Summary:
This patch adds support for translation of the OpenMP barrier construct to LLVM
IR. The OpenMP IRBuilder is used for this translation. In this patch the code
for translation is added to the existing LLVM dialect translation to LLVM IR.
The patch includes code changes and a testcase.
Reviewers: jdoerfert, nicolasvasilache, ftynse, rriddle, mehdi_amini
Reviewed By: ftynse, rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D72962
Some attribute kinds are not supported as "value" attributes of
`llvm.mlir.constant` when translating to LLVM IR. We were correctly reporting
an error, but continuing the translation using an "undef" value instead,
leading to a surprising mix of error messages and output IR. Abort the
translation after the error is reported.
Differential Revision: https://reviews.llvm.org/D75450
Summary:
This revision adds basic support for emitting line table information when exporting to LLVMIR. We don't yet have a story for supporting all of the LLVM debug metadata, so this revision stubs some features(like subprograms) to enable emitting line tables.
Differential Revision: https://reviews.llvm.org/D73934
Summary:
MLIR materializes various enumeration-based LLVM IR operands as enumeration
attributes using ODS. This requires bidirectional conversion between different
but very similar enums, currently hardcoded. Extend the ODS modeling of
LLVM-specific enumeration attributes to include the name of the corresponding
enum in the LLVM C++ API as well as the names of specific enumerants. Use this
new information to automatically generate the conversion functions between enum
attributes and LLVM API enums in the two-way conversion between the LLVM
dialect and LLVM IR proper.
Differential Revision: https://reviews.llvm.org/D73468
Summary:
This op is the counterpart to LLVM's atomicrmw instruction. Note that
volatile and syncscope attributes are not yet supported.
This will be useful for upcoming parallel versions of `affine.for` and generally
for reduction-like semantics.
Differential Revision: https://reviews.llvm.org/D72741
Summary:
MLIR unlike LLVM IR supports multidimensional vector types. Such types are
lowered to nested LLVM IR arrays wrapping an LLVM IR vector for the innermost
dimension of the MLIR vector. MLIR supports constants of such types using
ElementsAttr for values. Introduce support for converting ElementsAttr into
LLVM IR Constant Aggregates recursively. This enables translation of
multidimensional vector constants from MLIR to LLVM IR.
Differential Revision: https://reviews.llvm.org/D72846
Summary:
When converting splat constants for nested sequential LLVM IR types wrapped in
MLIR, the constant conversion was erroneously assuming it was always possible
to recursively construct a constant of a sequential type given only one value.
Instead, wait until all sequential types are unpacked recursively before
constructing a scalar constant and wrapping it into the surrounding sequential
type.
Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D72688
for (const auto &x : llvm::zip(..., ...))
->
for (auto x : llvm::zip(..., ...))
The return type of zip() is a wrapper that wraps a tuple of references.
> warning: loop variable 'p' is always a copy because the range of type 'detail::zippy<detail::zip_shortest, ArrayRef<long> &, ArrayRef<long> &>' does not return a reference [-Wrange-loop-analysis]
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
This function template has been introduced in the early days of MLIR to work
around the absence of common type for ranges of values (operands, block
argumeents, vectors, etc). Core IR now provides ValueRange for exactly this
purpose. Use it instead of the template parameter.
PiperOrigin-RevId: 286431338
* Fixes use of anonymous namespace for static methods.
* Uses explicit qualifiers(mlir::) instead of wrapping the definition with the namespace.
PiperOrigin-RevId: 286222654
The definition of the function template LLVM::ModuleTranslation::lookupValues
has been located in a source file. As long as it has been the only file that
actually called into the function, this did not cause any problem. However, it
creates linking issues if the function is used from other translation units.
PiperOrigin-RevId: 286203078
LLVM IR supports linkage on global objects such as global variables and
functions. Introduce the Linkage attribute into the LLVM dialect, backed by an
integer storage. Use this attribute on LLVM::GlobalOp and make it mandatory.
