Much better to keep this one focused on changing the project directory structure, may I suggest.

Actually, I'm going to step away from this now - I've appreciated the opportunity to share suggestions, but really all that matters is @jillro's views...
Good luck with the projects, everyone...

I agree that creating a src folder would improve developer experience, and I will do it myself very quick.
Aside from that, please try to stick to one topic, one issue. For your contributions, just try to make clear PR, with clean commit history and good commit messages. The project being small and young, there is no need for a complex workflow for contributions.


add flake8-bugbear for better python code contructs

I guess it just writes warnings but doesn't trigger failures?

Since the build is green, and I don't see any other changes, does this mean our code is already perfect?

I think there are no error pertaining to flake8-bugbear as yet in our code. But I found it's errors reporting on code really useful.

I guess it just writes warnings but doesn't trigger failures?

No errors in our code as yet. But any future additions that has such issues dhould trigger a failure.


Deprecation messages

getting these messages when I load up app
Container#eachAtRule is deprecated. Use Container#walkAtRules instead.
Container#eachRule is deprecated. Use Container#walkRules instead.
Container#eachDecl is deprecated. Use Container#walkDecls instead.
Node#before is deprecated. Use Node#raws.before
Node#removeSelf is deprecated. Use Node#remove.

Yeah, thank you for the info. It is a problem with the postcss plugins, used by require hook. Plugins expect postcss version 4 and should be updated in order to be used with version 5.
I'll link this ticket to the actual one to keep you informed. https://github.com/css-modules/css-modules-loader-core/issues/21

I think that it was solved now. Checkout the second version.


Update of lmieulet:meteor-coverage

Newer versions of the following dependencies are available:

lmieulet:meteor-coverage 1.1.4 (2.0.2 is available)

This is up to you and the rest of your project configuration. The package.js file allows the usage of version 1.1.4 and 2.0.2 and all the coming bugfix- and feature releases of both versions, according to https://docs.meteor.com/api/packagejs.html#PackageAPI-use
https://github.com/meteortesting/meteor-mocha/blob/26bfceeaeb6febe289680b14a9496b7e1d195dc9/package/package.js#L13-L15
If you want to use the version 2.0.2, please add it as a requirement in your project configuration and Meteor will automatically use it - provided you don't have another extension installed which explicitly requires a version of 1.x.x.

@aldeed  lmieulet:meteor-coverage < 2.0.2 had an unspecified dependency on the jquery package. But since it got removed from meteor core packages, this is now breaking a lot of new applications that don't depend on the jquery package anymore...

I don't know it for sure, but doesn't the package.js file decide which version to install? Because this file states:
https://github.com/meteortesting/meteor-mocha/blob/26bfceeaeb6febe289680b14a9496b7e1d195dc9/package/package.js#L14
I've searched through many posts here and there but couldn't find any suitable answer but this https://guide.meteor.com/writing-atmosphere-packages.html#version-constraints stating:

Note that the version solver also has a concept of “gravity” - when many solutions are possible for a certain set of dependencies, it always selects the oldest possible version. This is helpful if you are trying to develop a package to ship to lots of users, since it ensures your package will be compatible with the lowest common denominator of a dependency. If your package needs a newer version than is currently being selected for a certain dependency, you need to update your package.js to have a newer version constraint.

This means as long as you do not enforce it to use the version 2.x, it will stick to the old version if you only install it because it won't update beyond a feature-release. Major updates must be enforced if you want them to happen - or we remove the compatibility to 1.x ... even though it still is compatible ...

@SimonSimCity you're absolutely right, but this PR is removing 1.x compatibility, which is what I'm arguing for. Because a lot of people that upgrade Meteor might suddenly lose the jquery package. Then they would need to start figuring out they have to upgrade lmieulet:meteor-coverage which usually is not a direct dependency of them, but they get through this package. So especially less experienced Meteor users could lose quite some time on what's going wrong.
Now, I would agree that the more correct solution would be to have lmieulet:meteor-coverage release a new version in the 1.x range that specifies the jquery dependency. And that way you can remain compatibility with 1.x and not suddenly break things.

[...] but this PR is removing 1.x compatibility [...]

Is it really? If I'm right in what I wrote, this will not affect anything but the test environment of this extension because we haven't changed the package.js file.

Oops, I somehow thought this PR was actually changing the package.js file. My bad.

Yeah I believe .versions is rebuilt every time we meteor publish the package so this would get overwritten. It could be redone as a package.js PR if still necessary


New features

I have implemented 2 functions:

disable mirror for own video (in settings)
hide self view - hide own videos (main + extra) and screen sharing

I'm on holidays now, but if I find an hour I can make a pull request. Should I?

Yes

I will do it next week, I'm on holidays now.

Let's wait for Stefan @so010 review..

I will close this issue, let's cont on PR's


Feat/Add valkey performance testing terraform configs

The PR publishes the work done at https://github.com/3scale/platform/issues/1450 regarding performance tests of valkey/redis on AWS EC2/Elasticache.

Adding terraform configs
Adding a README with the configuration applied, and the commans to run each server (valkey/redis) or valkey-benchmark tool

/approve

/approve


feat(bundlerops): extending supported bundler operations list

Description
This PR extending supported bundler operations list with the following new operations:

eth_estimateUserOperationGas
pm_sponsorUserOperation

New operations are required for the shared library to use the bundler ops API endpoint.
The API SPEC updating PR: https://github.com/WalletConnect/walletconnect-specs/pull/254
How Has This Been Tested?

Not tested.

