blob: 57e042b36ab8ef69587ba4b8ad8bc15f07c1603a [file] [log] [blame]
#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);
}