This document describes how to define Dialects.
Before diving into how to define these constructs, below is a quick refresher from the MLIR LangRef.
Dialects are the mechanism by which to engage with and extend the MLIR ecosystem. They allow for defining new attributes, operations, and types. Dialects are used to model a variety of different abstractions; from traditional arithmetic to pattern rewrites; and is one of the most fundamental aspects of MLIR.
At the most fundamental level, defining a dialect in MLIR is as simple as specializing the C++ Dialect class. That being said, MLIR provides a powerful declaratively specification mechanism via TableGen; a generic language with tooling to maintain records of domain-specific information; that simplifies the definition process by automatically generating all of the necessary boilerplate C++ code, significantly reduces maintainence burden when changing aspects of dialect definitions, and also provides additional tools on top (such as documentation generation). Given the above, the declarative specification is the expected mechanism for defining new dialects, and is the method detailed within this document. Before continuing, it is highly recommended that users review the TableGen Programmer's Reference for an introduction to its syntax and constructs.
Below showcases an example simple Dialect definition. We generally recommend defining the Dialect class in a different .td file from the attributes, operations, types, and other sub-components of the dialect to establish a proper layering between the various different dialect components. It also prevents situations where you may inadvertantly generate multiple definitions for some constructs. This recommendation extends to all of the MLIR constructs, including Interfaces for example.
// Include the definition of the necessary tablegen constructs for defining // our dialect. include "mlir/IR/DialectBase.td" // Here is a simple definition of a dialect. def MyDialect : Dialect { let summary = "A short one line description of my dialect."; let description = [{ My dialect is a very important dialect. This section contains a much more detailed description that documents all of the important pieces of information to know about the document. }]; /// This is the namespace of the dialect. It is used to encapsulate the sub-components /// of the dialect, such as operations ("my_dialect.foo"). let name = "my_dialect"; /// The C++ namespace that the dialect, and its sub-components, get placed in. let cppNamespace = "::my_dialect"; }
The above showcases a very simple description of a dialect, but dialects have lots of other capabilities that you may or may not need to utilize.
Every dialect must implement an initialization hook to add attributes, operations, types, attach any desired interfaces, or perform any other necessary initialization for the dialect that should happen on construction. This hook is declared for every dialect to define, and has the form:
void MyDialect::initialize() { // Dialect initialization logic should be defined in here. }
The summary and description fields allow for providing user documentation for the dialect. The summary field expects a simple single-line string, with the description field used for long and extensive documentation. This documentation can be used to generate markdown documentation for the dialect and is used by upstream MLIR dialects.
The name of the C++ class which gets generated is the same as the name of our TableGen dialect definition, but with any _ characters stripped out. This means that if you name your dialect Foo_Dialect, the generated C++ class would be FooDialect. In the example above, we would get a C++ dialect named MyDialect.
The namespace that the C++ class for our dialect, and all of its sub-components, is placed under is specified by the cppNamespace field. By default, uses the name of the dialect as the only namespace. To avoid placing in any namespace, use "". To specify nested namespaces, use "::" as the delimiter between namespace, e.g., given "A::B", C++ classes will be placed within: namespace A { namespace B { <classes> } }.
Note that this works in conjunction with the dialect‘s C++ code. Depending on how the generated files are included, you may want to specify a full namespace path or a partial one. In general, it’s best to use full namespaces whenever you can. This makes it easier for dialects within different namespaces, and projects, to interact with each other.
When generating accessors for dialects and their components (attributes, operations, types, etc.), we prefix the name with get and set respectively, and transform snake_style names to camel case (UpperCamel when prefixed, and lowerCamel for individual variable names). For example, if an operation were defined as:
def MyOp : MyDialect<"op"> { let arguments = (ins StrAttr:$value, StrAttr:$other_value); }
It would have accessors generated for the value and other_value attributes as follows:
StringAttr MyOp::getValue(); void MyOp::setValue(StringAttr newValue); StringAttr MyOp::getOtherValue(); void MyOp::setOtherValue(StringAttr newValue);
MLIR has a very large ecosystem, and contains dialects that server many different purposes. It is quite common, given the above, that dialects may want to reuse certain components from other dialects. This may mean generating operations from those dialects during canonicalization, reusing attributes or types, etc. When a dialect has a dependency on another, i.e. when it constructs and/or generally relies on the components of another dialect, a dialect dependency should be explicitly recorded. An explicitly dependency ensures that dependent dialects are loaded alongside the dialect. Dialect dependencies can be recorded using the dependentDialects dialects field:
def MyDialect : Dialect { // Here we register the Arithmetic and Func dialect as dependencies of our `MyDialect`. let dependentDialects = [ "arith::ArithDialect", "func::FuncDialect" ]; }
The declarative Dialect definitions try to auto-generate as much logic and methods as possible. With that said, there will always be long-tail cases that won't be covered. For such cases, extraClassDeclaration can be used. Code within the extraClassDeclaration field will be copied literally to the generated C++ Dialect class.