Due Diligence

[ ] Breaking change
[ ] Requires a documentation update
[ ] Requires a e2e/integration test update

pm_sponsorUserOperation

I believe it's right because I see pm_sponsorUserOperation also in the yttrium source code.


To review the way that identified graphs that are associated to the trigger are matched and attached in the message

Currently in v1.11 the matching process looks for an exact item id match before embedding a graph into the message. However as multiple items may be related to a trigger, any graphs associated to these items could also be picked hence increasing the chance of finding a graph that can be associated to the trigger.

v1.15 has config.json and code that will allow selection of graphs via graph_match set to 'exact' (exact item id) or 'any' (any item id in the trigger).


Auto Sort icons alphabetically?

Is there a way either through css or another process to sort the icons alphabetically by bookmark name? Dragging is a bit tedious and I also have to display the text to figure out which icon should go where. Any tips or tricks are much appreciated:-)

There's no way to sort alphabetically now but that's an interesting idea.  Dragging is the only way (outside of exporting the settings and manually editing them in a text editor).  I'll add this to the list

Thanks. I actually thought I'd editing the settings but the code was to dense to decipher in text edit for Mac. By the way you also mention custom CSS. Where can I find the proper CSS values to enter and do I have to use !important to override the default settings?


When graph's title has multiple lines of text or graph contains sub-title, only the first line of the title is displayed

When graph's title has multiple lines of text or graph contains sub-title, only the first line of the title is displayed in the generated image file.
SVG string: https://www.dropbox.com/s/55wde9einohm08r/chart.svg

is this issue fixed somehow? or was it a non issue?


fix(workflows): Update Dart setup version and package dependencies

Updated the Dart setup version in workflows to v1.6.4 and dev dependencies versions for dart_code_linter to v1.1.3 and test to v1.25.4, also fixed some typos

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Warning: This coverage report may be inaccurate.
This pull request's base commit is no longer the HEAD commit of its target branch. This means it includes changes from outside the original pull request, including, potentially, unrelated coverage changes.

For more information on this, see Tracking coverage changes with pull request builds.
To avoid this issue with future PRs, see these Recommended CI Configurations.
For a quick fix, rebase this PR at GitHub. Your next report should be accurate.

Details

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 100.0%

Totals

Change from base Build<PHONE_NUMBER>:
0.0%

Covered Lines:
30

Relevant Lines:
30

💛  - Coveralls


Enhance Styles v7

Proposed breaking changes for next major version of Enhance Styles
Emit only custom properties
Users should be able to configure Enhance Styles to only emit custom properties so that folks who want to use those without utility classes may do so.
Current modules which export custom styles:

type scale
space scale
theme
color

This would need to be compatible with another desired change, which is:
Make files, config, and output 1:1
Users should be able to opt out of any modules they don't require. Currently the styleguide.json allows for configuring some fields; most have defaults if no configuration is specified, some (like color) do not. We should unify the configuration file with the range of available modules for utility classes, such that all modules are included by default, but users can choose to opt out of certain modules if they prefer. For example, to configure the type scale but opt out of background- classes:
{
  "typeScale": {…},
  "background": false,
}

https://discord.com/channels/1012099764713705472/1059964929681141870/1222028737747353621

Closing this in favour of this project; issues will be created from that project as they are take on.


503 - unable to reach the service from client pod

i have  a deployment,  once the  service is created client pods are unable to call the service or the app pod as the sidecar returns
"503 upstream connect error or disconnect/reset before headers. reset reason: connection failure"
if i remove the service  able to reach the app pod.
when i deploy this manifests to a namespace that does not have istio injection enabled it works without a issue and able to reach the service or  app pod
[ ] Docs
[ ] Installation
[X] Networking
[ ] Performance and Scalability
[ ] Extensions and Telemetry
[ ] Security
[ ] Test and Release
[ ] User Experience
[ ] Developer Infrastructure
Expected behavior
access the service ,app pod from client pods.
Steps to reproduce the bug

connecting to the service , app pod from curl container

conn         ClusterIP   <IP_ADDRESS>   <none>        8082/TCP   19m

[ root@curl:/ ]$ curl -v http://conn:8082
> GET / HTTP/1.1
> User-Agent: curl/7.35.0
> Host: conn:8082
> Accept: */*
>
< HTTP/1.1 503 Service Unavailable
< content-length: 91
< content-type: text/plain
< date: Fri, 25 Sep 2020 16:46:21 GMT
< server: envoy
< x-envoy-upstream-service-time: 42
<
upstream connect error or disconnect/reset before headers. reset reason: connection failure[ root@curl:/ ]$
[ root@curl:/ ]$ curl http://<IP_ADDRESS>:8083
upstream connect error or disconnect/reset before headers. reset reason: connection failure[ root@curl:/ ]$

remove the service and connect to the app pod
[opc@fusionx-rnd-vm ~]$ k delete svc conn
service "conn" deleted
[opc@fusionx-rnd-vm ~]$ k exec -ti curl -- sh
Defaulting container name to curl.
Use 'kubectl describe pod/curl -n default' to see all of the containers in this pod.
sh: shopt: not found
[ root@curl:/ ]$ curl http://<IP_ADDRESS>:8083
{"version":"2.3.0","commit":"fc1aaa116b661c8a","kafka_cluster_id":"OSS"}[ root@curl:/ ]$

Version (include the output of istioctl version --remote and kubectl version --short and helm version if you used Helm)
client version: 1.6.7
control plane version: 1.6.7
data plane version: 1.6.7 (6 proxies)
Client Version: v1.19.0
Server Version: v1.19.2
How was Istio installed?
istioctl manifest apply --set profile=demo   --set values.global.mtls.auto=false   --set values.global.mtls.enabled=false
Environment where bug was observed (cloud vendor, OS, etc)
minikube version: v<IP_ADDRESS>.7, kubernetes v1.19.0
OKE , v1.15.7
deployment_manifest.zip
istio-dump.tar.gz

