Introduce the initial support for operation interfaces in C API and Python bindings. Interfaces are a key component of MLIR's extensibility and should be available in bindings to make use of full potential of MLIR. This initial implementation exposes InferTypeOpInterface all the way to the Python bindings since it can be later used to simplify the operation construction methods by inferring their return types instead of requiring the user to do so. The general infrastructure for binding interfaces is defined and InferTypeOpInterface can be used as an example for binding other interfaces. Reviewed By: gysit Differential Revision: https://reviews.llvm.org/D111656
241 lines
9.0 KiB
C++
241 lines
9.0 KiB
C++
//===- IRInterfaces.cpp - MLIR IR interfaces pybind -----------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "IRModule.h"
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#include "mlir-c/BuiltinAttributes.h"
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#include "mlir-c/Interfaces.h"
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namespace py = pybind11;
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namespace mlir {
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namespace python {
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constexpr static const char *constructorDoc =
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R"(Creates an interface from a given operation/opview object or from a
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subclass of OpView. Raises ValueError if the operation does not implement the
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interface.)";
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constexpr static const char *operationDoc =
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R"(Returns an Operation for which the interface was constructed.)";
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constexpr static const char *opviewDoc =
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R"(Returns an OpView subclass _instance_ for which the interface was
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constructed)";
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constexpr static const char *inferReturnTypesDoc =
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R"(Given the arguments required to build an operation, attempts to infer
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its return types. Raises ValueError on failure.)";
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/// CRTP base class for Python classes representing MLIR Op interfaces.
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/// Interface hierarchies are flat so no base class is expected here. The
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/// derived class is expected to define the following static fields:
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/// - `const char *pyClassName` - the name of the Python class to create;
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/// - `GetTypeIDFunctionTy getInterfaceID` - the function producing the TypeID
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/// of the interface.
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/// Derived classes may redefine the `bindDerived(ClassTy &)` method to bind
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/// interface-specific methods.
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///
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/// An interface class may be constructed from either an Operation/OpView object
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/// or from a subclass of OpView. In the latter case, only the static interface
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/// methods are available, similarly to calling ConcereteOp::staticMethod on the
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/// C++ side. Implementations of concrete interfaces can use the `isStatic`
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/// method to check whether the interface object was constructed from a class or
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/// an operation/opview instance. The `getOpName` always succeeds and returns a
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/// canonical name of the operation suitable for lookups.
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template <typename ConcreteIface>
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class PyConcreteOpInterface {
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protected:
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using ClassTy = py::class_<ConcreteIface>;
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using GetTypeIDFunctionTy = MlirTypeID (*)();
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public:
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/// Constructs an interface instance from an object that is either an
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/// operation or a subclass of OpView. In the latter case, only the static
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/// methods of the interface are accessible to the caller.
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PyConcreteOpInterface(py::object object, DefaultingPyMlirContext context)
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: obj(object) {
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try {
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operation = &py::cast<PyOperation &>(obj);
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} catch (py::cast_error &err) {
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// Do nothing.
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}
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try {
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operation = &py::cast<PyOpView &>(obj).getOperation();
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} catch (py::cast_error &err) {
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// Do nothing.
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}
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if (operation != nullptr) {
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if (!mlirOperationImplementsInterface(*operation,
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ConcreteIface::getInterfaceID())) {
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std::string msg = "the operation does not implement ";
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throw py::value_error(msg + ConcreteIface::pyClassName);
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}
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MlirIdentifier identifier = mlirOperationGetName(*operation);
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MlirStringRef stringRef = mlirIdentifierStr(identifier);
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opName = std::string(stringRef.data, stringRef.length);
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} else {
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try {
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opName = obj.attr("OPERATION_NAME").template cast<std::string>();
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} catch (py::cast_error &err) {
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throw py::type_error(
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"Op interface does not refer to an operation or OpView class");
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}
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if (!mlirOperationImplementsInterfaceStatic(
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mlirStringRefCreate(opName.data(), opName.length()),
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context.resolve().get(), ConcreteIface::getInterfaceID())) {
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std::string msg = "the operation does not implement ";
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throw py::value_error(msg + ConcreteIface::pyClassName);
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}
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}
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}
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/// Creates the Python bindings for this class in the given module.
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static void bind(py::module &m) {
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py::class_<ConcreteIface> cls(m, "InferTypeOpInterface",
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py::module_local());
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cls.def(py::init<py::object, DefaultingPyMlirContext>(), py::arg("object"),
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py::arg("context") = py::none(), constructorDoc)
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.def_property_readonly("operation",
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&PyConcreteOpInterface::getOperationObject,
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operationDoc)
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.def_property_readonly("opview", &PyConcreteOpInterface::getOpView,
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opviewDoc);
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ConcreteIface::bindDerived(cls);
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}
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/// Hook for derived classes to add class-specific bindings.