Note that extraClassDeclaration is a mechanism intended for long-tail cases by power users; for not-yet-implemented widely-applicable cases, improving the infrastructure is preferable.
hasConstantMaterializer: Materializing Constants from AttributesThis field is utilized to materialize a constant operation from an Attribute value and a Type. This is generally used when an operation within this dialect has been folded, and a constant operation should be generated. hasConstantMaterializer is used to enable materialization, and the materializeConstant hook is declared on the dialect. This hook takes in an Attribute value, generally returned by fold, and produces a “constant-like” operation that materializes that value. See the documentation for canonicalization for a more in-depth introduction to folding in MLIR.
Constant materialization logic can then be defined in the source file:
/// Hook to materialize a single constant operation from a given attribute value /// with the desired resultant type. This method should use the provided builder /// to create the operation without changing the insertion position. The /// generated operation is expected to be constant-like. On success, this hook /// should return the operation generated to represent the constant value. /// Otherwise, it should return nullptr on failure. Operation *MyDialect::materializeConstant(OpBuilder &builder, Attribute value, Type type, Location loc) { ... }
hasNonDefaultDestructor: Providing a custom destructorThis field should be used when the Dialect class has a custom destructor, i.e. when the dialect has some special logic to be run in the ~MyDialect. In this case, only the declaration of the destructor is generated for the Dialect class.
As described by the MLIR Language Reference, discardable attribute are a type of attribute that has its semantics defined by the dialect whose name prefixes that of the attribute. For example, if an operation has an attribute named gpu.contained_module, the gpu dialect defines the semantics and invariants, such as when and where it is valid to use, of that attribute. To hook into this verification for attributes that are prefixed by our dialect, several hooks on the Dialect may be used:
hasOperationAttrVerifyThis field generates the hook for verifying when a discardable attribute of this dialect has been used within the attribute dictionary of an operation. This hook has the form:
/// Verify the use of the given attribute, whose name is prefixed by the namespace of this /// dialect, that was used in `op`s dictionary. LogicalResult MyDialect::verifyOperationAttribute(Operation *op, NamedAttribute attribute);
hasRegionArgAttrVerifyThis field generates the hook for verifying when a discardable attribute of this dialect has been used within the attribute dictionary of a region entry block argument. Note that the block arguments of a region entry block do not themselves have attribute dictionaries, but some operations may provide special dictionary attributes that correspond to the arguments of a region. For example, operations that implement FunctionOpInterface may have attribute dictionaries on the operation that correspond to the arguments of entry block of the function. In these cases, those operations will invoke this hook on the dialect to ensure the attribute is verified. The hook necessary for the dialect to implement has the form:
/// Verify the use of the given attribute, whose name is prefixed by the namespace of this /// dialect, that was used on the attribute dictionary of a region entry block argument. /// Note: As described above, when a region entry block has a dictionary is up to the individual /// operation to define. LogicalResult MyDialect::verifyRegionArgAttribute(Operation *op, unsigned regionIndex, unsigned argIndex, NamedAttribute attribute);
hasRegionResultAttrVerifyThis field generates the hook for verifying when a discardable attribute of this dialect has been used within the attribute dictionary of a region result. Note that the results of a region do not themselves have attribute dictionaries, but some operations may provide special dictionary attributes that correspond to the results of a region. For example, operations that implement FunctionOpInterface may have attribute dictionaries on the operation that correspond to the results of the function. In these cases, those operations will invoke this hook on the dialect to ensure the attribute is verified. The hook necessary for the dialect to implement has the form:
/// Generate verification for the given attribute, whose name is prefixed by the namespace /// of this dialect, that was used on the attribute dictionary of a region result. /// Note: As described above, when a region entry block has a dictionary is up to the individual /// operation to define. LogicalResult MyDialect::verifyRegionResultAttribute(Operation *op, unsigned regionIndex, unsigned argIndex, NamedAttribute attribute);
useFoldAPIThere are currently two possible values that are allowed to be assigned to this field:
kEmitFoldAdaptorFolder generates a fold method making use of the op's FoldAdaptor to allow access of operands via convenient getter.
