A previous commit added support for integer signedness in C++
IntegerType. This change introduces ODS definitions for
integer types and integer (element) attributes w.r.t. signedness.
This commit also updates various existing definitions' descriptions
to mention signless where suitable to make it more clear.
Positive and non-negative integer attributes are removed to avoid
the explosion of subclasses. Instead, one should use more atmoic
constraints together with Confined to model that. For example,
`Confined<..., [IntPositive]>`.
Differential Revision: https://reviews.llvm.org/D75610
For ODS generated operations enable querying whether there is a derived
attribute with a given name.
Rollforward of commit 5aa57c2 without using llvm::is_contained.
This reverts commit 5aa57c2812.
The source code generated due to this ods change does not compile,
as it passes to few arguments to llvm::is_contained.
Originally, intrinsics generator for the LLVM dialect has been producing
customized code fragments for the translation of MLIR operations to LLVM IR
intrinsics. LLVM dialect ODS now provides a generalized version of the
translation code, parameterizable with the properties of the operation.
Generate ODS that uses this version of the translation code instead of
generating a new version of it for each intrinsic.
Differential Revision: https://reviews.llvm.org/D74893
This revision add support for formatting successor variables in a similar way to operands, attributes, etc.
Differential Revision: https://reviews.llvm.org/D74789
This matches the '(print|parse)OptionalAttrDictWithKeyword' functionality provided by the assembly parser/printer.
Differential Revision: https://reviews.llvm.org/D74682
When operations have optional attributes, or optional operands(i.e. empty variadic operands), the assembly format often has an optional section to represent these arguments. This revision adds basic support for defining an "optional group" in the assembly format to support this. An optional group is defined by wrapping a set of elements in `()` followed by `?` and requires the following:
* The first element of the group must be either a literal or an operand argument.
- This is because the first element must be optionally parsable.
* There must be exactly one argument variable within the group that is marked as the anchor of the group. The anchor is the element whose presence controls whether the group should be printed/parsed. An element is marked as the anchor by adding a trailing `^`.
* The group must only contain literals, variables, and type directives.
- Any attribute variables may be used, but only optional attributes can be marked as the anchor.
- Only variadic, i.e. optional, operand arguments can be used.
- The elements of a type directive must be defined within the same optional group.
An example of this can be seen with the assembly format for ReturnOp, which has a variadic number of operands.
```
def ReturnOp : ... {
let arguments = (ins Variadic<AnyType>:$operands);
// We only print the operands+types if there are a non-zero number
// of operands.
let assemblyFormat = "attr-dict ($operands^ `:` type($operands))?";
}
```
Differential Revision: https://reviews.llvm.org/D74681
Thus far IntegerType has been signless: a value of IntegerType does
not have a sign intrinsically and it's up to the specific operation
to decide how to interpret those bits. For example, std.addi does
two's complement arithmetic, and std.divis/std.diviu treats the first
bit as a sign.
This design choice was made some time ago when we did't have lots
of dialects and dialects were more rigid. Today we have much more
extensible infrastructure and different dialect may want different
modelling over integer signedness. So while we can say we want
signless integers in the standard dialect, we cannot dictate for
others. Requiring each dialect to model the signedness semantics
with another set of custom types is duplicating the functionality
everywhere, considering the fundamental role integer types play.
This CL extends the IntegerType with a signedness semantics bit.
This gives each dialect an option to opt in signedness semantics
if that's what they want and helps code sharing. The parser is
modified to recognize `si[1-9][0-9]*` and `ui[1-9][0-9]*` as
signed and unsigned integer types, respectively, leaving the
original `i[1-9][0-9]*` to continue to mean no indication over
signedness semantics. All existing dialects are not affected (yet)
as this is a feature to opt in.
More discussions can be found at:
https://groups.google.com/a/tensorflow.org/d/msg/mlir/XmkV8HOPWpo/7O4X0Nb_AQAJ
Differential Revision: https://reviews.llvm.org/D72533
In some dialects, attributes may have default values that may be
determined only after shape inference. For example, attributes that
are dependent on the rank of the input cannot be assigned a default
value until the rank of the tensor is inferred.
While we can set attributes without explicit setters, referring to
the attributes via accessors instead of having to use the string
interface is better for compile time verification.
