8.7 KiB
Introduction to MLIR Operation Traits
[TOC]
MLIR allows for a truly open operation ecosystem, as any dialect may define
operations that suit a specific level of abstraction. Traits
are a mechanism
in which to abstract implementation details and properties that are common
across many different operations. Traits
may be used to specify special
properties and constraints of the operation, including whether the operation has
side effects or whether its output has the same type as the input. Some examples
of traits are Commutative
, SingleResult
, Terminator
, etc. See the more
comprehensive list below for more examples of what is possible.
Defining a Trait
Traits may be defined in C++ by inheriting from the
OpTrait::TraitBase<ConcreteType, TraitType>
class. This base class takes as
template parameters:
- ConcreteType
- The concrete operation type that this trait was attached to.
- TraitType
- The type of the trait class that is being defined, for use with the
Curiously Recurring Template Pattern
.
- The type of the trait class that is being defined, for use with the
A derived trait class is expected to take a single template that corresponds to
the ConcreteType
. An example trait definition is shown below:
template <typename ConcreteType>
class MyTrait : public OpTrait::TraitBase<ConcreteType, MyTrait> {
};
Derived traits may also provide a verifyTrait
hook, that is called when
verifying the concrete operation. The trait verifiers will currently always be
invoked before the main Op::verify
.
template <typename ConcreteType>
class MyTrait : public OpTrait::TraitBase<ConcreteType, MyTrait> {
public:
/// Override the 'verifyTrait' hook to add additional verification on the
/// concrete operation.
static LogicalResult verifyTrait(Operation *op) {
// ...
}
};
Note: It is generally good practice to define the implementation of the
verifyTrait
hook out-of-line as a free function when possible to avoid
instantiating the implementation for every concrete operation type.
Parametric Traits
The above demonstrates the definition of a simple self-contained trait. It is also often useful to provide some static parameters to the trait to control its behavior. Given that the definition of the trait class is rigid, i.e. we must have a single template argument for the concrete operation, the templates for the parameters will need to be split out. An example is shown below:
template <int Parameter>
class MyParametricTrait {
public:
template <typename ConcreteType>
class Impl : public OpTrait::TraitBase<ConcreteType, Impl> {
// Inside of 'Impl' we have full access to the template parameters
// specified above.
};
};
Attaching a Trait
Traits may be used when defining a derived operation type, by simply adding the
name of the trait class to the Op
class after the concrete operation type:
/// Here we define 'MyOp' along with the 'MyTrait' and `MyParametric trait
/// classes we defined previously.
class MyOp : public Op<MyOp, MyTrait, MyParametricTrait<10>::Impl> {};
To use a trait in the ODS framework, we need to provide a
definition of the trait class. This can be done using the NativeOpTrait
and
ParamNativeOpTrait
classes. ParamNativeOpTrait
provides a mechanism in which
to specify arguments to a parametric trait class with an internal Impl
.
// The argument is the c++ trait class name.
def MyTrait : NativeOpTrait<"MyTrait">;
// The first argument is the parent c++ class name. The second argument is a
// string containing the parameter list.
class MyParametricTrait<int prop>
: NativeOpTrait<"MyParametricTrait", !cast<string>(!head(parameters))>;
These can then be used in the traits
list of an op definition:
def OpWithInferTypeInterfaceOp : Op<...[MyTrait, MyParametricTrait<10>]> { ... }
See the documentation on operation definitions for more details.
Using a Trait
Traits may be used to provide additional methods, static fields, or other
information directly on the concrete operation. Traits
internally become
Base
classes of the concrete operation, so all of these are directly
accessible. To expose this information opaquely to transformations and analyses,
interfaces
may be used.
To query if a specific operation contains a specific trait, the hasTrait<>
method may be used. This takes as a template parameter the trait class, which is
the same as the one passed when attaching the trait to an operation.
Operation *op = ..;
if (op->hasTrait<MyTrait>() || op->hasTrait<MyParametricTrait<10>::Impl>())
...;
Trait List
MLIR provides a suite of traits that provide various functionalities that are common across many different operations. Below is a list of some key traits that may be used directly by any dialect. The format of the header for each trait section goes as follows:
Header
- (
C++ class
--ODS class
(if applicable))
- (
Broadcastable
OpTrait::BroadcastableTwoOperandsOneResult
--Broadcastable
This trait provides the API for operations that are known to have
broadcast-compatible
operand and result types. Specifically, starting from the most varying
dimension, each dimension pair of the two operands' types should either be the
same or one of them is one. Also, the result type should have the corresponding
dimension equal to the larger one, if known. Shapes are checked partially if
ranks or dimensions are not known. For example, an op with tensor<?x2xf32>
and
tensor<2xf32>
as operand types and tensor<3x2xf32>
as the result type is
broadcast-compatible.
Ths trait assumes the op has two operands and one result, and it asserts if the pre-condition is not satisfied.
Commutative
OpTrait::IsCommutative
--Commutative
This trait adds the property that the operation is commutative, i.e. X op Y == Y op X
Function-Like
OpTrait::FunctionLike
This trait provides APIs for operations that behave like functions. In particular:
- Ops must be symbols, i.e. also have the
Symbol
trait; - Ops have a single region with multiple blocks that corresponds to the body of the function;
- the absence of a region corresponds to an external function;
- arguments of the first block of the region are treated as function arguments;
- they can have argument and result attributes that are stored in dictionary attributes on the operation itself.
This trait does NOT provide type support for the functions, meaning that
concrete Ops must handle the type of the declared or defined function.
getTypeAttrName()
is a convenience function that returns the name of the
attribute that can be used to store the function type, but the trait makes no
assumption based on it.
HasParent
OpTrait::HasParent<typename ParentOpType>
--HasParent<string op>
This trait provides APIs and verifiers for operations that can only be nested
within regions that are attached to operations of ParentOpType
.
IsolatedFromAbove
OpTrait::IsIsolatedFromAbove
--IsolatedFromAbove
This trait signals that the regions of an operations are known to be isolated
from above. This trait asserts that the regions of an operation will not
capture, or reference, SSA values defined above the region scope. This means
that the following is invalid if foo.region_op
is defined as
IsolatedFromAbove
:
%result = constant 10 : i32
foo.region_op {
foo.yield %result : i32
}
This trait is an important structural property of the IR, and enables operations to have passes scheduled under them.
NoSideEffect
OpTrait::HasNoSideEffect
--NoSideEffect
This trait signifies that the operation is pure and has no visible side effects.
Single Block with Implicit Terminator
OpTrait::SingleBlockImplicitTerminator<typename TerminatorOpType>
:SingleBlockImplicitTerminator<string op>
This trait provides APIs and verifiers for operations with regions that have a
single block that must terminate with TerminatorOpType
.
Symbol
OpTrait::Symbol
--Symbol
This trait is used for operations that define a Symbol
.
TODO(riverriddle) Link to the proper document detailing the design of symbols.
SymbolTable
OpTrait::SymbolTable
--SymbolTable
This trait is used for operations that define a SymbolTable
.
TODO(riverriddle) Link to the proper document detailing the design of symbols.
Terminator
OpTrait::IsTerminator
--Terminator
This trait provides verification and functionality for operations that are known to be terminators.