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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 " + detail::get_last_error_string_());
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 " + detail::get_last_error_string_());
}
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 " + detail::get_last_error_string_());
}
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 " + detail::get_last_error_string_());
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 " + detail::get_last_error_string_());
return kernel_cache;
}
std::string
kernel_cache_to_json_helper(std::shared_ptr<cudnn_frontend::KernelCache> const& kernel_cache) {
std::string str_json;
auto err = kernel_cache->to_json(str_json);
throw_if(err.is_bad(), err.code, err.get_message());
return str_json;
}
void
kernel_cache_from_json_helper(std::shared_ptr<cudnn_frontend::KernelCache> kernel_cache, std::string const& str_json) {
auto err = kernel_cache->from_json(str_json);
throw_if(err.is_bad(), err.code, err.get_message());
}
std::shared_ptr<cudnn_frontend::DeviceProperties>
create_device_properties_helper(int32_t device_id) {
auto device_properties = std::make_shared<cudnn_frontend::DeviceProperties>();
throw_if(device_properties == nullptr,
cudnn_frontend::error_code_t::INVALID_VALUE,
"device properties creation failed " + detail::get_last_error_string_());
if (device_id >= 0) {
auto err = device_properties->set_device_id(device_id).build();
throw_if(!err.is_good(), err.code, err.get_message());
}
return device_properties;
}
std::shared_ptr<cudnn_frontend::DeviceProperties>
create_device_properties_helper(std::string const& json_str) {
auto device_properties = std::make_shared<cudnn_frontend::DeviceProperties>();
throw_if(device_properties == nullptr,
cudnn_frontend::error_code_t::INVALID_VALUE,
"device properties creation failed " + detail::get_last_error_string_());
std::vector<uint8_t> serialization_buf(json_str.begin(), json_str.end());
auto err = device_properties->deserialize(serialization_buf);
throw_if(err.is_bad(), err.code, err.get_message());
return device_properties;
}
std::string
serialize_device_properties_helper(std::shared_ptr<cudnn_frontend::DeviceProperties> const& device_properties) {
std::vector<uint8_t> serialization_buf;
auto err = device_properties->serialize(serialization_buf);
throw_if(err.is_bad(), err.code, err.get_message());
return std::string(serialization_buf.begin(), serialization_buf.end());
}
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("FP8_E8M0", cudnn_frontend::DataType_t::FP8_E8M0)
.value("FP4_E2M1", cudnn_frontend::DataType_t::FP4_E2M1)
.value("INT4", cudnn_frontend::DataType_t::INT4)
.value("NOT_SET", cudnn_frontend::DataType_t::NOT_SET);
py::enum_<cudnn_frontend::TensorReordering_t>(m, "tensor_reordering")
.value("NONE", cudnn_frontend::TensorReordering_t::NONE)
.value("INT8x32", cudnn_frontend::TensorReordering_t::INT8x32)
.value("F16x16", cudnn_frontend::TensorReordering_t::F16x16)
.value("F8_128x4", cudnn_frontend::TensorReordering_t::F8_128x4);
py::enum_<cudnn_frontend::graph::ScalarType>(m, "scalar_type")
.value("RUNTIME_PARAM", cudnn_frontend::graph::ScalarType::RUNTIME_PARAM)