Implement parsing/printing of the attribute and conversion to LLVM IR.
See tensorflow/mlir#277.
PiperOrigin-RevId: 283309328
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
This allows GlobalOp to either take a value attribute (for simple constants) or a region that can
contain IR instructions (that must be constant-foldable) to create a ConstantExpr initializer.
Example:
// A complex initializer is constructed with an initializer region.
llvm.mlir.global constant @int_gep() : !llvm<"i32*"> {
%0 = llvm.mlir.addressof @g2 : !llvm<"i32*">
%1 = llvm.mlir.constant(2 : i32) : !llvm.i32
%2 = llvm.getelementptr %0[%1] : (!llvm<"i32*">, !llvm.i32) -> !llvm<"i32*">
llvm.return %2 : !llvm<"i32*">
}
PiperOrigin-RevId: 278717836
Translation to LLVM expects the entry module to have only specific types of ops
that correspond to LLVM IR entities allowed in a module. Currently those are
restricted to functions and globals. Introduce an additional check at the
module level. Inside individual functions, the check for supported Ops is
already performed, but it accepts all LLVM dialect Ops and wouldn't be
immediately applicable at the module level.
PiperOrigin-RevId: 274058651
This function-like operation allows one to define functions that have wrapped
LLVM IR function type, in particular variadic functions. The operation was
added in parallel to the existing lowering flow, this commit only switches the
flow to use it.
Using a custom function type makes the LLVM IR dialect type system more
consistent and avoids complex conversion rules for functions that previously
had to use the built-in function type instead of a wrapped LLVM IR dialect type
and perform conversions during the analysis.
PiperOrigin-RevId: 273910855
Make GlobalOp's value attribute an OptionalAttr. Change code that uses the value to handle 'nullopt'. Translate an unitialized value attribute to llvm::UndefValue.
PiperOrigin-RevId: 270423646
Some of the operations in the LLVM dialect are required to model the LLVM IR in
MLIR, for example "constant" operations are needed to declare a constant value
since MLIR, unlike LLVM, does not support immediate values as operands. To
avoid confusion with actual LLVM operations, we prefix such axuiliary
operations with "mlir.".
PiperOrigin-RevId: 266942838
This will allow iterating the values of a non-opaque ElementsAttr, with all of the types currently supported by DenseElementsAttr. This should help reduce the amount of specialization on DenseElementsAttr.
PiperOrigin-RevId: 264968151
This will allow iterating the values of a non-opaque ElementsAttr, with all of the types currently supported by DenseElementsAttr. This should help reduce the amount of specialization on DenseElementsAttr.
PiperOrigin-RevId: 264637293
Prefer to enumerate all cases in the switch instead of using default to allow
compiler to flag missing cases. This also avoids -Wcovered-switch-default
warning.
PiperOrigin-RevId: 262935972
This instruction is a local counterpart of llvm.global that takes a symbol
reference to a global and produces an SSA value containing the pointer to it.
Used in combination, these two operations allow one to use globals with other
operations expecting SSA values. At a cost of IR indirection, we make sure the
functions don't implicitly capture the surrounding SSA values and remain
suitable for parallel processing.
PiperOrigin-RevId: 262908622
The translation code predates the introduction of LogicalResult and was relying
on the obsolete LLVM convention of returning false on success. Change it to
use MLIR's LogicalResult abstraction instead. NFC.
PiperOrigin-RevId: 262589432
Unlike regular constant values, strings must be placed in some memory and
referred to through a pointer to that memory. Until now, they were not
supported in function-local constant declarations with `llvm.constant`.
Introduce support for global strings using `llvm.global`, which would translate
them into global arrays in LLVM IR and thus make sure they have some memory
allocated for storage.
PiperOrigin-RevId: 262569316
This adds support for fcmp to the LLVM dialect and adds any necessary lowerings, as well as support for EDSCs.