Does the connectorqa app listen on pod IP, localhost, or <IP_ADDRESS>? You can see with netstat -nl from the pod (proxy container has it if your app does not)

this is the output
NAME                          READY   STATUS    RESTARTS   AGE   IP            NODE       NOMINATED NODE   READINESS GATES
connectorqa-cc8b54bb9-gpktr   2/2     Running   701        26d   <IP_ADDRESS>   minikube   <none>           <none>

[opc@fusionx-rnd-vm ~]$ k exec connectorqa-cc8b54bb9-gpktr -c kcbackgrnd -- netstat -nl
Active Internet connections (only servers)
Proto Recv-Q Send-Q Local Address           Foreign Address         State
tcp        0      0 <IP_ADDRESS>:15090           <IP_ADDRESS>:*               LISTEN
tcp        0      0 <IP_ADDRESS>:8083        <IP_ADDRESS>:*               LISTEN
tcp        0      0 <IP_ADDRESS>:15000         <IP_ADDRESS>:*               LISTEN
tcp        0      0 <IP_ADDRESS>:15001           <IP_ADDRESS>:*               LISTEN
tcp        0      0 <IP_ADDRESS>:34012           <IP_ADDRESS>:*               LISTEN
tcp        0      0 <IP_ADDRESS>:15006           <IP_ADDRESS>:*               LISTEN
tcp        0      0 <IP_ADDRESS>:15021           <IP_ADDRESS>:*               LISTEN
tcp6       0      0 :::15020                :::*                    LISTEN
Active UNIX domain sockets (only servers)
Proto RefCnt Flags       Type       State         I-Node   Path
unix  2      [ ACC ]     STREAM     LISTENING     288851   ./etc/istio/proxy/SDS

<IP_ADDRESS>:8083

This shows its listening on the Pod IP. Istio requires the app to listen on <IP_ADDRESS> or <IP_ADDRESS> currently. This is a very under documented area, which I am working on fixing, as well as an open PR to support this: https://github.com/istio/istio/pull/28178

Closing as this is working as expected; this wil be supported in newer versions (per api above). Thanks!

Closing as this is working as expected; this wil be supported in newer versions (per api above). Thanks!


test: run tmt integration test on testing farm

This PR follows https://github.com/containers/bootc/pull/593 to run tmt integration test on testing farm. Two plan files has to be added:

build.fmf: tmt plan file used to deploy testing farm runner and run tmt integration on the runner
build-tmt.fmf: tmt test file used to make .git always present. Only discover.fmf setting is able to make tmt copy the git root instead of fmf root to the test directory

Testing farm:

Command: testing-farm request --plan /build --git-url https://github.com/henrywang/bootc.git --git-ref tf_run --compose Fedora-40 --arch x86_64
Result log (x86_64): https://artifacts.osci.redhat.com/testing-farm/6bd48984-4aaf-4dd1-9f85-cec5e1d11ce1/
Duration: less than 10 minutes.

Command: testing-farm request --plan /build --git-url https://github.com/henrywang/bootc.git --git-ref tf_run --compose Fedora-40 --arch x86_64

Cool. Just so I understand though, we haven't wired up this to PRs here, right?

Cool. Just so I understand though, we haven't wired up this to PRs here, right?

Right. PR https://github.com/containers/bootc/pull/615 finished tmt integration test.


[FEATURE]: Re-executing job

Hey!
The current implementation of the plugin does not allow for the re-execution of jobs for specific entries or the addition of entry rules for skipping in the job. This limitation poses challenges when it comes to handling certain records in the collection type.
I would like to propose an enhancement to the plugin that enables the re-execution of jobs for specific entries (update translated entries with new values from the translation service) and the ability to add entry rules for skipping. This would provide greater flexibility and control over the execution of jobs, allowing for a more tailored and efficient workflow.
Is it possible in the future? Do you have plans for that?
Thank you!

Closed as duplicate of #109.
It is already availabe on the next channel


Upstream the changes from bug 1431533

Bug 1431533 part 5a (https://hg.mozilla.org/mozilla-central/rev/e6a7b5e11ba8) included a mass rewrite changing all instances of Components.utils.import to ChromeUtils.import. We should upstream those too.

Thanks for the pointer; however this was taken care of in commit https://github.com/mozilla/pdf.js/commit/4db49b6613401a336f68098656e56e1fca442895, which was included in PR #9433.

Looks like there's a bit of a whitespace issue in PdfJs.jsm, though.
https://github.com/mozilla/pdf.js/commit/4db49b6613401a336f68098656e56e1fca442895#diff-fac62551eadfe79f141900988b8e8a8dL52

Looks like there's a bit of an indentation issue in PdfJs.jsm, though.

Whoops, I was mostly using ESLint to automatically apply the changes and forgot to manually re-indent that; sorry if this caused you unnecessary merge conflicts!
Unless you need this fixed right away, I'll just address it when upstreaming the changes from https://bugzilla.mozilla.org/show_bug.cgi?id=1432992 since that one looks pretty close to landing.

