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#include <utility>
#include "pybind11/pybind11.h"
#include "pybind11/cast.h"
#include "pybind11/stl.h"
#include "pybind11/complex.h"
#include "pybind11/functional.h"
#include "cudnn_frontend.h"
namespace py = pybind11;
using namespace pybind11::literals;
namespace cudnn_frontend {
namespace python_bindings {
void
throw_if(bool const cond, cudnn_frontend::error_code_t const error_code, std::string const& error_msg);
class HandleManagement {
public:
static std::intptr_t
create_handle() {
cudnnHandle_t handle;
auto status = detail::create_handle(&handle);
throw_if(
status != CUDNN_STATUS_SUCCESS, cudnn_frontend::error_code_t::HANDLE_ERROR, "cudnnHandle Create failed");
return reinterpret_cast<std::intptr_t>(handle);
}
static void
destroy_handle(std::intptr_t handle) {
auto status = detail::destroy_handle((cudnnHandle_t)handle);
throw_if(
status != CUDNN_STATUS_SUCCESS, cudnn_frontend::error_code_t::HANDLE_ERROR, "cudnnHandle Destroy failed");
}
static void
set_stream(std::intptr_t handle, std::intptr_t stream) {
auto status = detail::set_stream((cudnnHandle_t)handle, (cudaStream_t)stream);
throw_if(status != CUDNN_STATUS_SUCCESS, cudnn_frontend::error_code_t::HANDLE_ERROR, "cudnnSetStream failed");
}
static std::intptr_t
get_stream(std::intptr_t handle) {
cudaStream_t streamId = nullptr;
auto status = detail::get_stream((cudnnHandle_t)handle, &streamId);
throw_if(status != CUDNN_STATUS_SUCCESS, cudnn_frontend::error_code_t::HANDLE_ERROR, "cudnnGetStream failed");
return reinterpret_cast<std::intptr_t>(streamId);
}
};
std::shared_ptr<cudnn_frontend::KernelCache>
create_kernel_cache_helper() {
auto kernel_cache = std::make_shared<cudnn_frontend::KernelCache>();
throw_if(kernel_cache == nullptr, cudnn_frontend::error_code_t::INVALID_VALUE, "kernel cache creation failed");
return kernel_cache;
}
static std::string
get_last_error_string() {
return detail::get_last_error_string_();
}
void
init_properties(py::module_& m) {
py::enum_<cudnn_frontend::DataType_t>(m, "data_type")
.value("FLOAT", cudnn_frontend::DataType_t::FLOAT)
.value("DOUBLE", cudnn_frontend::DataType_t::DOUBLE)
.value("HALF", cudnn_frontend::DataType_t::HALF)
.value("INT8", cudnn_frontend::DataType_t::INT8)
.value("INT32", cudnn_frontend::DataType_t::INT32)
.value("INT8x4", cudnn_frontend::DataType_t::INT8x4)
.value("UINT8", cudnn_frontend::DataType_t::UINT8)
.value("UINT8x4", cudnn_frontend::DataType_t::UINT8x4)
.value("INT8x32", cudnn_frontend::DataType_t::INT8x32)
.value("BFLOAT16", cudnn_frontend::DataType_t::BFLOAT16)
.value("INT64", cudnn_frontend::DataType_t::INT64)
.value("BOOLEAN", cudnn_frontend::DataType_t::BOOLEAN)
.value("FP8_E4M3", cudnn_frontend::DataType_t::FP8_E4M3)
.value("FP8_E5M2", cudnn_frontend::DataType_t::FP8_E5M2)
.value("FAST_FLOAT_FOR_FP8", cudnn_frontend::DataType_t::FAST_FLOAT_FOR_FP8)
.value("NOT_SET", cudnn_frontend::DataType_t::NOT_SET);
