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//===- ExecutionEngineModule.cpp - Python module for execution engine -----===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#include "mlir-c/ExecutionEngine.h"
#include "mlir/Bindings/Python/IRCore.h"
#include "mlir/Bindings/Python/Nanobind.h"
#include "mlir/Bindings/Python/NanobindAdaptors.h"
namespace nb = nanobind;
namespace mlir {
namespace python {
namespace MLIR_BINDINGS_PYTHON_DOMAIN {
namespace execution_engine {
/// Owning Wrapper around an ExecutionEngine.
class PyExecutionEngine {
public:
PyExecutionEngine(MlirExecutionEngine executionEngine)
: executionEngine(executionEngine) {}
PyExecutionEngine(PyExecutionEngine &&other) noexcept
: executionEngine(other.executionEngine) {
other.executionEngine.ptr = nullptr;
}
~PyExecutionEngine() {
if (!mlirExecutionEngineIsNull(executionEngine))
mlirExecutionEngineDestroy(executionEngine);
}
MlirExecutionEngine get() { return executionEngine; }
void release() {
executionEngine.ptr = nullptr;
referencedObjects.clear();
}
nb::object getCapsule() {
return nb::steal<nb::object>(mlirPythonExecutionEngineToCapsule(get()));
}
// Add an object to the list of referenced objects whose lifetime must exceed
// those of the ExecutionEngine.
void addReferencedObject(const nb::object &obj) {
referencedObjects.push_back(obj);
}
static nb::object createFromCapsule(const nb::object &capsule) {
MlirExecutionEngine rawPm =
mlirPythonCapsuleToExecutionEngine(capsule.ptr());
if (mlirExecutionEngineIsNull(rawPm))
throw nb::python_error();
return nb::cast(PyExecutionEngine(rawPm), nb::rv_policy::move);
}
private:
MlirExecutionEngine executionEngine;
// We support Python ctypes closures as callbacks. Keep a list of the objects
// so that they don't get garbage collected. (The ExecutionEngine itself
// just holds raw pointers with no lifetime semantics).
std::vector<nb::object> referencedObjects;
};
} // namespace execution_engine
} // namespace MLIR_BINDINGS_PYTHON_DOMAIN
} // namespace python
} // namespace mlir
/// Create the `mlir.execution_engine` module here.
NB_MODULE(_mlirExecutionEngine, m) {
m.doc() = "MLIR Execution Engine";
using namespace mlir::python::MLIR_BINDINGS_PYTHON_DOMAIN;
using namespace execution_engine;
//----------------------------------------------------------------------------
// Mapping of the top-level PassManager
//----------------------------------------------------------------------------
nb::class_<PyExecutionEngine>(m, "ExecutionEngine")
.def(
"__init__",
[](PyExecutionEngine &self, PyModule &module, int optLevel,
const std::vector<std::string> &sharedLibPaths,
bool enableObjectDump, bool enablePIC) {
llvm::SmallVector<MlirStringRef, 4> libPaths;
for (const std::string &path : sharedLibPaths)
libPaths.push_back({path.c_str(), path.length()});
MlirExecutionEngine executionEngine = mlirExecutionEngineCreate(
module.get(), optLevel, libPaths.size(), libPaths.data(),
enableObjectDump, enablePIC);
if (mlirExecutionEngineIsNull(executionEngine))
throw std::runtime_error(
"Failure while creating the ExecutionEngine.");
new (&self) PyExecutionEngine(executionEngine);
},
nb::arg("module"), nb::arg("opt_level") = 2,
nb::arg("shared_libs") = nb::list(),
nb::arg("enable_object_dump") = true, nb::arg("enable_pic") = false,
"Create a new ExecutionEngine instance for the given Module. The "
"module must contain only dialects that can be translated to LLVM. "
"Perform transformations and code generation at the optimization "
"level `opt_level` if specified, or otherwise at the default "
"level of two (-O2). Load a list of libraries specified in "
"`shared_libs`.")
.def_prop_ro(MLIR_PYTHON_CAPI_PTR_ATTR, &PyExecutionEngine::getCapsule)
.def("_testing_release", &PyExecutionEngine::release,
"Releases (leaks) the backing ExecutionEngine (for testing purpose)")
.def(MLIR_PYTHON_CAPI_FACTORY_ATTR, &PyExecutionEngine::createFromCapsule)
.def(
"raw_lookup",
[](PyExecutionEngine &executionEngine, const std::string &func) {
auto *res = mlirExecutionEngineLookupPacked(
executionEngine.get(),
mlirStringRefCreate(func.c_str(), func.size()));
return reinterpret_cast<uintptr_t>(res);
},
nb::arg("func_name"),
"Lookup function `func` in the ExecutionEngine.")
.def(
"raw_register_runtime",
[](PyExecutionEngine &executionEngine, const std::string &name,
const nb::object &callbackObj) {
executionEngine.addReferencedObject(callbackObj);
uintptr_t rawSym =
nb::cast<uintptr_t>(nb::getattr(callbackObj, "value"));
mlirExecutionEngineRegisterSymbol(
executionEngine.get(),
mlirStringRefCreate(name.c_str(), name.size()),
reinterpret_cast<void *>(rawSym));
},
nb::arg("name"), nb::arg("callback"),
"Register `callback` as the runtime symbol `name`.")
.def(
"initialize",
[](PyExecutionEngine &executionEngine) {
mlirExecutionEngineInitialize(executionEngine.get());
},
"Initialize the ExecutionEngine. Global constructors specified by "
"`llvm.mlir.global_ctors` will be run. One common scenario is that "
"kernel binary compiled from `gpu.module` gets loaded during "
"initialization. Make sure all symbols are resolvable before "
"initialization by calling `register_runtime` or including "
"shared libraries.")
.def(
"dump_to_object_file",
[](PyExecutionEngine &executionEngine, const std::string &fileName) {
mlirExecutionEngineDumpToObjectFile(
executionEngine.get(),
mlirStringRefCreate(fileName.c_str(), fileName.size()));
},
nb::arg("file_name"), "Dump ExecutionEngine to an object file.");
}
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