I want to use the com.apple.vm.networking entitlement which has a note: This entitlement is restricted to developers of virtualization software. To request this entitlement, contact your Apple representative. https://developer.apple.com/support/technical/ says: « Request entitlements using entitlement forms and ask for status updates in the resulting email thread. » but I haven't been able to find these "entitlement forms". Does anyone know what the right process is to request an entitlement?

I created a macOS 14 VM using https://github.com/s-u/macosvm which uses the Virtualization Framework. I want to check if I can use paravirtualized graphics for tensorflow workloads. I followed the steps from https://developer.apple.com/metal/tensorflow-plugin/ but when I run the script from step 4. Verify, I get a segmentation fault (see below). Did anyone try to get this kind of GPU compute in a VM and succeed? /Users/teuf/venv-metal/lib/python3.9/site-packages/urllib3/__init__.py:34: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020 warnings.warn( 2023-11-20 07:41:11.723578: I metal_plugin/src/device/metal_device.cc:1154] Metal device set to: Apple Paravirtual device 2023-11-20 07:41:11.723620: I metal_plugin/src/device/metal_device.cc:296] systemMemory: 10.00 GB 2023-11-20 07:41:11.723626: I metal_plugin/src/device/metal_device.cc:313] maxCacheSize: 0.50 GB 2023-11-20 07:41:11.723700: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support. 2023-11-20 07:41:11.723968: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>) zsh: segmentation fault python3 ./tensorflow-test.py Thread 0 Crashed:: Dispatch queue: metal gpu stream 0 MPSCore 0x1999598f8 MPSDevice::GetMPSLibrary_DoNotUse(MPSLibraryInfo const*) + 92 1 MPSCore 0x19995c544 0x199927000 + 218436 2 MPSCore 0x19995c908 0x199927000 + 219400 3 MetalPerformanceShadersGraph 0x1fb696a58 0x1fb583000 + 1129048 4 MetalPerformanceShadersGraph 0x1fb6f0cc8 0x1fb583000 + 1498312 5 MetalPerformanceShadersGraph 0x1fb6ef2dc 0x1fb583000 + 1491676 6 MetalPerformanceShadersGraph 0x1fb717ea0 0x1fb583000 + 1658528 7 MetalPerformanceShadersGraph 0x1fb717ce4 0x1fb583000 + 1658084 8 MetalPerformanceShadersGraph 0x1fb6edaac 0x1fb583000 + 1485484 9 MetalPerformanceShadersGraph 0x1fb7a85e0 0x1fb583000 + 2250208 10 MetalPerformanceShadersGraph 0x1fb7a79f0 0x1fb583000 + 2247152 11 MetalPerformanceShadersGraph 0x1fb6602b4 0x1fb583000 + 905908 12 MetalPerformanceShadersGraph 0x1fb65f7b0 0x1fb583000 + 903088 13 libmetal_plugin.dylib 0x1156dfdcc invocation function for block in metal_plugin::runMPSGraph(MetalStream*, MPSGraph*, NSDictionary*, NSDictionary*) + 164 14 libdispatch.dylib 0x18e79b910 _dispatch_client_callout + 20 15 libdispatch.dylib 0x18e7aacc4 _dispatch_lane_barrier_sync_invoke_and_complete + 56 16 libmetal_plugin.dylib 0x1156dfd14 metal_plugin::runMPSGraph(MetalStream*, MPSGraph*, NSDictionary*, NSDictionary*) + 108 17 libmetal_plugin.dylib 0x115606634 metal_plugin::MPSStatelessRandomUniformOp<float>::ProduceOutput(metal_plugin::OpKernelContext*, metal_plugin::Tensor*) + 876 18 libmetal_plugin.dylib 0x115607620 metal_plugin::MPSStatelessRandomOpBase::Compute(metal_plugin::OpKernelContext*) + 620 19 libmetal_plugin.dylib 