.value("COMPILE_TIME_CONST", cudnn_frontend::graph::ScalarType::COMPILE_TIME_CONST);
py::enum_<cudnn_frontend::ReshapeMode_t>(m, "reshape_mode")
.value("VIEW_ONLY", cudnn_frontend::ReshapeMode_t::VIEW_ONLY)
.value("LOGICAL", cudnn_frontend::ReshapeMode_t::LOGICAL);
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_has_compile_time_constant", &cudnn_frontend::graph::Tensor_attributes::get_has_compile_time_constant)
.def("get_uid", &cudnn_frontend::graph::Tensor_attributes::get_uid)
.def("set_uid", &cudnn_frontend::graph::Tensor_attributes::set_uid)
.def("get_reordering_type", &cudnn_frontend::graph::Tensor_attributes::get_reordering_type)
.def("set_reordering_type",
&cudnn_frontend::graph::Tensor_attributes::set_reordering_type,
py::return_value_policy::reference)
.def("get_alignment", &cudnn_frontend::graph::Tensor_attributes::get_alignment)
.def("set_alignment",
&cudnn_frontend::graph::Tensor_attributes::set_alignment,
py::return_value_policy::reference)
.def("get_vector_count", &cudnn_frontend::graph::Tensor_attributes::get_vector_count)
.def("get_vector_dimension", &cudnn_frontend::graph::Tensor_attributes::get_vector_dimension)
.def("set_vector_count_and_dimension",
&cudnn_frontend::graph::Tensor_attributes::set_vector_count_and_dimension,
py::return_value_policy::reference)
.def("set_ragged_offset", &cudnn_frontend::graph::Tensor_attributes::set_ragged_offset)
.def("get_ragged_offset_multiplier", &cudnn_frontend::graph::Tensor_attributes::get_ragged_offset_multiplier)
.def("set_ragged_offset_multiplier",
&cudnn_frontend::graph::Tensor_attributes::set_ragged_offset_multiplier,
py::return_value_policy::reference)
.def("__repr__", [](cudnn_frontend::graph::Tensor_attributes const& props) {
std::ostringstream out;
out << json{props};
return out.str();
});
py::enum_<cudnn_frontend::KnobType_t>(m, "knob_type")
.value("NOT_SET", cudnn_frontend::KnobType_t::NOT_SET)
.value("SWIZZLE", cudnn_frontend::KnobType_t::SWIZZLE)
.value("TILE_SIZE", cudnn_frontend::KnobType_t::TILE_SIZE)
.value("EDGE", cudnn_frontend::KnobType_t::EDGE)
.value("MULTIPLY", cudnn_frontend::KnobType_t::MULTIPLY)
.value("SPLIT_K_BUF", cudnn_frontend::KnobType_t::SPLIT_K_BUF)
.value("TILEK", cudnn_frontend::KnobType_t::TILEK)
.value("STAGES", cudnn_frontend::KnobType_t::STAGES)
.value("REDUCTION_MODE", cudnn_frontend::KnobType_t::REDUCTION_MODE)
.value("SPLIT_K_SLC", cudnn_frontend::KnobType_t::SPLIT_K_SLC)
.value("IDX_MODE", cudnn_frontend::KnobType_t::IDX_MODE)
.value("SPECFILT", cudnn_frontend::KnobType_t::SPECFILT)
.value("KERNEL_CFG", cudnn_frontend::KnobType_t::KERNEL_CFG)
.value("WORKSPACE", cudnn_frontend::KnobType_t::WORKSPACE)
.value("TILE_CGA_M", cudnn_frontend::KnobType_t::TILE_CGA_M)
.value("TILE_CGA_N", cudnn_frontend::KnobType_t::TILE_CGA_N)
.value("BLOCK_SIZE", cudnn_frontend::KnobType_t::BLOCK_SIZE)
.value("OCCUPANCY", cudnn_frontend::KnobType_t::OCCUPANCY)
.value("ARRAY_SIZE_PER_THREAD", cudnn_frontend::KnobType_t::ARRAY_SIZE_PER_THREAD)
.value("SPLIT_COLS", cudnn_frontend::KnobType_t::SPLIT_COLS)
.value("TILE_ROWS", cudnn_frontend::KnobType_t::TILE_ROWS)
.value("TILE_COLS", cudnn_frontend::KnobType_t::TILE_COLS)