Generated code example:
OpFoldResult fold(FoldAdaptor adaptor); // or LogicalResult fold(FoldAdaptor adaptor, SmallVectorImpl<OpFoldResult>& results);
kEmitRawAttributesFolder generates the deprecated legacy fold method, containing ArrayRef<Attribute> in the parameter list instead of the op's FoldAdaptor. This API is scheduled for removal and should not be used by new dialects.
Generated code example:
OpFoldResult fold(ArrayRef<Attribute> operands); // or LogicalResult fold(ArrayRef<Attribute> operands, SmallVectorImpl<OpFoldResult>& results);
Some dialects have an open ecosystem and don‘t register all of the possible operations. In such cases it is still possible to provide support for implementing an OpInterface for these operations. When an operation isn’t registered or does not provide an implementation for an interface, the query will fallback to the dialect itself. The hasOperationInterfaceFallback field may be used to declare this fallback for operations:
/// Return an interface model for the interface with the given `typeId` for the operation /// with the given name. void *MyDialect::getRegisteredInterfaceForOp(TypeID typeID, StringAttr opName);
For a more detail description of the expected usages of this hook, view the detailed interface documentation.
When a dialect registers an Attribute or Type, it must also override the respective Dialect::parseAttribute/Dialect::printAttribute or Dialect::parseType/Dialect::printType methods. In these cases, the dialect must explicitly handle the parsing and printing of each individual attribute or type within the dialect. If all of the attributes and types of the dialect provide a mnemonic, however, these methods may be autogenerated by using the useDefaultAttributePrinterParser and useDefaultTypePrinterParser fields. By default, these fields are set to 1(enabled), meaning that if a dialect needs to explicitly handle the parser and printer of its Attributes and Types it should set these to 0 as necessary.
Generally, canonicalization patterns are specific to individual operations within a dialect. There are some cases, however, that prompt canonicalization patterns to be added to the dialect-level. For example, if a dialect defines a canonicalization pattern that operates on an interface or trait, it can be beneficial to only add this pattern once, instead of duplicating per-operation that implements that interface. To enable the generation of this hook, the hasCanonicalizer field may be used. This will declare the getCanonicalizationPatterns method on the dialect, which has the form:
/// Return the canonicalization patterns for this dialect: void MyDialect::getCanonicalizationPatterns(RewritePatternSet &results) const;
See the documentation for Canonicalization in MLIR for a much more detailed description about canonicalization patterns.
This section documents the design and API of the extensible dialects. Extensible dialects are dialects that can be extended with new operations and types defined at runtime. This allows for users to define dialects via with meta-programming, or from another language, without having to recompile C++ code.
Dialects defined in C++ can be extended with new operations, types, etc., at runtime by inheriting from mlir::ExtensibleDialect instead of mlir::Dialect (note that ExtensibleDialect inherits from Dialect). The ExtensibleDialect class contains the necessary fields and methods to extend the dialect at runtime.
class MyDialect : public mlir::ExtensibleDialect { ... }
For dialects defined in TableGen, this is done by setting the isExtensible flag to 1.
def Test_Dialect : Dialect { let isExtensible = 1; ... }
An extensible Dialect can be casted back to ExtensibleDialect using llvm::dyn_cast, or llvm::cast:
if (auto extensibleDialect = llvm::dyn_cast<ExtensibleDialect>(dialect)) { ... }
Dynamic dialects are extensible dialects that can be defined at runtime. They are only populated with dynamic operations, types, and attributes. They can be registered in a DialectRegistry with insertDynamic.
auto populateDialect = [](MLIRContext *ctx, DynamicDialect* dialect) { // Code that will be ran when the dynamic dialect is created and loaded. // For instance, this is where we register the dynamic operations, types, and // attributes of the dialect. ... } registry.insertDynamic("dialectName", populateDialect);
Once a dynamic dialect is registered in the MLIRContext, it can be retrieved with getOrLoadDialect.
Dialect *dialect = ctx->getOrLoadDialect("dialectName");
The DynamicOpDefinition class represents the definition of an operation defined at runtime. It is created using the DynamicOpDefinition::get functions. An operation defined at runtime must provide a name, a dialect in which the operation will be registered in, an operation verifier. It may also optionally define a custom parser and a printer, fold hook, and more.