I think it's fine to wait. I just dropped that hunk from the update I did
today.
On Mon, Feb 5, 2018 at 2:43 PM, Jonas Jenwald<EMAIL_ADDRESS>wrote:

Looks like there's a bit of an indentation issue in PdfJs.jsm, though.
Whoops, I was mostly using ESLint to automatically apply the changes and
forgot to manually re-indent that; sorry if this caused you unnecessary
merge conflicts!
Unless you need this fixed right away, I'll just address it when
upstreaming the changes from https://bugzilla.mozilla.org/
show_bug.cgi?id=1432992 since that one looks pretty close to landing.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
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Proposal for improving section "Attach to an app from the XAML designer"

Recently, I needed to debug a custom XAML control at design time. I tried this by following the documentation available for that topic. However, I just couldn't make it work. Eventually, I created an issue regarding this here. A Micrososft engineer's response (see comments) to that issue finally pointed out the missing steps required to make design time debugging work for me.
I have combined the steps given by that Microsoft engineer and those given in the existing documentation and created my own description on how to debug XAML controls at design time. My proposal is to change the documentation as follows:
Instead of the title Attach to an app from the XAML designer I propose Debug a custom XAML control at design time by attaching to Visual Studio's XAML designer.
Replace the steps associated with the above mentioned title with the following description:

Open your solution/project in a first Visual Studio instance.
Build the solution/project.
Open the XAML page containing the custom control you want to debug.
For UWP projects targeting Windows build 16299 or above, this step will start the UwpSurface.exe process. For WPF or UWP versions prior to 16299, this step will start the XDesProc.exe process.
Open a second Visual Studio instance. Do not open a solution/project in that instance.
In the second Visual Studio instance open the "Debug" menu and choose "Attach to Process…".
Depending on your project (see step 3), select either the UwpSurface.exe or the XDesProc.exe process from the list of available processes.
In the "Attach to:" field of that dialog, choose the correct code type for the custom control you want to debug. If your custom control has been written in a .NET language, choose the appropriate .NET code type such as "Managed (CoreCLR)". If your custom control has been written in C++, choose "Native".
Attach the second Visual Studio instance by clicking the "Attach button".
In the second Visual Studio instance open the code files associated with the custom control you want to debug. Make sure to just open these files, not the entire solution/project.
Place the necessary breakpoints in the previously opened files.
In the first Visual Studio instance close the XAML page you opened in step 3.
In the first Visual Studio instance open the XAML page you closed in the previous step. This will cause the debugger to stop at the first breakpoint you set in the second Visual Studio instance.
Debug the code in the second Visual Studio instance.

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

ID: c195bbb1-22be-9da7-9792-1c829d73a21b
Version Independent ID: 0d83875a-56c4-d897-e771-aa3ef9bf910d
Content: Debug at design time - Visual Studio
Content Source: docs/debugger/walkthrough-debugging-at-design-time.md
Product: visual-studio-windows
Technology: vs-ide-debug
GitHub Login: @Mikejo5000
Microsoft Alias: mikejo

@ackh -- thank you for your feedback and thorough improvements.

Good feedback, thanks! Updating doc.


Kf 3006 feat seldon rock integration

Summary of changes:
- Updated ROCK definition.
- Updated tests.
CI might not pass due to resource limitation in Github runner that prevents some integration test in Seldon Core Operator from completion.
All tests pass locally:
$ tox -e integration
integration: recreate env because requirements removed: google-auth==2.19.0 pytz==2023.3 jujubundlelib==0.5.7 aiohttp==3.8.4 charmed-kubeflow-chisme==0.0.9 async-timeout==4.0.2 attrs==23.1.0 ptyprocess==0.7.0 ordered-set==4.1.0 wcwidth==0.2.6 kubernetes==26.1.0 mypy-extensions==1.0.0 paramiko==2.12.0 parso==0.8.3 websockets==7.0 aiosignal==1.3.1 asttokens==2.2.1 juju==<IP_ADDRESS> oauthlib==3.2.2 pygments==2.15.1 decorator==5.1.1 theblues==0.5.2 bcrypt==4.0.1 tomli==2.0.1 deepdiff==6.2.1 h11==0.14.0 websocket-client==1.5.2 packaging==23.1 yarl==1.9.2 macaroonbakery==1.3.1 multidict==6.0.4 markupsafe==2.1.2 lightkube-models==<IP_ADDRESS> pyasn1==0.5.0 requests-oauthlib==1.3.1 pymacaroons==0.13.0 ruamel-yaml-clib==0.2.7 ruamel-yaml==0.17.28 backcall==0.2.0 certifi==2023.5.7 httpcore==0.17.2 tenacity==8.2.2 httpx==0.24.1 traitlets==5.9.0 pynacl==1.5.0 cffi==1.15.1 stack-data==0.6.2 frozenlist==1.3.3 requests==2.31.0 urllib3==1.26.16 pytest==7.3.1 cryptography==40.0.2 iniconfig==2.0.0 ops==2.2.0 matplotlib-inline==0.1.6 exceptiongroup==1.1.1 typing-extensions==4.6.2 typing-inspect==0.9.0 prompt-toolkit==3.0.38 pyasn1-modules==0.3.0 anyio==3.6.2 pluggy==1.0.0 six==1.16.0 cachetools==5.3.0 sniffio==1.3.0 executing==1.2.0 toposort==1.10 pyrfc3339==1.1 charset-normalizer==3.1.0 pyyaml==6.0 pure-eval==0.2.2 idna==3.4 pytest-asyncio==0.21.0 protobuf==3.20.3 pickleshare==0.7.5 pycparser==2.21 ipython==8.12.2 jedi==0.18.2 ipdb==0.13.13 pytest-operator==0.27.0 python-dateutil==2.8.2 rsa==4.9 pexpect==4.8.0 jinja2==3.1.2 lightkube==0.13.0
integration: remove tox env folder /home/ubuntu/rocks/seldonio-rocks/seldon-core-operator/.tox/integration
integration: install_deps> python -I -m pip install charmed_kubeflow_chisme 'juju~=2.9.0' ops pytest pytest-operator
integration: commands[0]> rockcraft pack
Launching instance...
Retrieved base ubuntu:22.04 for amd64
Extracted ubuntu:22.04
Executed: skip pull seldon-core-operator (already ran)
Executed: skip pull mpl-deps (already ran)
Executed: skip pull non-root-user (already ran)
Executed: skip pull pebble (already ran)
Executed: skip pull security-team-requirement (already ran)
Executed: skip overlay seldon-core-operator (already ran)
Executed: skip overlay mpl-deps (already ran)
Executed: skip overlay non-root-user (already ran)
Executed: skip overlay pebble (already ran)
Executed: skip overlay security-team-requirement (already ran)
Executed: skip build seldon-core-operator (already ran)
Executed: skip build mpl-deps (already ran)
Executed: skip build non-root-user (already ran)
Executed: skip build pebble (already ran)
Executed: skip build security-team-requirement (already ran)
Executed: skip stage seldon-core-operator (already ran)
Executed: skip stage mpl-deps (already ran)
Executed: skip stage non-root-user (already ran)
Executed: skip stage pebble (already ran)
Executed: skip stage security-team-requirement (already ran)
Executed: skip prime seldon-core-operator (already ran)
Executed: skip prime mpl-deps (already ran)
Executed: skip prime non-root-user (already ran)
Executed: skip prime pebble (already ran)
Executed: skip prime security-team-requirement (already ran)
Executed parts lifecycle
Created new layer
Entrypoint set to ['/bin/pebble', 'enter', '--verbose']
Labels and annotations set to ['org.opencontainers.image.version=v1.15.0_22.04_1', 'org.opencontainers.image.title=seldon-core-operator', 'org.opencontainers.image.ref.name=seldon-core-operator', 'org.opencontainers.image.licenses=Apache-2.0', 'org.opencontainers.image.created=2023-06-02T18:58:01.377502+00:00', 'org.opencontainers.image.base.digest=dc0d5441e7cf0f2015bede5eccac3a95b8cb8264c47aeb48f6d1d04b453b4177']
Exported to OCI archive 'seldon-core-operator_v1.15.0_22.04_1_amd64.rock'
integration: commands[1]> rm -rf charm_repo
integration: commands[2]> git clone --branch main https://github.com/canonical/seldon-core-operator.git charm_repo
Cloning into 'charm_repo'...
remote: Enumerating objects: 1217, done.
remote: Counting objects: 100% (221/221), done.
remote: Compressing objects: 100% (98/98), done.
remote: Total 1217 (delta 154), reused 154 (delta 117), pack-reused 996
Receiving objects: 100% (1217/1217), 576.63 KiB | 4.24 MiB/s, done.