py::class_<cudnn_frontend::graph::Tensor_attributes, std::shared_ptr<cudnn_frontend::graph::Tensor_attributes>>(
m, "tensor")
.def(py::init<>())
.def("get_name", &cudnn_frontend::graph::Tensor_attributes::get_name)
.def("set_name", &cudnn_frontend::graph::Tensor_attributes::set_name)
.def("get_data_type", &cudnn_frontend::graph::Tensor_attributes::get_data_type)
.def("_set_data_type", &cudnn_frontend::graph::Tensor_attributes::set_data_type)
.def("get_dim", &cudnn_frontend::graph::Tensor_attributes::get_dim)
.def("set_dim", &cudnn_frontend::graph::Tensor_attributes::set_dim)
.def("get_stride", &cudnn_frontend::graph::Tensor_attributes::get_stride)
.def("set_stride", &cudnn_frontend::graph::Tensor_attributes::set_stride)
.def("get_is_virtual", &cudnn_frontend::graph::Tensor_attributes::get_is_virtual)
.def("set_is_virtual", &cudnn_frontend::graph::Tensor_attributes::set_is_virtual)
.def(
"set_output",
[](cudnn_frontend::graph::Tensor_attributes& self,
bool const is_output) -> cudnn_frontend::graph::Tensor_attributes& {
self.set_is_virtual(!is_output);
return self;
},
py::return_value_policy::reference) // NOTICE THATS ITS JUST ANOTHER NAME FOR SET_IS_VIRTUAL
.def("get_is_pass_by_value", &cudnn_frontend::graph::Tensor_attributes::get_is_pass_by_value)
.def("set_is_pass_by_value", &cudnn_frontend::graph::Tensor_attributes::set_is_pass_by_value)
.def("get_uid", &cudnn_frontend::graph::Tensor_attributes::get_uid)
.def("set_uid", &cudnn_frontend::graph::Tensor_attributes::set_uid)
.def("set_ragged_offset", &cudnn_frontend::graph::Tensor_attributes::set_ragged_offset)
.def("__repr__", [](cudnn_frontend::graph::Tensor_attributes const& props) {
std::ostringstream out;
out << json{props};
return out.str();
});
m.def("get_last_error_string", &get_last_error_string);
py::class_<cudnn_frontend::KernelCache, std::shared_ptr<cudnn_frontend::KernelCache>>(m, "kernel_cache");
m.def("create_kernel_cache", &create_kernel_cache_helper);
m.def("create_handle", &HandleManagement::create_handle);
m.def("destroy_handle", &HandleManagement::destroy_handle);
m.def("get_stream", &HandleManagement::get_stream);
m.def("set_stream", &HandleManagement::set_stream, py::arg("handle"), py::arg("stream"));
py::enum_<cudnn_frontend::NormFwdPhase_t>(m, "norm_forward_phase")
.value("INFERENCE", cudnn_frontend::NormFwdPhase_t::INFERENCE)
.value("TRAINING", cudnn_frontend::NormFwdPhase_t::TRAINING)
.value("NOT_SET", cudnn_frontend::NormFwdPhase_t::NOT_SET);
py::enum_<cudnn_frontend::HeurMode_t>(m, "heur_mode")
.value("A", cudnn_frontend::HeurMode_t::A)
.value("B", cudnn_frontend::HeurMode_t::B)
.value("FALLBACK", cudnn_frontend::HeurMode_t::FALLBACK);
py::enum_<cudnn_frontend::ConvolutionMode_t>(m, "convolution_mode")
.value("CONVOLUTION", cudnn_frontend::ConvolutionMode_t::CONVOLUTION)
.value("CROSS_CORRELATION", cudnn_frontend::ConvolutionMode_t::CROSS_CORRELATION);