.value("LOAD_SIZE", cudnn_frontend::KnobType_t::LOAD_SIZE)
.value("CTA_COUNT", cudnn_frontend::KnobType_t::CTA_COUNT)
.value("STREAM_K", cudnn_frontend::KnobType_t::STREAM_K)
.value("SPLIT_P_SLC", cudnn_frontend::KnobType_t::SPLIT_P_SLC)
.value("TILE_M", cudnn_frontend::KnobType_t::TILE_M)
.value("TILE_N", cudnn_frontend::KnobType_t::TILE_N)
.value("WARP_SPEC_CFG", cudnn_frontend::KnobType_t::WARP_SPEC_CFG)
.value("SWAP_AB", cudnn_frontend::KnobType_t::SWAP_AB)
.value("INPUT_TMA_ENABLE", cudnn_frontend::KnobType_t::INPUT_TMA_ENABLE)
.value("OUTPUT_TMA_ENABLE", cudnn_frontend::KnobType_t::OUTPUT_TMA_ENABLE);
py::class_<cudnn_frontend::Knob, std::shared_ptr<cudnn_frontend::Knob>>(m, "knob")
.def(py::init<cudnn_frontend::KnobType_t, int64_t, int64_t, int64_t>(),
py::arg_v("knob_type", cudnn_frontend::KnobType_t::NOT_SET),
py::arg_v("max_value", py::none()),
py::arg_v("min_value", py::none()),
py::arg_v("stride", py::none()))
.def_readonly("type", &cudnn_frontend::Knob::type)
.def_readonly("max_value", &cudnn_frontend::Knob::maxValue)
.def_readonly("min_value", &cudnn_frontend::Knob::minValue)
.def_readonly("stride", &cudnn_frontend::Knob::stride)
.def("__repr__", [](cudnn_frontend::Knob const& knob) {
std::stringstream ss;
json j;
j["knob_type"] = knob.type;
j["max_value"] = knob.maxValue;
j["min_value"] = knob.minValue;
j["stride"] = knob.stride;
ss << j.dump();
return ss.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")
.def("serialize", &kernel_cache_to_json_helper)
.def("deserialize", &kernel_cache_from_json_helper);
m.def("create_kernel_cache", &create_kernel_cache_helper);
py::class_<cudnn_frontend::DeviceProperties, std::shared_ptr<cudnn_frontend::DeviceProperties>>(m,
"device_properties")
.def("serialize", &serialize_device_properties_helper);
m.def(
"create_device_properties",
static_cast<std::shared_ptr<cudnn_frontend::DeviceProperties> (*)(int32_t)>(&create_device_properties_helper));
m.def("create_device_properties",
static_cast<std::shared_ptr<cudnn_frontend::DeviceProperties> (*)(std::string const&)>(
&create_device_properties_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)
.value("OPENSOURCE", cudnn_frontend::HeurMode_t::OPENSOURCE);
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)
.value("CUBLASLT_DEPENDENCY", cudnn_frontend::BehaviorNote_t::CUBLASLT_DEPENDENCY);
py::enum_<cudnn_frontend::DiagonalAlignment_t>(m, "diagonal_alignment")
.value("TOP_LEFT", cudnn_frontend::DiagonalAlignment_t::TOP_LEFT)
.value("BOTTOM_RIGHT", cudnn_frontend::DiagonalAlignment_t::BOTTOM_RIGHT);
py::enum_<cudnn_frontend::AttentionImplementation_t>(m, "attention_implementation")
.value("AUTO", cudnn_frontend::AttentionImplementation_t::AUTO)
.value("COMPOSITE", cudnn_frontend::AttentionImplementation_t::COMPOSITE)
.value("UNIFIED", cudnn_frontend::AttentionImplementation_t::UNIFIED);
py::enum_<cudnn_frontend::MoeGroupedMatmulMode_t>(m, "moe_grouped_matmul_mode")
.value("NONE", cudnn_frontend::MoeGroupedMatmulMode_t::NONE)
.value("GATHER", cudnn_frontend::MoeGroupedMatmulMode_t::GATHER)
.value("SCATTER", cudnn_frontend::MoeGroupedMatmulMode_t::SCATTER);
}
} // 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