summaryrefslogtreecommitdiffstats
path: root/mlir/test/lib
Commit message (Collapse)AuthorAgeFilesLines
* Make helper functions static or move them into anonymous namespaces. NFC.Benjamin Kramer2020-01-141-2/+3
|
* [mlir] NFC: Remove unused variable.River Riddle2020-01-131-1/+1
|
* [mlir] Add support for attaching a visibility to symbols.River Riddle2020-01-131-1/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Summary: The visibility defines the structural reachability of the symbol within the IR. Symbols can define one of three visibilities: * Public The symbol \may be accessed from outside of the visible IR. We cannot assume that we can observe all of the uses of this symbol. * Private The symbol may only be referenced from within the operations in the current symbol table, via SymbolRefAttr. * Nested The symbol may be referenced by operations in symbol tables above the current symbol table, as long as each symbol table parent also defines a non-private symbol. This allows or referencing the symbol from outside of the defining symbol table, while retaining the ability for the compiler to see all uses. These properties help to reason about the properties of a symbol, and will be used in a follow up to implement a dce pass on dead symbols. A few examples of what this would look like in the IR are shown below: module @public_module { // This function can be accessed by 'live.user' func @nested_function() attributes { sym_visibility = "nested" } // This function cannot be accessed outside of 'public_module' func @private_function() attributes { sym_visibility = "private" } } // This function can only be accessed from within this module. func @private_function() attributes { sym_visibility = "private" } // This function may be referenced externally. func @public_function() "live.user"() {uses = [@public_module::@nested_function, @private_function, @public_function]} : () -> () Depends On D72043 Reviewed By: mehdi_amini Differential Revision: https://reviews.llvm.org/D72044
* [mlir] Update the CallGraph for nested symbol references, and simplify ↵River Riddle2020-01-131-7/+4
| | | | | | | | | | | | | CallableOpInterface Summary: This enables tracking calls that cross symbol table boundaries. It also simplifies some of the implementation details of CallableOpInterface, i.e. there can only be one region within the callable operation. Depends On D72042 Reviewed By: jpienaar Differential Revision: https://reviews.llvm.org/D72043
* [mlir] Update the use-list algorithms in SymbolTable to support nested ↵River Riddle2020-01-131-42/+60
| | | | | | | | | | references. Summary: This updates the use list algorithms to support querying from a specific symbol, allowing for the collection and detection of nested references. This works by walking the parent "symbol scopes" and applying the existing algorithm at each level. Reviewed By: jpienaar Differential Revision: https://reviews.llvm.org/D72042
* [mlir] m_Constant()Lorenzo Chelini2020-01-131-0/+3
| | | | | | Summary: Introduce m_Constant() which allows matching a constant operation without forcing the user also to capture the attribute value. Differential Revision: https://reviews.llvm.org/D72397
* [mlir] NFC: Remove Value::operator* and Value::operator-> now that Value is ↵River Riddle2020-01-116-17/+17
| | | | | | | | | | properly value-typed. Summary: These were temporary methods used to simplify the transition. Reviewed By: antiagainst Differential Revision: https://reviews.llvm.org/D72548
* [mlir][GPU] introduce utilities for promotion to workgroup memoryAlex Zinenko2020-01-092-0/+43
| | | | | | | | | | | | | | | | | | | Introduce a set of function that promote a memref argument of a `gpu.func` to workgroup memory using memory attribution. The promotion boils down to additional loops performing the copy from the original argument to the attributed memory in the beginning of the function, and back at the end of the function using all available threads. The loop bounds are specified so as to adapt to any size of the workgroup. These utilities are intended to compose with other existing utilities (loop coalescing and tiling) in cases where the distribution of work across threads is uneven, e.g. copying a 2D memref with only the threads along the "x" dimension. Similarly, specialization of the kernel to specific launch sizes should be implemented as a separate pass combining constant propagation and canonicalization. Introduce a simple attribute-driven pass to test the promotion transformation since we don't have a heuristic at the moment. Differential revision: https://reviews.llvm.org/D71904
* [mlir] Rewrite the internal representation of OpResult to be optimized for ↵River Riddle2020-01-021-1/+1
| | | | | | | | | | | | | | memory. Summary: This changes the implementation of OpResult to have some of the results be represented inline in Value, via a pointer int pair of Operation*+result number, and the rest being trailing objects on the main operation. The full details of the new representation is detailed in the proposal here: https://groups.google.com/a/tensorflow.org/g/mlir/c/XXzzKhqqF_0/m/v6bKb08WCgAJ The only difference between here and the above proposal is that we only steal 2-bits for the Value kind instead of 3. This means that we can only fit 2-results inline instead of 6. This allows for other users to steal the final bit for PointerUnion/etc. If necessary, we can always steal this bit back in the future to save more space if 3-6 results are common enough. Reviewed By: jpienaar Differential Revision: https://reviews.llvm.org/D72020