[MRG] Add doc note to annotations_from_events function

Reference issue
Closes: #8457
What does this implement/fix?
Adds a section on notes for annotations_from_events to remind users to invert dictionary.

Thanks @adam2392


python310Packages.pyotgw: 2.0.3 -> 2.1.0

Description of changes
https://github.com/mvn23/pyotgw/blob/master/CHANGELOG.md#210

Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
22.11 Release Notes (or backporting 22.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 196093 run on x86_64-linux 1

3 packages built:

home-assistant-component-tests.opentherm_gw
python310Packages.pyotgw
python39Packages.pyotgw


H6147 Appears in Homebridge but Doesn't Actually Work

I have  a couple Govee products that work fine with the plugin (v 7.9.0), but just added a H6147 lightstrip that is having an issue. The light strip shows up in Homekit no problem, and says it's off. But when I try to turn on, it spins for awhile and then says "No Response". Eventually the no-response state reverts back to just being Off. But it never can turn on (or off if I turn it on manually). Running Homebridge (v 1.6.0) on a dedicated Pi with no other issues and over 100 devices.
[1/23/2023, 1:29:16 PM] [Govee] [Game Room] could not connect as Error: Peripheral already connected.
[1/23/2023, 1:29:23 PM] [Govee] [Game Room] could not find device [d4:ad:fc:bf:16:80].
[1/23/2023, 1:29:23 PM] [Govee] [Game Room] could not be updated as no connection method available at file:///usr/lib/node_modules/homebridge-govee/lib/platform.js:1872:13.
[1/23/2023, 1:29:23 PM] [Govee] [Game Room] could not connect as Error: Peripheral already connected.
[1/23/2023, 1:29:30 PM] [Govee] [Game Room] could not find device [d4:ad:fc:bf:16:80].
[1/23/2023, 1:29:30 PM] [Govee] [Game Room] could not be updated as no connection method available at file:///usr/lib/node_modules/homebridge-govee/lib/platform.js:1872:13.
[1/23/2023, 1:29:30 PM] [Govee] [Game Room] could not connect as Error: Peripheral already connected.
[1/23/2023, 1:29:37 PM] [Govee] [Game Room] could not find device [d4:ad:fc:bf:16:80].
[1/23/2023, 1:29:37 PM] [Govee] [Game Room] could not be updated as no connection method available at file:///usr/lib/node_modules/homebridge-govee/lib/platform.js:1872:13.

Is the H6147 bluetooth only?

Is the H6147 bluetooth only?

Not sure about the H6147 but I’m getting this error on the H6053 which is BLE only.

@farhandsome can you update to the beta version of the plugin? 10.15.1-beta.0
In fact just yesterday I was changing some code to try and make the Bluetooth a bit more stable.
Can you see if this makes a difference at all?

@bwp91

Hmm, I'm not seeing that version in the plugin window. Am I needing to update?