The proposed patch add one method per operation attribute that let us
set its value. The code is a very small modification of the existing
getter methods.
Differential Revision: https://reviews.llvm.org/D74143
In code generators, one can automate the translation of typed ArrayAttrs
if element attribute translators are already implemented. However, the
type of the element attribute is lost at the construction of
TypedArrayAttrBase. With this change one can inspect the element type
and generate the translation logic automatically, which will reduce the
code repetition.
Differential Revision: https://reviews.llvm.org/D73579
This revision makes sure that errors emitted outside of testing are treated as fatal errors. This avoids the current silent failures that occur when the format is invalid.
Summary: This revision add support for accepting a few type constraints, e.g. AllTypesMatch, when inferring types for operands and results. This is used to remove the c++ parsers for several additional operations.
Differential Revision: https://reviews.llvm.org/D73735
Summary:
This revision add support, and testing, for generating the parser and printer from the declarative operation format.
Differential Revision: https://reviews.llvm.org/D73406
Summary:
This is the first revision in a series that adds support for declaratively specifying the asm format of an operation. This revision
focuses solely on parsing the format. Future revisions will add support for generating the proper parser/printer, as well as
transitioning the syntax definition of many existing operations.
This was originally proposed here:
https://llvm.discourse.group/t/rfc-declarative-op-assembly-format/340
Differential Revision: https://reviews.llvm.org/D73405
Summary:
LLVMIRIntrinsicGen is using LLVM_Op as the base class for intrinsics.
This works for LLVM intrinsics in the LLVM Dialect, but when we are
trying to convert custom intrinsics that originate from a custom
LLVM dialect (like NVVM or ROCDL) these usually have a different
"cppNamespace" that needs to be applied to these dialect.
These dialect specific characteristics (like "cppNamespace")
are typically organized by creating a custom op (like NVVM_Op or
ROCDL_Op) that passes the correct dialect to the LLVM_OpBase class.
It seems natural to allow LLVMIRIntrinsicGen to take that into
consideration when generating the conversion code from one of these
dialect to a set of target specific intrinsics.
Reviewers: rriddle, andydavis1, antiagainst, nicolasvasilache, ftynse
Subscribers: jdoerfert, mehdi_amini, jpienaar, burmako, shauheen, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73233
Summary:
llvm::to_vector() accepts a Range value and not the pair of arguments
we are currently passing. Also we probably want the lowered LLVM
values in the vector, while operand_begin()/operand_end() on MLIR ops
returns MLIR types. lookupValues() seems the correct way to collect
such values.
Reviewers: rriddle, andydavis1, antiagainst, nicolasvasilache, ftynse
Subscribers: jdoerfert, mehdi_amini, jpienaar, burmako, shauheen, arpith-jacob, mgester, lucyrfox, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D73137
Summary:
Add method in ODS to specify verification for operations implementing a
OpInterface. Use this with infer type op interface to verify that the
inferred type matches the return type and remove special case in
TestPatterns.
This could also have been achieved by using OpInterfaceMethod but verify
seems pretty common and it is not an arbitrary method that just happened
to be named verifyTrait, so having it be defined in special way seems
appropriate/better documenting.
Differential Revision: https://reviews.llvm.org/D73122
Summary:
If an intrinsic has overloadable types like llvm_anyint_ty or
llvm_anyfloat_ty then to getDeclaration() we need to pass a list
of the types that are "undefined" essentially concretizing them.
This patch add support for deriving such types from the MLIR op
that has been matched.
Reviewers: andydavis1, ftynse, nicolasvasilache, antiagainst
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, arpith-jacob, mgester, lucyrfox, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72974
For the generated builder taking in unwrapped attribute values,
if the argument is a string, we should avoid wrapping it in quotes;
otherwise we are always setting the string attribute to contain
the string argument's name. The quotes come from StrinAttr's
`constBuilderCall`, which is reasonable for string literals, but
not function arguments containing strings.
Differential Revision: https://reviews.llvm.org/D72977
Introduce a new generator for MLIR tablegen driver that consumes LLVM IR
intrinsic definitions and produces MLIR ODS definitions. This is useful to
bulk-generate MLIR operations equivalent to existing LLVM IR intrinsics, such
as additional arithmetic instructions or NVVM.
A test exercising the generation is also added. It reads the main LLVM
intrinsics file and produces ODS to make sure the TableGen model remains in
sync with what is used in LLVM.