* [mlir][Linalg] Extend generic ops to allow tensorsNicolas Vasilache2020-01-021-11/+23
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Summary: This diff adds support to allow `linalg.generic` and `linalg.indexed_generic` to take tensor input and output arguments. The subset of output tensor operand types must appear verbatim in the result types after an arrow. The parser, printer and verifier are extended to accomodate this behavior. The Linalg operations now support variadic ranked tensor return values. This extension exhibited issues with the current handling of NativeCall in RewriterGen.cpp. As a consequence, an explicit cast to `SmallVector<Value, 4>` is added in the proper place to support the new behavior (better suggestions are welcome). Relevant cleanups and name uniformization are applied. Relevant invalid and roundtrip test are added. Reviewers: mehdi_amini, rriddle, jpienaar, antiagainst, ftynse Subscribers: burmako, shauheen, llvm-commits Tags: #llvm Differential Revision: https://reviews.llvm.org/D72022
* [mlir][Linalg] NFC - Cleanup Linalg Declarative TransformationsNicolas Vasilache2020-01-021-59/+59
| | | | | | | | | | | | | | | | | | Summary: This is part of an ongoing cleanup and uniformization work. This diff performs 3 types of cleanups: 1. Uniformize transformation names. 2. Replace all pattern operands that need not be captured by `$_` 3. Replace all usage of pattern captured op by the normalized `op` name (instead of positional parameters such as `$0`) Reviewers: ftynse Subscribers: mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, llvm-commits Tags: #llvm Differential Revision: https://reviews.llvm.org/D72081
* Refactor the way that pass options are specified.River Riddle2019-12-232-43/+28
| | | | | | | | | This change refactors pass options to be more similar to how statistics are modeled. More specifically, the options are specified directly on the pass instead of in a separate options class. (Note that the behavior and specification for pass pipelines remains the same.) This brings about several benefits: * The specification of options is much simpler * The round-trip format of a pass can be generated automatically * This gives a somewhat deeper integration with "configuring" a pass, which we could potentially expose to users in the future. PiperOrigin-RevId: 286953824
* NFC: Replace ValuePtr with Value and remove it now that Value is value-typed.River Riddle2019-12-235-24/+23
| | | | | | ValuePtr was a temporary typedef during the transition to a value-typed Value. PiperOrigin-RevId: 286945714
* Adjust License.txt file to use the LLVM licenseMehdi Amini2019-12-2323-299/+92
| | | | PiperOrigin-RevId: 286906740
* NFC: Introduce new ValuePtr/ValueRef typedefs to simplify the transition to ↵River Riddle2019-12-225-23/+24
| | | | | | | | | | Value being value-typed. 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
* Allow dialect to create friendly names for region argumentsFrank Laub2019-12-191-0/+14
| | | | | | | | | This is the block argument equivalent of the existing `getAsmResultNames` hook. Closes tensorflow/mlir#329 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/329 from plaidml:flaub-region-arg-names fc7876f2d1335024e441083cd25263fd6247eb7d PiperOrigin-RevId: 286523299
* Add support for providing a default implementation for an interface method.River Riddle2019-12-181-2/+1
| | | | | | | | | | | | | | | | | | | | This enables providing a default implementation of an interface method. This method is defined on the Trait that is attached to the operation, and thus has all of the same constraints and properties as any other interface method. This allows for interface authors to provide a conservative default implementation for certain methods, without requiring that all users explicitly define it. The default implementation can be specified via the argument directly after the interface method body: StaticInterfaceMethod< /*desc=*/"Returns whether two array of types are compatible result types for an op.", /*retTy=*/"bool", /*methodName=*/"isCompatibleReturnTypes", /*args=*/(ins "ArrayRef<Type>":$lhs, "ArrayRef<Type>":$rhs), /*methodBody=*/[{ return ConcreteOp::isCompatibleReturnTypes(lhs, rhs); }], /*defaultImplementation=*/[{ /// Returns whether two arrays are equal as strongest check for /// compatibility by default. return lhs == rhs; }] PiperOrigin-RevId: 286226054
* [Linalg] Expose subview promotion as a declarative patternJose Ignacio Gomez2019-12-161-1/+7
| | | | | | | | | | | | This PR targest issue tensorflow/mlir#295. It exposes the already existing subiew promotion pass as a declarative pattern Change-Id: If901ebef9fb53fcd0b12ecc536f6b174ce320b92 Closes tensorflow/mlir#315 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/315 from tetuante:issue295 8e5f268b6d85f31015c33505329dbd7a4db97ac5 PiperOrigin-RevId: 285801463