Sorry - you should see 10.15.1-beta.1 soon

@bwp91
[12/12/2024, 19:48:28] [Govee] [RGBHanMonitor] could not be updated as Promise timed out after 10000 milliseconds at file:///var/lib/homebridge/node_modules/homebridge-govee/node_modules/p-timeout/index.js:76:24. [12/12/2024, 19:48:38] [Govee] [RGBHanMonitor] could not be updated as Promise timed out after 10000 milliseconds at file:///var/lib/homebridge/node_modules/homebridge-govee/node_modules/p-timeout/index.js:76:24. [12/12/2024, 19:48:39] [Govee] [RGBHanMonitor] starting BLE update with params [{"cmd":1,"data":0}]. [12/12/2024, 19:48:39] [Govee] [RGBHanMonitor] attempting connection with device. [12/12/2024, 19:48:49] [Govee] [RGBHanMonitor] could not be updated as Promise timed out after 10000 milliseconds at file:///var/lib/homebridge/node_modules/homebridge-govee/node_modules/p-timeout/index.js:76:24.
Hey so I just did install the beta and now this is the error I get.


Replace localhost urls to be configurable

In gateway home page, several services links are provided which are with url localhost, to be changed.

it now only works with "docker compose up" demo.


On julia v0.5: Internal Error - EOF not defined

I was using the precompiled Mac binaries for julia v0.4.5. with no problem. I cloned and built julia v0.5.0-rc1+1, did Pkg.add("Atom"). And then opened Atom. I switched the julia path in julia-client settings, and then restarted Atom. It went through the "the first time you run it will take a couple of minutes" thing, and the terminal works (though it spits out a lot of warnings about AbstractString being deprecated).
But any time I type, or even click into a .jl file, errors start popping up in the right side of the window:
UndefVarError: EOF not defined
 in scopes(::LNR.LineNumberingReader{Base.AbstractIOBuffer{Array{UInt8,1}}}, ::LNR.Cursor) at /Users/KBLaptop/.julia/v0.5/CodeTools/src/parse/scope.jl:153
 in codemodule(::String, ::Int64) at /Users/KBLaptop/.julia/v0.5/CodeTools/src/parse/parse.jl:6
 in filemodule_(::String) at /Users/KBLaptop/.julia/v0.5/CodeTools/src/module.jl:93
 in macro expansion at ./dict.jl:689 [inlined]
 in (::CodeTools.##1#2{CodeTools.#filemodule_,Dict{Any,Any}})(::String, ::Vararg{String,N}) at /Users/KBLaptop/.julia/v0.5/CodeTools/src/utils.jl:3
 in modulenames(::Dict{String,Any}, ::LNR.Cursor) at /Users/KBLaptop/.julia/v0.5/Atom/src/eval.jl:10
 in (::Atom.##104#105)(::Dict{String,Any}) at /Users/KBLaptop/.julia/v0.5/Atom/src/eval.jl:24
 in handlemsg(::Dict{String,Any}, ::Dict{String,Any}, ::Vararg{Dict{String,Any},N}) at /Users/KBLaptop/.julia/v0.5/Atom/src/comm.jl:82
 in (::Atom.##5#8)() at ./event.jl:46

MacOS v10.11.6
Atom v1.9.8
julia-client v0.4.7
I tried uninstalling and reinstalling uber-juno, and the Atom.jl package and all dependencies in Julia, still get the same problem.
I then installed the pre-compiled binaries for mac for v0.4.6, and switched the julia path to /Applications/Julia-0.4.6.app/Contents/Resources/julia/bin/julia. This works fine, no errors.
Ditto if I git checkout v0.4.6, build from there and use /usr/bin/julia as the path.

Try Pkg.checkout("CodeTools") (and possibly a few others), until the new versions are tagged.

Tried checking out CodeTools, Ink, Atom - I'm getting slightly different errors, but still getting lots of them on typing and on evaluation... Should I just keep going through the list?

We just did a bunch of releases so you should be able to use the latest tags. Take a look at Pkg.status() and Pkg.free(X) the stuff you checked out, and see how that goes.

This problem is solved, now I'm having others... Will investigate further and report back.


User-agent: * should disallow everything

http://cocon.se/robots.txt has just User-agent: *.  It appears that they expect it to disallow everything.

robots.allowed('http://cocon.se/visualisation/', "*") : False

cocon.se is wrong in that expectation. I don't think we should ignore the actual standard.

Hummm ... With this robots.txt file, Goole allow this Url.
I also tested with Scrapy/Protego, which allow this Url.


Fix String.toFloat

Added handling of NaN and Infinity.
toFloat "1." and toFloat ".1" now result in an error.

Closes #336.

Are you sure NaN / Infinity should even be parsed (as they are not available as literals in Elm)?

I think that toFloat (toString someFloat) should not throw. There are no NaN and Infinity literals in Haskell and read . show is an identity.

How is this pull request related to https://github.com/elm-lang/core/pull/343?

This PR improves String.toFloat by disallowing dangling dots and adding proper handling of NaN and Infinity:
> String.toFloat ".1"
Err ("could not convert string '.1' to a Float") : Result.Result String Float

> 0 / 0
NaN : Float
> String.toFloat (toString (0 / 0))
Ok NaN : Result.Result String Float

> -1 / 0
-Infinity : Float
> String.toFloat (toString (-1 / 0))
Ok -Infinity : Result.Result String Float

Disallowing dangling dots is reasonable because Elm itself does not support them:
> 1 + .1
-- SYNTAX PROBLEM -------------------------------------------- repl-temp-000.elm

I ran into something unexpected when parsing your code!