Differential Revision: https://reviews.llvm.org/D72926
Summary:
* Add shaped container type interface which allows infering the shape, element
type and attribute of shaped container type separately. Show usage by way of
tensor type inference trait which combines the shape & element type in
infering a tensor type;
- All components need not be specified;
- Attribute is added to allow for layout attribute that was previously
discussed;
* Expand the test driver to make it easier to test new creation instances
(adding new operands or ops with attributes or regions would trigger build
functions/type inference methods);
- The verification part will be moved out of the test and to verify method
instead of ops implementing the type inference interface in a follow up;
* Add MLIRContext as arg to possible to create type for ops without arguments,
region or location;
* Also move out the section in OpDefinitions doc to separate ShapeInference doc
where the shape function requirements can be captured;
- Part of this would move to the shape dialect and/or shape dialect ops be
included as subsection of this doc;
* Update ODS's variable usage to match camelBack format for builder,
state and arg variables;
- I could have split this out, but I had to make some changes around
these and the inconsistency bugged me :)
Differential Revision: https://reviews.llvm.org/D72432
This is an initial step to refactoring the representation of OpResult as proposed in: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ
This change will make it much simpler to incrementally transition all of the existing code to use value-typed semantics.
PiperOrigin-RevId: 286844725
Concatting lists in TableGen is easy, creating unique lists less so. There is no reason for duplicated op traits so we could throw an error instead but duplicates could occur due to concatting different list of traits in ODS (e.g., for convenience reasons), so just dedup them during Operator trait construction instead.
PiperOrigin-RevId: 286488423
Introduce affine.prefetch: op to prefetch using a multi-dimensional
subscript on a memref; similar to affine.load but has no effect on
semantics, but only on performance.
Provide lowering through std.prefetch, llvm.prefetch and map to llvm's
prefetch instrinsic. All attributes reflected through the lowering -
locality hint, rw, and instr/data cache.
affine.prefetch %0[%i, %j + 5], false, 3, true : memref<400x400xi32>
Signed-off-by: Uday Bondhugula <uday@polymagelabs.com>
Closestensorflow/mlir#225
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/225 from bondhugula:prefetch 4c3b4e93bc64d9a5719504e6d6e1657818a2ead0
PiperOrigin-RevId: 286212997
This is needed for calling the generator on a .td file that contains both OpInterface definitions and op definitions with DeclareOpInterfaceMethods<...> Traits.
PiperOrigin-RevId: 285465784
This will be evolved into a simple programming model for custom ops and custom layers in followup CLs.
This CL also deletes the obsolete tablegen's reference-impl.td that was using EDSCs.
PiperOrigin-RevId: 285459545
Add variant that does invoke infer type op interface where defined. Also add entry function that invokes that different separate argument builders for wrapped, unwrapped and inference variant.
PiperOrigin-RevId: 285220709
Currently named accessors are generated for attributes returning a consumer
friendly type. But sometimes the attributes are used while transforming an
existing op and then the returned type has to be converted back into an
attribute or the raw `getAttr` needs to be used. Generate raw named accessor
for attributes to reference the raw attributes without having to use the string
interface for better compile time verification. This allows calling
`blahAttr()` instead of `getAttr("blah")`.
Raw here refers to returning the underlying storage attribute.
PiperOrigin-RevId: 284583426
This allows for users to provide operand_range and result_range in builder.create<> calls, instead of requiring an explicit copy into a separate data structure like SmallVector/std::vector.
PiperOrigin-RevId: 284360710
Previously the error case was using a sentinel in the error case which was bad. Also make the one `build` invoke the other `build` to reuse verification there.
And follow up on suggestion to use formatv which I missed during previous review.
PiperOrigin-RevId: 284265762
For ops with infer type op interface defined, generate version that calls the inferal method on build. This is intermediate step to removing special casing of SameOperandsAndResultType & FirstAttrDereivedResultType. After that would be generating the inference code, with the initial focus on shaped container types. In between I plan to refactor these a bit to reuse generated paths. The intention would not be to add the type inference trait in multiple places, but rather to take advantage of the current modelling in ODS where possible to emit it instead.
Switch the `inferReturnTypes` method to be static.