0x1156061f8 void metal_plugin::ComputeOpKernel<metal_plugin::MPSStatelessRandomUniformOp<float>>(void*, TF_OpKernelContext*) + 44 20 libtensorflow_framework.2.dylib 0x10b807354 tensorflow::PluggableDevice::Compute(tensorflow::OpKernel*, tensorflow::OpKernelContext*) + 148 21 libtensorflow_framework.2.dylib 0x10b7413e0 tensorflow::(anonymous namespace)::SingleThreadedExecutorImpl::Run(tensorflow::Executor::Args const&) + 2100 22 libtensorflow_framework.2.dylib 0x10b70b820 tensorflow::FunctionLibraryRuntimeImpl::RunSync(tensorflow::FunctionLibraryRuntime::Options, unsigned long long, absl::lts_20230125::Span<tensorflow::Tensor const>, std::__1::vector<tensorflow::Tensor, std::__1::allocator<tensorflow::Tensor>>*) + 420 23 libtensorflow_framework.2.dylib 0x10b715668 tensorflow::ProcessFunctionLibraryRuntime::RunMultiDeviceSync(tensorflow::FunctionLibraryRuntime::Options const&, unsigned long long, std::__1::vector<std::__1::variant<tensorflow::Tensor, tensorflow::TensorShape>, std::__1::allocator<std::__1::variant<tensorflow::Tensor, tensorflow::TensorShape>>>*, std::__1::function<absl::lts_20230125::Status (tensorflow::ProcessFunctionLibraryRuntime::ComponentFunctionData const&, tensorflow::ProcessFunctionLibraryRuntime::InternalArgs*)>) const + 1336 24 libtensorflow_framework.2.dylib 0x10b71a8a4 tensorflow::ProcessFunctionLibraryRuntime::RunSync(tensorflow::FunctionLibraryRuntime::Options const&, unsigned long long, absl::lts_20230125::Span<tensorflow::Tensor const>, std::__1::vector<tensorflow::Tensor, std::__1::allocator<tensorflow::Tensor>>*) const + 848 25 libtensorflow_cc.2.dylib 0x2801b5008 tensorflow::KernelAndDeviceFunc::Run(tensorflow::ScopedStepContainer*, tensorflow::EagerKernelArgs const&, std::__1::vector<std::__1::variant<tensorflow::Tensor, tensorflow::TensorShape>, std::__1::allocator<std::__1::variant<tensorflow::Tensor, tensorflow::TensorShape>>>*, tsl::CancellationManager*, std::__1::optional<tensorflow::EagerFunctionParams> const&, std::__1::optional<tensorflow::ManagedStackTrace> const&, tsl::CoordinationServiceAgent*) + 572 26 libtensorflow_cc.2.dylib 0x28016613c tensorflow::EagerKernelExecute(tensorflow::EagerContext*, absl::lts_20230125::InlinedVector<tensorflow::TensorHandle*, 4ul, std::__1::allocator<tensorflow::TensorHandle*>> const&, std::__1::optional<tensorflow::EagerFunctionParams> const&, tsl::core::RefCountPtr<tensorflow::KernelAndDevice> const&, tensorflow::GraphCollector*, tsl::CancellationManager*, absl::lts_20230125::Span<tensorflow::TensorHandle*>, std::__1::optional<tensorflow::ManagedStackTrace> const&) + 452 27 libtensorflow_cc.2.dylib 0x2801708ec tensorflow::ExecuteNode::Run() + 396 28 libtensorflow_cc.2.dylib 0x2801b0118 tensorflow::EagerExecutor::SyncExecute(tensorflow::EagerNode*) + 244 29 libtensorflow_cc.2.dylib 0x280165ac8 tensorflow::(anonymous namespace)::EagerLocalExecute(tensorflow::EagerOperation*, tensorflow::TensorHandle**, int*) + 2580 30 libtensorflow_cc.2.dylib 0x2801637a8 tensorflow::DoEagerExecute(tensorflow::EagerOperation*, tensorflow::TensorHandle**, int*) + 416 31 libtensorflow_cc.2.dylib 0x2801631e8 tensorflow::EagerOperation::Execute(absl::lts_20230125::Span<tensorflow::AbstractTensorHandle*>, int*) + 132