py::enum_<cudnn_frontend::ReductionMode_t>(m, "reduction_mode")
.value("ADD", cudnn_frontend::ReductionMode_t::ADD)
.value("MUL", cudnn_frontend::ReductionMode_t::MUL)
.value("MIN", cudnn_frontend::ReductionMode_t::MIN)
.value("MAX", cudnn_frontend::ReductionMode_t::MAX)
.value("AMAX", cudnn_frontend::ReductionMode_t::AMAX)
.value("AVG", cudnn_frontend::ReductionMode_t::AVG)
.value("NORM1", cudnn_frontend::ReductionMode_t::NORM1)
.value("NORM2", cudnn_frontend::ReductionMode_t::NORM2)
.value("MUL_NO_ZEROS", cudnn_frontend::ReductionMode_t::MUL_NO_ZEROS)
.value("NOT_SET", cudnn_frontend::ReductionMode_t::NOT_SET);
py::enum_<cudnn_frontend::BuildPlanPolicy_t>(m, "build_plan_policy")
.value("HEURISTICS_CHOICE", cudnn_frontend::BuildPlanPolicy_t::HEURISTICS_CHOICE)
.value("ALL", cudnn_frontend::BuildPlanPolicy_t::ALL);
py::enum_<cudnn_frontend::NumericalNote_t>(m, "numerical_note")
.value("TENSOR_CORE", cudnn_frontend::NumericalNote_t::TENSOR_CORE)
.value("DOWN_CONVERT_INPUTS", cudnn_frontend::NumericalNote_t::DOWN_CONVERT_INPUTS)
.value("REDUCED_PRECISION_REDUCTION", cudnn_frontend::NumericalNote_t::REDUCED_PRECISION_REDUCTION)
.value("FFT", cudnn_frontend::NumericalNote_t::FFT)
.value("NONDETERMINISTIC", cudnn_frontend::NumericalNote_t::NONDETERMINISTIC)
.value("WINOGRAD", cudnn_frontend::NumericalNote_t::WINOGRAD)
.value("WINOGRAD_TILE_4x4", cudnn_frontend::NumericalNote_t::WINOGRAD_TILE_4x4)
.value("WINOGRAD_TILE_6x6", cudnn_frontend::NumericalNote_t::WINOGRAD_TILE_6x6)
.value("WINOGRAD_TILE_13x13", cudnn_frontend::NumericalNote_t::WINOGRAD_TILE_13x13)
.value("STRICT_NAN_PROP", cudnn_frontend::NumericalNote_t::STRICT_NAN_PROP);
py::enum_<cudnn_frontend::BehaviorNote_t>(m, "behavior_note")
.value("RUNTIME_COMPILATION", cudnn_frontend::BehaviorNote_t::RUNTIME_COMPILATION)
.value("REQUIRES_FILTER_INT8x32_REORDER", cudnn_frontend::BehaviorNote_t::REQUIRES_FILTER_INT8x32_REORDER)
.value("REQUIRES_BIAS_INT8x32_REORDER", cudnn_frontend::BehaviorNote_t::REQUIRES_BIAS_INT8x32_REORDER)
.value("SUPPORTS_CUDA_GRAPH_NATIVE_API", cudnn_frontend::BehaviorNote_t::SUPPORTS_CUDA_GRAPH_NATIVE_API);
}
} // namespace python_bindings
} // namespace cudnn_frontend
// namespace pybind11 {
// namespace detail {
// template <> struct type_caster<std::shared_ptr<cudnn_frontend::KernelCache>> {
// public:
// PYBIND11_TYPE_CASTER(std::shared_ptr<cudnn_frontend::KernelCache>, _("KernelCachePtr"));
// bool load(handle , bool) {
// return false; // Prevent Python -> C++ conversion
// }
// static handle cast(std::shared_ptr<cudnn_frontend::KernelCache> src, return_value_policy, handle) {
// if (!src) return none().release();
// return capsule(new std::shared_ptr<cudnn_frontend::KernelCache>(std::move(src)),
// [](void *ptr) { delete static_cast<std::shared_ptr<cudnn_frontend::KernelCache>*>(ptr);
// }).release();
// }
// };
// }} // namespace pybind11::detail
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