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static void bindDerived(ClassTy &cls) {}
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/// Returns `true` if this object was constructed from a subclass of OpView
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/// rather than from an operation instance.
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bool isStatic() { return operation == nullptr; }
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/// Returns the operation instance from which this object was constructed.
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/// Throws a type error if this object was constructed from a subclass of
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/// OpView.
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py::object getOperationObject() {
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if (operation == nullptr) {
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throw py::type_error("Cannot get an operation from a static interface");
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}
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return operation->getRef().releaseObject();
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}
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/// Returns the opview of the operation instance from which this object was
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/// constructed. Throws a type error if this object was constructed form a
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/// subclass of OpView.
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py::object getOpView() {
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if (operation == nullptr) {
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throw py::type_error("Cannot get an opview from a static interface");
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}
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return operation->createOpView();
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}
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/// Returns the canonical name of the operation this interface is constructed
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/// from.
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const std::string &getOpName() { return opName; }
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private:
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PyOperation *operation = nullptr;
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std::string opName;
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py::object obj;
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};
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/// Python wrapper for InterTypeOpInterface. This interface has only static
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/// methods.
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class PyInferTypeOpInterface
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: public PyConcreteOpInterface<PyInferTypeOpInterface> {
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public:
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using PyConcreteOpInterface<PyInferTypeOpInterface>::PyConcreteOpInterface;
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constexpr static const char *pyClassName = "InferTypeOpInterface";
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constexpr static GetTypeIDFunctionTy getInterfaceID =
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&mlirInferTypeOpInterfaceTypeID;
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/// C-style user-data structure for type appending callback.
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struct AppendResultsCallbackData {
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std::vector<PyType> &inferredTypes;
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PyMlirContext &pyMlirContext;
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};
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/// Appends the types provided as the two first arguments to the user-data
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/// structure (expects AppendResultsCallbackData).
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static void appendResultsCallback(intptr_t nTypes, MlirType *types,
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void *userData) {
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auto *data = static_cast<AppendResultsCallbackData *>(userData);
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data->inferredTypes.reserve(data->inferredTypes.size() + nTypes);
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for (intptr_t i = 0; i < nTypes; ++i) {
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data->inferredTypes.push_back(
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PyType(data->pyMlirContext.getRef(), types[i]));
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}
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}
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/// Given the arguments required to build an operation, attempts to infer its
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/// return types. Throws value_error on faliure.
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std::vector<PyType>
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inferReturnTypes(llvm::Optional<std::vector<PyValue>> operands,
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llvm::Optional<PyAttribute> attributes,
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llvm::Optional<std::vector<PyRegion>> regions,
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DefaultingPyMlirContext context,
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DefaultingPyLocation location) {
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llvm::SmallVector<MlirValue> mlirOperands;
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llvm::SmallVector<MlirRegion> mlirRegions;
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if (operands) {
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mlirOperands.reserve(operands->size());
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for (PyValue &value : *operands) {
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mlirOperands.push_back(value);
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}
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}
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if (regions) {
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mlirRegions.reserve(regions->size());
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for (PyRegion ®ion : *regions) {
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mlirRegions.push_back(region);
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}
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}
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std::vector<PyType> inferredTypes;
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PyMlirContext &pyContext = context.resolve();
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AppendResultsCallbackData data{inferredTypes, pyContext};
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MlirStringRef opNameRef =
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mlirStringRefCreate(getOpName().data(), getOpName().length());
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MlirAttribute attributeDict =
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attributes ? attributes->get() : mlirAttributeGetNull();
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MlirLogicalResult result = mlirInferTypeOpInterfaceInferReturnTypes(
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opNameRef, pyContext.get(), location.resolve(), mlirOperands.size(),
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mlirOperands.data(), attributeDict, mlirRegions.size(),
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mlirRegions.data(), &appendResultsCallback, &data);
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if (mlirLogicalResultIsFailure(result)) {
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throw py::value_error("Failed to infer result types");
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}
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return inferredTypes;
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}
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static void bindDerived(ClassTy &cls) {
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cls.def("inferReturnTypes", &PyInferTypeOpInterface::inferReturnTypes,
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py::arg("operands") = py::none(),
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py::arg("attributes") = py::none(), py::arg("regions") = py::none(),
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py::arg("context") = py::none(), py::arg("loc") = py::none(),
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inferReturnTypesDoc);
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}
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};
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void populateIRInterfaces(py::module &m) { PyInferTypeOpInterface::bind(m); }
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} // namespace python
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} // namespace mlir
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