| #include <torch/extension.h> |
| #include <ATen/native/mps/OperationUtils.h> |
| |
| // this sample custom kernel is taken from: |
| // https://developer.apple.com/documentation/metal/performing_calculations_on_a_gpu |
| static const char* CUSTOM_KERNEL = R"MPS_ADD_ARRAYS( |
| #include <metal_stdlib> |
| using namespace metal; |
| kernel void add_arrays(device const float* inA, |
| device const float* inB, |
| device float* result, |
| uint index [[thread_position_in_grid]]) |
| { |
| result[index] = inA[index] + inB[index]; |
| } |
| )MPS_ADD_ARRAYS"; |
| |
| at::Tensor get_cpu_add_output(at::Tensor & cpu_input1, at::Tensor & cpu_input2) { |
| return cpu_input1 + cpu_input2; |
| } |
| |
| at::Tensor get_mps_add_output(at::Tensor & mps_input1, at::Tensor & mps_input2) { |
| |
| // smoke tests |
| TORCH_CHECK(mps_input1.is_mps()); |
| TORCH_CHECK(mps_input2.is_mps()); |
| TORCH_CHECK(mps_input1.sizes() == mps_input2.sizes()); |
| |
| using namespace at::native::mps; |
| at::Tensor mps_output = at::empty_like(mps_input1); |
| |
| @autoreleasepool { |
| id<MTLDevice> device = MPSDevice::getInstance()->device(); |
| NSError *error = nil; |
| size_t numThreads = mps_output.numel(); |
| id<MTLLibrary> customKernelLibrary = [device newLibraryWithSource: [NSString stringWithUTF8String:CUSTOM_KERNEL] |
| options: nil |
| error: &error]; |
| TORCH_CHECK(customKernelLibrary, "Failed to to create custom kernel library, error: ", error.localizedDescription.UTF8String); |
| |
| id<MTLFunction> customFunction = [customKernelLibrary newFunctionWithName: @"add_arrays"]; |
| TORCH_CHECK(customFunction, "Failed to create function state object for the kernel"); |
| |
| id<MTLComputePipelineState> kernelPSO = [device newComputePipelineStateWithFunction: customFunction error: &error]; |
| TORCH_CHECK(kernelPSO, error.localizedDescription.UTF8String); |
| |
| MPSStream* mpsStream = getCurrentMPSStream(); |
| |
| dispatch_sync(mpsStream->queue(), ^() { |
| // Start a compute pass. |
| id<MTLComputeCommandEncoder> computeEncoder = mpsStream->commandEncoder(); |
| TORCH_CHECK(computeEncoder, "Failed to create compute command encoder"); |
| |
| // Encode the pipeline state object and its parameters. |
| [computeEncoder setComputePipelineState: kernelPSO]; |
| [computeEncoder setBuffer: getMTLBufferStorage(mps_input1) offset:0 atIndex:0]; |
| [computeEncoder setBuffer: getMTLBufferStorage(mps_input2) offset:0 atIndex:1]; |
| [computeEncoder setBuffer: getMTLBufferStorage(mps_output) offset:0 atIndex:2]; |
| MTLSize gridSize = MTLSizeMake(numThreads, 1, 1); |
| |
| // Calculate a thread group size. |
| NSUInteger threadsPerGroupSize = std::min(kernelPSO.maxTotalThreadsPerThreadgroup, numThreads); |
| MTLSize threadGroupSize = MTLSizeMake(threadsPerGroupSize, 1, 1); |
| |
| // Encode the compute command. |
| [computeEncoder dispatchThreads: gridSize threadsPerThreadgroup: threadGroupSize]; |
| |
| }); |
| } |
| return mps_output; |
| } |
| |
| PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { |
| m.def("get_cpu_add_output", &get_cpu_add_output); |
| m.def("get_mps_add_output", &get_mps_add_output); |
| } |