Closestensorflow/mlir#69
PiperOrigin-RevId: 262475255
Due to the absence of ODS support for enum attributes, the implementation of
the LLVM dialect `icmp` operation was reusing the comparison predicate from the
Standard dialect, creating an avoidable library dependency. With ODS support
and ICmpPredicate attribute recently introduced, the dependency is no longer
justified. Update the Standard to LLVM convresion to also convert the
CmpIPredicate into LLVM::ICmpPredicate and remove the unnecessary includes.
Note that the MLIRLLVMIR library did not explicitly depend on MLIRStandardOps,
requiring dependees of MLIRLLVMIR to also depend on MLIRStandardOps, which
should no longer be the case.
PiperOrigin-RevId: 258148456
This allows for the attribute to hold symbolic references to other operations than FuncOp. This also allows for removing the dependence on FuncOp from the base Builder.
PiperOrigin-RevId: 257650017
Modules can now contain more than just Functions, this just updates the iteration API to reflect that. The 'begin'/'end' methods have also been updated to iterate over opaque Operations.
PiperOrigin-RevId: 257099084
As with Functions, Module will soon become an operation, which are value-typed. This eases the transition from Module to ModuleOp. A new class, OwningModuleRef is provided to allow for owning a reference to a Module, and will auto-delete the held module on destruction.
PiperOrigin-RevId: 256196193
Move the data members out of Function and into a new impl storage class 'FunctionStorage'. This allows for Function to become value typed, which will greatly simplify the transition of Function to FuncOp(given that FuncOp is also value typed).
PiperOrigin-RevId: 255983022
This allows for iterating over the internal elements via an iterator_range of Attribute, and also allows for removing the final SmallVectorImpl based 'getValues' method.
PiperOrigin-RevId: 255309555
Now that Locations are attributes, they have direct access to the MLIR context. This allows for simplifying error emission by removing unnecessary context lookups.
PiperOrigin-RevId: 255112791
* There is no longer a need to explicitly remap function attrs.
- This removes a potentially expensive call from the destructor of Function.
- This will enable some interprocedural transformations to now run intraprocedurally.
- This wasn't scalable and forces dialect defined attributes to override
a virtual function.
* Replacing a function is now a trivial operation.
* This is a necessary first step to representing functions as operations.
--
PiperOrigin-RevId: 249510802
This means that we can now do something like:
ctx->getRegisteredDialect<LLVMDialect>();
as opposed to:
static_cast<LLVMDialect *>(ctx->getRegisteredDialect("llvm");
--
PiperOrigin-RevId: 247989896
The Diagnostic class contains all of the information necessary to report a diagnostic to the DiagnosticEngine. It should generally not be constructed directly, and instead used transitively via InFlightDiagnostic. A diagnostic is currently comprised of several different elements:
* A severity level.
* A source Location.
* A list of DiagnosticArguments that help compose and comprise the output message.
* A DiagnosticArgument represents any value that may be part of the diagnostic, e.g. string, integer, Type, Attribute, etc.
* Arguments can be added to the diagnostic via the stream(<<) operator.
* (In a future cl) A list of attached notes.
* These are in the form of other diagnostics that provide supplemental information to the main diagnostic, but do not have context on their own.
The InFlightDiagnostic class represents an RAII wrapper around a Diagnostic that is set to be reported with the diagnostic engine. This allows for the user to modify a diagnostic that is inflight. The internally wrapped diagnostic can be reported directly or automatically upon destruction.
These classes allow for more natural composition of diagnostics by removing the restriction that the message of a diagnostic is comprised of a single Twine. They should also allow for nice incremental improvements to the diagnostics experience in the future, e.g. formatv style diagnostics.
Simple Example:
emitError(loc, "integer bitwidth is limited to " + Twine(IntegerType::kMaxWidth) + " bits");
emitError(loc) << "integer bitwidth is limited to " << IntegerType::kMaxWidth << " bits";
--
PiperOrigin-RevId: 246526439
Kiran Chandramohan