3│   1 + .1
          ^

The other PR fixes #336 by making String.toFloat "." return an Err. It does not fix String.toFloat "-.", which is still an Ok NaN.

Ah, I see, thanks for clarifying. So, just to be sure: Does this PR solve a superset of the problems that the other PR solves? So the "." case is handled here as well?
My original question was because both PRs are mentioned to adress #336, and the code changes are overlapping, so there would be a conflict if one gets merged.
Am I right that your position is that the other PR should be closed and this one merged?
What about Evan's comment over there, about first using a regular expression to reject invalid strings? Maybe that would simplify the solution here as well, since after that check has passed there are fewer cases to consider?

Yes, that's right.
A regex would indeed simplify the code. Also, Evan's regex allows e notation (e.g. toFloat "1.2e3"), which is currently not supported but should probably be.

e notation is valid as a literal and therefore should be valid in String.toFloat. (Similarly, hex literals should be accepted by String.toInt, although they currently are not.)

So, @slava-sh, are you willing to revise your pull request by using a regex and also supporting e notation?

Yes, I'll do this.

Done.

Cool!
I think this should be part of a bugfix release core-3.0.1, see here, but it's @evancz's to decide.

I added this to #721, but it is very unclear that "Fix String.toFloat" is a legitimate title for this suggestion. In any case, it is now tracked in a meta issue so these decisions can be made in a comprehensive way.


[Improvement](inverted index) delay inverted index col read to reduce IO #26080

Proposed changes
Issue Number: close #xxx
pick from #26080
Further comments
If this is a relatively large or complex change, kick off the discussion at<EMAIL_ADDRESS>by explaining why you chose the solution you did and what alternatives you considered, etc...

run buildall


  So, try to use gradle or maven to build your new project.

Thx~


[Spigot] OTG does not always send updates to client when spawning a BO3 or BO4 in v9_r7

OTG Plugin or Mod

[ ] OTG Mod for Forge
[x] OTG Plugin for Spigot

OTG Version
[Please specify the full OTG version that you are running by placing "x" into []]

[ ] 1.12.2_v8_r1
[ ] 1.12.2-v6
[x] 1.12.2-v9_r7

Description
Whenever a BO3 or BO4 generates in a world, parts of it are cut off on the client side and not updated, creating a lot of ghost blocks.
I loaded Biome Bundle on v9_r7 and got massive ghosting from practically all generating BO3's which persisted until I relogged. I also loaded up the Dungeons preset and noticed some chunks were all ghost blocks.
Fix
I managed to fix this by changing:
notifyAndUpdatePhysics(this.world.getWorld(), blockPos, chunk, oldBlockData, blockData, 2 | 16);
to:
world.getWorld().notifyAndUpdatePhysics(blockPos, chunk, oldBlockData, blockData, 2 | 16);
on line 242 of Bukkit's OTGChunkGenerator. This is what the line was in v8.3.
With that fix, the ghosting with both the BO3's in BB and the BO4's in the dungeon preset appear to be gone.
I didn't submit a PR for this bc it's a tiny fix, and it also doesn't fix whatever is wrong with the new method for updating clients.

Hey @authvin , the customised notifyAndUpdatePhysics method is in there to avoid cascading chunkgen caused by block updates to neighbouring blocks in adjacent chunks when placing blocks on chunk borders. For Forge I've removed this workaround a while ago, I'll do the same for Spigot as you suggest. Not entirely sure how I fixed this anymore, in theory this could cause cascading chunkgen when placing things like torches on walls, fences, redstone etc, will need to test. Have included this for 9.0_r8.


implementing rel="noreferrer"

Hello, I am currently using the latest version of this package available on npm (2.8.1) and am opening this issue per following through on a Lighthouse report I was running against my website, in particular the recommendation that the usage of an anchor tag with the  target="_blank" attribute, e.g.
Click me

should also include noopener noreferrer, e.g.
Click me

I see the latest version in GitHub has support for noopener.  I would like to make a PR to add noreferrer as well.
From that point, when do you think a new version could be available in GitHub?
Thanks for the great library!  ✌

oops, nevermind, I see the recommendation is really that only 1 needs to be set (in this case noopener from this library).
So I guess there isn't anything to do here per se, aside from await a new release of this library.


VERIFY EMAIL BUG

Describe the bug
A clear and concise description of what the bug is.

When i signup using  full name , email and password and am taken to dashboard where there is a banner that says verify your email when i check my email i get verify link when i click on it i get 500 status

If this is happening on the demo, it could be related to libsql or Turso rather than Better Auth. If it's happening locally, please share the server logs so I can help.

Its on demo
On Sun, Oct 20, 2024, 7:09 AM Bereket Engida @.***>
wrote:

If this is happening on the demo, it could be related to libsql or Turso
rather than Better Auth. If it's happening locally, please share the server
logs so I can help.
—
Reply to this email directly, view it on GitHub
https://github.com/better-auth/better-auth/issues/251#issuecomment-2424552257,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AUNJ2QZQUHNMVUX6X2M4TALZ4MUF7AVCNFSM6AAAAABQH2CEE6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDIMRUGU2TEMRVG4
.
You are receiving this because you authored the thread.Message ID:
@.***>

please try it again and let me know if it's still an issue.

i got the same error

i got the same error

My error was an drizzle error:
https://github.com/drizzle-team/drizzle-orm/issues/1113#issuecomment-2290376956

I think this should be fixed past v1. Feel free to re-open if not.


