blob: ba741738fae862e42a0ea04ff3feb80513a682e9 [file] [log] [blame]
#include <torch/extension.h>
#include <ATen/Generator.h>
#include <ATen/Tensor.h>
#include <ATen/native/DistributionTemplates.h>
#include <ATen/native/cpu/DistributionTemplates.h>
#include <ATen/core/op_registration/op_registration.h>
#include <memory>
using namespace at;
static size_t instance_count = 0;
struct TestCPUGenerator : public c10::GeneratorImpl {
TestCPUGenerator(uint64_t value) : c10::GeneratorImpl{Device(DeviceType::CPU), DispatchKeySet(DispatchKey::CustomRNGKeyId)}, value_(value) {
++instance_count;
}
~TestCPUGenerator() {
--instance_count;
}
uint32_t random() { return static_cast<uint32_t>(value_); }
uint64_t random64() { return value_; }
void set_current_seed(uint64_t seed) override { throw std::runtime_error("not implemented"); }
uint64_t current_seed() const override { throw std::runtime_error("not implemented"); }
uint64_t seed() override { throw std::runtime_error("not implemented"); }
TestCPUGenerator* clone_impl() const override { throw std::runtime_error("not implemented"); }
static DeviceType device_type() { return DeviceType::CPU; }
uint64_t value_;
};
Tensor& random_(Tensor& self, c10::optional<Generator> generator) {
return at::native::templates::random_impl<native::templates::cpu::RandomKernel, TestCPUGenerator>(self, generator);
}
Tensor& random_from_to(Tensor& self, int64_t from, optional<int64_t> to, c10::optional<Generator> generator) {
return at::native::templates::random_from_to_impl<native::templates::cpu::RandomFromToKernel, TestCPUGenerator>(self, from, to, generator);
}
Tensor& random_to(Tensor& self, int64_t to, c10::optional<Generator> generator) {
return random_from_to(self, 0, to, generator);
}
Generator createTestCPUGenerator(uint64_t value) {
return at::make_generator<TestCPUGenerator>(value);
}
Generator identity(Generator g) {
return g;
}
size_t getInstanceCount() {
return instance_count;
}
static auto registry = torch::RegisterOperators()
.op(torch::RegisterOperators::options()
.schema("aten::random_.from(Tensor(a!) self, int from, int? to, *, Generator? generator=None) -> Tensor(a!)")
.impl_unboxedOnlyKernel<decltype(random_from_to), &random_from_to>(DispatchKey::CustomRNGKeyId))
.op(torch::RegisterOperators::options()
.schema("aten::random_.to(Tensor(a!) self, int to, *, Generator? generator=None) -> Tensor(a!)")
.impl_unboxedOnlyKernel<decltype(random_to), &random_to>(DispatchKey::CustomRNGKeyId))
.op(torch::RegisterOperators::options()
.schema("aten::random_(Tensor(a!) self, *, Generator? generator=None) -> Tensor(a!)")
.impl_unboxedOnlyKernel<decltype(random_), &random_>(DispatchKey::CustomRNGKeyId));
PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.def("createTestCPUGenerator", &createTestCPUGenerator);
m.def("getInstanceCount", &getInstanceCount);
m.def("identity", &identity);
}