// The operation name, without the dialect name prefix. StringRef name = "my_operation_name"; // The dialect defining the operation. Dialect* dialect = ctx->getOrLoadDialect<MyDialect>(); // Operation verifier definition. AbstractOperation::VerifyInvariantsFn verifyFn = [](Operation* op) { // Logic for the operation verification. ... } // Parser function definition. AbstractOperation::ParseAssemblyFn parseFn = [](OpAsmParser &parser, OperationState &state) { // Parse the operation, given that the name is already parsed. ... }; // Printer function auto printFn = [](Operation *op, OpAsmPrinter &printer) { printer << op->getName(); // Print the operation, given that the name is already printed. ... }; // General folder implementation, see AbstractOperation::foldHook for more // information. auto foldHookFn = [](Operation * op, ArrayRef<Attribute> operands, SmallVectorImpl<OpFoldResult> &result) { ... }; // Returns any canonicalization pattern rewrites that the operation // supports, for use by the canonicalization pass. auto getCanonicalizationPatterns = [](RewritePatternSet &results, MLIRContext *context) { ... } // Definition of the operation. std::unique_ptr<DynamicOpDefinition> opDef = DynamicOpDefinition::get(name, dialect, std::move(verifyFn), std::move(parseFn), std::move(printFn), std::move(foldHookFn), std::move(getCanonicalizationPatterns));
Once the operation is defined, it can be registered by an ExtensibleDialect:
extensibleDialect->registerDynamicOperation(std::move(opDef));
Note that the Dialect given to the operation should be the one registering the operation.
It is possible to match on an operation defined at runtime using their names:
if (op->getName().getStringRef() == "my_dialect.my_dynamic_op") { ... }
An operation defined at runtime can be created by instantiating an OperationState with the operation name, and using it with a rewriter (for instance a PatternRewriter) to create the operation.
OperationState state(location, "my_dialect.my_dynamic_op", operands, resultTypes, attributes); rewriter.createOperation(state);
Contrary to types defined in C++ or in TableGen, types defined at runtime can only have as argument a list of Attribute.
Similarily to operations, a type is defined at runtime using the class DynamicTypeDefinition, which is created using the DynamicTypeDefinition::get functions. A type definition requires a name, the dialect that will register the type, and a parameter verifier. It can also define optionally a custom parser and printer for the arguments (the type name is assumed to be already parsed/printed).
// The type name, without the dialect name prefix. StringRef name = "my_type_name"; // The dialect defining the type. Dialect* dialect = ctx->getOrLoadDialect<MyDialect>(); // The type verifier. // A type defined at runtime has a list of attributes as parameters. auto verifier = [](function_ref<InFlightDiagnostic()> emitError, ArrayRef<Attribute> args) { ... }; // The type parameters parser. auto parser = [](DialectAsmParser &parser, llvm::SmallVectorImpl<Attribute> &parsedParams) { ... }; // The type parameters printer. auto printer =[](DialectAsmPrinter &printer, ArrayRef<Attribute> params) { ... }; std::unique_ptr<DynamicTypeDefinition> typeDef = DynamicTypeDefinition::get(std::move(name), std::move(dialect), std::move(verifier), std::move(printer), std::move(parser));
If the printer and the parser are ommited, a default parser and printer is generated with the format !dialect.typename<arg1, arg2, ..., argN>.
The type can then be registered by the ExtensibleDialect:
dialect->registerDynamicType(std::move(typeDef));
parseType methods generated by TableGen can parse types defined at runtime, though overriden parseType methods need to add the necessary support for them.
Type MyDialect::parseType(DialectAsmParser &parser) const { ... // The type name. StringRef typeTag; if (failed(parser.parseKeyword(&typeTag))) return Type(); // Try to parse a dynamic type with 'typeTag' name. Type dynType; auto parseResult = parseOptionalDynamicType(typeTag, parser, dynType); if (parseResult.has_value()) { if (succeeded(parseResult.getValue())) return dynType; return Type(); } ... }
Dynamic types are instances of DynamicType. It is possible to get a dynamic type with DynamicType::get and ExtensibleDialect::lookupTypeDefinition.
auto typeDef = extensibleDialect->lookupTypeDefinition("my_dynamic_type"); ArrayRef<Attribute> params = ...; auto type = DynamicType::get(typeDef, params);
It is also possible to cast a Type known to be defined at runtime to a DynamicType.
auto dynType = type.cast<DynamicType>(); auto typeDef = dynType.getTypeDef(); auto args = dynType.getParams();
Similar to types defined at runtime, attributes defined at runtime can only have as argument a list of Attribute.