Updated the hyperlink

Describe the proposed changes
URL (which is text)is updated with hyperlink
Unreleased project version

Related issue

Related issue or PR in another project

Please take a look

https://docs.docker.com/engine/installation/ubuntulinux/ is replaced with a href tag so that its visible as link & open in new tab

Deploy preview ready!
Built with commit d297602d8ad03561675bf19a566101fc12073dfe
https://deploy-preview-668--docker-docs.netlify.com

Sent a new pull request


None.get(): undefined is incompatible with never

doesn't compile:
error TS2430: Interface 'None' incorrectly extends interface 'Option<never>'.
  Types of property 'get' are incompatible.
    Type '() => undefined' is not assignable to type '() => never'.
      Type 'undefined' is not assignable to type 'never'.

Weird I didn't see this. Which tsc version do you use?

tsc Version 2.3.2

Same version space-lift uses to compile its src and tests. The npm run build command sets 3 tsc flags:
--noImplicitAny
--strictNullChecks
--suppressImplicitAnyIndexErrors

With these flags, the compilation succeeds.
If we remove --strictNullChecks, then I get your error.

It works. Thank you! :smile:

I have the same issue, problem is I couldn't just turn on --strictNullChecks as we have a relatively big code base. Would be nice if the lib would be less restrictive on compiler options, how about:
export interface None extends Option<never> {
    type: 'none';
    get(): never;
}

?

Hummm, but None really does return undefined :(


Adjust docker client timeout

2016-04-12 09:11:31,786 - atomic_reactor.core - DEBUG - image_id = 'brew-pulp-docker01.internalqa.redhat.com:8888/rhel7:latest'
2016-04-12 09:11:32,456 - atomic_reactor.core - INFO - removing image 'rhel7:latest' from filesystem
2016-04-12 09:11:32,456 - atomic_reactor.core - DEBUG - image_id = 'rhel7:latest'
2016-04-12 09:11:33,137 - atomic_reactor.plugins.remove_built_image - WARNING - failed to remove image rhel7:latest (409: Conflict), ignoring

This failure happened because the docker daemon was legitimately taking longer than the default 60s timeout.
We should set the docker client timeout to something more sensible, eg 600s.

@maxamillion I think you've seen this too.

Oh, this isn't a timeout issue but something else. I think the 409 error means there is a container started from that image.
However, I have seen remove_built_image fail with a timeout.

@twaugh probably there's a container using rhel:7 image running on the host, I haven't seen that error with busybox

Not necessarily even running I think. I bet it comes from cancelling a build.

This is the timeout I meant:
2016-04-22 13:35:26,448 - atomic_reactor.plugin - DEBUG - running plugin 'remove_built_image'
2016-04-22 13:35:26,449 - atomic_reactor.plugin - INFO - running plugin instance with args: '{}'
2016-04-22 13:35:26,449 - atomic_reactor.core - INFO - removing image 'cafcfc72fd65eae4ae1088b8b6f713b317f3566fe18652cebba3a0dc821635b6' from filesystem
2016-04-22 13:35:26,449 - atomic_reactor.core - DEBUG - image_id = 'cafcfc72fd65eae4ae1088b8b6f713b317f3566fe18652cebba3a0dc821635b6'
2016-04-22 13:37:26,593 - atomic_reactor.plugin - DEBUG - Traceback (most recent call last):
  File "/usr/lib/python2.7/site-packages/atomic_reactor/plugin.py", line 203, in run
    plugin_response = plugin_instance.run()
  File "/usr/lib/python2.7/site-packages/atomic_reactor/plugins/exit_remove_built_image.py", line 38, in run
    self.remove_image(image, force=True)
  File "/usr/lib/python2.7/site-packages/atomic_reactor/plugins/exit_remove_built_image.py", line 58, in remove_image
    self.tasker.remove_image(image, force=force)
  File "/usr/lib/python2.7/site-packages/atomic_reactor/core.py", line 508, in remove_image
    self.d.remove_image(image_id, force=force, noprune=noprune)  # returns None
  File "/usr/lib/python2.7/site-packages/docker/utils/decorators.py", line 21, in wrapped
    return f(self, resource_id, *args, **kwargs)
  File "/usr/lib/python2.7/site-packages/docker/api/image.py", line 256, in remove_image
    res = self._delete(self._url("/images/{0}", image), params=params)
  File "/usr/lib/python2.7/site-packages/docker/utils/decorators.py", line 47, in inner
    return f(self, *args, **kwargs)
  File "/usr/lib/python2.7/site-packages/docker/client.py", line 120, in _delete
    return self.delete(url, **self._set_request_timeout(kwargs))
  File "/usr/lib/python2.7/site-packages/requests/sessions.py", line 536, in delete
    return self.request('DELETE', url, **kwargs)
  File "/usr/lib/python2.7/site-packages/requests/sessions.py", line 464, in request
    resp = self.send(prep, **send_kwargs)
  File "/usr/lib/python2.7/site-packages/requests/sessions.py", line 576, in send
    r = adapter.send(request, **kwargs)
  File "/usr/lib/python2.7/site-packages/requests/adapters.py", line 433, in send
    raise ReadTimeout(e, request=request)
ReadTimeout: UnixHTTPConnectionPool(host='localhost', port=None): Read timed out. (read timeout=120)

2016-04-22 13:37:26,593 - atomic_reactor.plugin - WARNING - plugin 'remove_built_image' raised an exception: ReadTimeout(ReadTimeoutError("UnixHTTPConnectionPool(host='localhost', port=None): Read timed out. (read timeout=120)",),)
2016-04-22 13:37:26,593 - atomic_reactor.plugin - INFO - error is not fatal, continuing...

This is more OPC than docker issue. When dockerd fails higher timeout wont' help