Skipping ops with regions here as I don't like the Region vs unique_ptr<Region> difference at the moment, and I want the infer return type trait to be useful for verification too. So instead, just skip it for now to avoid churn.
PiperOrigin-RevId: 284217913
Existing builders generated by ODS require attributes to be passed
in as mlir::Attribute or its subclasses. This is okay foraggregate-
parameter builders, which is primarily to be used by programmatic
C++ code generation; it is inconvenient for separate-parameter
builders meant to be called in manually written C++ code because
it requires developers to wrap raw values into mlir::Attribute by
themselves.
This CL extends to generate additional builder methods that
take raw values for attributes and handles the wrapping in the
builder implementation. Additionally, if an attribute appears
late in the arguments list and has a default value, the default
value is supplied in the declaration if possible.
PiperOrigin-RevId: 283355919
Right now op argument matching in DRR is position-based, meaning we need to
specify N arguments for an op with N ODS-declared argument. This can be annoying
when we don't want to capture all the arguments. `$_` is to remedy the situation.
PiperOrigin-RevId: 283339992
Support for including a file multiple times was added in tablegen, removing the need for these extra guards. This is because we already insert c/c++ style header guards within each of the specific .td files.
PiperOrigin-RevId: 282076728
This changes changes the OpDefinitionsGen to automatically add the OpAsmOpInterface for operations with multiple result groups using the provided ODS names. We currently just limit the generation to multi-result ops as most single result operations don't have an interesting name(result/output/etc.). An example is shown below:
// The following operation:
def MyOp : ... {
let results = (outs AnyType:$first, Variadic<AnyType>:$middle, AnyType);
}
// May now be printed as:
%first, %middle:2, %0 = "my.op" ...
PiperOrigin-RevId: 281834156
Thus far DRR always invokes the separate-parameter builder (i.e., requiring
a separate parameter for each result-type/operand/attribute) for creating
ops, no matter whether we can auto-generate a builder with type-deduction
ability or not.
This CL changes the path for ops that we can auto-generate type-deduction
builders, i.e., with SameOperandsAndResultType/FirstAttrDerivedResultType
traits. Now they are going through a aggregate-parameter builder (i.e.,
requiring one parameter for all result-types/operands/attributes).
attributes.)
It is expected this approach will be more friendly for future shape inference
function autogen and calling those autogen'd shape inference function without
excessive packing and repacking operand/attribute lists.
Also, it would enable better support for creating ops with optional attributes
because we are not required to provide an Attribute() as placeholder for
an optional attribute anymore.
PiperOrigin-RevId: 280654800
The `Operator` class keeps an `arguments` field, which contains pointers
to `operands` and `attributes` elements. Thus it must be populated after
`operands` and `attributes` are finalized so to have stable pointers.
SmallVector may re-allocate when still having new elements added, which
will invalidate pointers.
PiperOrigin-RevId: 280466896
This change allows for adding additional nested references to a SymbolRefAttr to allow for further resolving a symbol if that symbol also defines a SymbolTable. If a referenced symbol also defines a symbol table, a nested reference can be used to refer to a symbol within that table. Nested references are printed after the main reference in the following form:
symbol-ref-attribute ::= symbol-ref-id (`::` symbol-ref-id)*
Example:
module @reference {
func @nested_reference()
}
my_reference_op @reference::@nested_reference
Given that SymbolRefAttr is now more general, the existing functionality centered around a single reference is moved to a derived class FlatSymbolRefAttr. Followup commits will add support to lookups, rauw, etc. for scoped references.
PiperOrigin-RevId: 279860501
A return type that differs from the inferred return type need not indicate that an operation is invalid (e.g., tensor<*xf32> vs tensor<10xf32>) but they should be compatible for the operation to be considered valid. Add method to query if inferred type is compatible with return type.
Also add InferTypeOpIntefaceDefault trait that considers equality and compatibility as the same. Currently an op has to opt in to using it explicitly.
PiperOrigin-RevId: 279085639
Upstream LLVM gained support for #ifndef with https://reviews.llvm.org/D61888
This is changed mechanically via the following command:
find . -name "*.td" -exec sed -i -e ':a' -e 'N' -e '$!ba' -e 's/#ifdef \([A-Z_]*\)\n#else/#ifndef \1/g' {} \;
PiperOrigin-RevId: 277789427
Lei Zhang