Similarily to types, an attribute is defined at runtime using the class DynamicAttrDefinition, which is created using the DynamicAttrDefinition::get functions. An attribute definition requires a name, the dialect that will register the attribute, and a parameter verifier. It can also define optionally a custom parser and printer for the arguments (the attribute name is assumed to be already parsed/printed).
// The attribute name, without the dialect name prefix. StringRef name = "my_attribute_name"; // The dialect defining the attribute. Dialect* dialect = ctx->getOrLoadDialect<MyDialect>(); // The attribute verifier. // An attribute defined at runtime has a list of attributes as parameters. auto verifier = [](function_ref<InFlightDiagnostic()> emitError, ArrayRef<Attribute> args) { ... }; // The attribute parameters parser. auto parser = [](DialectAsmParser &parser, llvm::SmallVectorImpl<Attribute> &parsedParams) { ... }; // The attribute parameters printer. auto printer =[](DialectAsmPrinter &printer, ArrayRef<Attribute> params) { ... }; std::unique_ptr<DynamicAttrDefinition> attrDef = DynamicAttrDefinition::get(std::move(name), std::move(dialect), std::move(verifier), std::move(printer), std::move(parser));
If the printer and the parser are ommited, a default parser and printer is generated with the format !dialect.attrname<arg1, arg2, ..., argN>.
The attribute can then be registered by the ExtensibleDialect:
dialect->registerDynamicAttr(std::move(typeDef));
parseAttribute methods generated by TableGen can parse attributes defined at runtime, though overriden parseAttribute methods need to add the necessary support for them.
Attribute MyDialect::parseAttribute(DialectAsmParser &parser, Type type) const override { ... // The attribute name. StringRef attrTag; if (failed(parser.parseKeyword(&attrTag))) return Attribute(); // Try to parse a dynamic attribute with 'attrTag' name. Attribute dynAttr; auto parseResult = parseOptionalDynamicAttr(attrTag, parser, dynAttr); if (parseResult.has_value()) { if (succeeded(*parseResult)) return dynAttr; return Attribute(); }
Similar to types, attributes defined at runtime are instances of DynamicAttr. It is possible to get a dynamic attribute with DynamicAttr::get and ExtensibleDialect::lookupAttrDefinition.
auto attrDef = extensibleDialect->lookupAttrDefinition("my_dynamic_attr"); ArrayRef<Attribute> params = ...; auto attr = DynamicAttr::get(attrDef, params);
It is also possible to cast an Attribute known to be defined at runtime to a DynamicAttr.
auto dynAttr = attr.cast<DynamicAttr>(); auto attrDef = dynAttr.getAttrDef(); auto args = dynAttr.getParams();
The role of extensible dialects is to own the necessary data for defined operations and types. They also contain the necessary accessors to easily access them.
In order to cast a Dialect back to an ExtensibleDialect, we implement the IsExtensibleDialect interface to all ExtensibleDialect. The casting is done by checking if the Dialect implements IsExtensibleDialect or not.
Operations are represented in mlir using the AbstractOperation class. They are registered in dialects the same way operations defined in C++ are registered, which is by calling AbstractOperation::insert.
The only difference is that a new TypeID needs to be created for each operation, since operations are not represented by a C++ class. This is done using a TypeIDAllocator, which can allocate a new unique TypeID at runtime.
Unlike operations, types need to define a C++ storage class that takes care of type parameters. They also need to define another C++ class to access that storage. DynamicTypeStorage defines the storage of types defined at runtime, and DynamicType gives access to the storage, as well as defining useful functions. A DynamicTypeStorage contains a list of Attribute type parameters, as well as a pointer to the type definition.
Types are registered using the Dialect::addType method, which expect a TypeID that is generated using a TypeIDAllocator. The type uniquer also register the type with the given TypeID. This mean that we can reuse our single DynamicType with different TypeID to represent the different types defined at runtime.
Since the different types defined at runtime have different TypeID, it is not possible to use TypeID to cast a Type into a DynamicType. Thus, similar to Dialect, all DynamicType define a IsDynamicTypeTrait, so casting a Type to a DynamicType boils down to querying the IsDynamicTypeTrait trait.