* Try to fold operations in DialectConversion when trying to legalize.River Riddle2019-12-131-1/+2
| | | | | | This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter. PiperOrigin-RevId: 285448440
* Add missing CMake dependency for MLIRTestIR.Mahesh Ravishankar2019-12-111-0/+3
| | | | PiperOrigin-RevId: 285039153
* Continue refactoring StructuredOps utilitiesNicolas Vasilache2019-12-111-3/+4
| | | | | | | This CL adds more common information to StructuredOpsUtils.h The n_view attribute is retired in favor of args_in + args_out but the CL is otherwise NFC. PiperOrigin-RevId: 285000621
* Roll-forward initial liveness analysis including test cases.Alexander Belyaev2019-12-112-0/+43
| | | | | | Fix the usage of the map size when appending to the map with []. PiperOrigin-RevId: 284985916
* Automated rollback of commit 98fbf41044d3364dbaf18db81b9e8d9520d14761Alexander Belyaev2019-12-112-43/+0
| | | | PiperOrigin-RevId: 284979684
* Add initial liveness analysis including test cases.Marcel Koester2019-12-112-0/+43
| | | | | | Closes tensorflow/mlir#255 PiperOrigin-RevId: 284935454
* Add VectorOp transform pattern which splits vector TransferReadOps to target ↵Andy Davis2019-12-101-0/+1
| | | | | | vector unroll size. PiperOrigin-RevId: 284880592
* Fold TestLinalgTilePermutePatterns into TestLinalgTransformPatterns - NFCNicolas Vasilache2019-12-105-130/+27
| | | | | | Centralize all patterns that test Linalg transforms in a single pass. PiperOrigin-RevId: 284835938
* [Linalg] Add a Linalg iterator permutation transformationJose Ignacio Gomez2019-12-101-0/+13
| | | | | | | | | | | | | | | This patch closes issue tensorflow/mlir#272 We add a standalone iterator permutation transformation to Linalg. This transformation composes a permutation map with the maps in the "indexing_maps" attribute. It also permutes "iterator_types" accordingly. Change-Id: I7c1e693b8203aeecc595a7c012e738ca1100c857 Closes tensorflow/mlir#307 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/307 from tetuante:issue272 f7908d58792f4111119721885e247045104f1131 PiperOrigin-RevId: 284824102
* Uniformize Vector transforms as patterns on the model of Linalg - NFCNicolas Vasilache2019-12-104-6/+57
| | | | | | This reorganizes the vector transformations to be more easily testable as patterns and more easily composable into fused passes in the future. PiperOrigin-RevId: 284817474
* Minor spelling tweaksKazuaki Ishizaki2019-12-091-3/+3
| | | | | | Closes tensorflow/mlir#304 PiperOrigin-RevId: 284568358
* [StructuredOps][Linalg] Add a primitive pattern to rewrite the ↵Nicolas Vasilache2019-12-091-0/+7
| | | | | | | | | | | linalg.generic form of matmul to vector form. This CL uses the newly expanded matcher support to easily detect when a linalg.generic has a multiply-accumulate body. A linalg.generic with such a body is rewritten as a vector contraction. This CL additionally limits the rewrite to the case of matrix multiplication on contiguous and statically shaped memrefs for now. Before expanding further, we should harden the infrastructure for expressing custom ops with the structured ops abstraction. PiperOrigin-RevId: 284566659
* Add RegionRange for when need to abstract over different region iterationJacques Pienaar2019-12-091-1/+1
| | | | | | | | | | | | Follows ValueRange in representing a generic abstraction over the different ways to represent a range of Regions. This wrapper is not as ValueRange and only considers the current cases of interest: MutableArrayRef<Region> and ArrayRef<std::unique_ptr<Region>> as occurs during op construction vs op region querying. Note: ArrayRef<std::unique_ptr<Region>> allows for unset regions, so this range returns a pointer to a Region instead of a Region. PiperOrigin-RevId: 284563229
* Post-submit cleanups in RecursiveMatchersNicolas Vasilache2019-12-091-28/+34
| | | | | | | This CL addresses leftover cleanups and adds a test mixing RecursiveMatchers and m_Constant that captures properly. PiperOrigin-RevId: 284551567
* Add a layer of recursive matchers that compose.Nicolas Vasilache2019-12-082-0/+151
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This CL adds support for building matchers recursively. The following matchers are provided: 1. `m_any()` can match any value 2. `m_val(Value *)` binds to a value and must match it 3. `RecursivePatternMatcher<OpType, Matchers...>` n-arity pattern that matches `OpType` and whose operands must be matched exactly by `Matchers...`. This allows building expression templates for patterns, declaratively, in a very natural fashion. For example pattern `p9` defined as follows: ``` auto mul_of_muladd = m_Op<MulFOp>(m_Op<MulFOp>(), m_Op<AddFOp>()); auto mul_of_anyadd = m_Op<MulFOp>(m_any(), m_Op<AddFOp>()); auto p9 = m_Op<MulFOp>(m_Op<MulFOp>( mul_of_muladd, m_Op<MulFOp>()), m_Op<MulFOp>(mul_of_anyadd, mul_of_anyadd)); ``` Successfully matches `%6` in: ``` %0 = addf %a, %b: f32 %1 = addf %a, %c: f32 // matched %2 = addf %c, %b: f32 %3 = mulf %a, %2: f32 // matched %4 = mulf %3, %1: f32 // matched %5 = mulf %4, %4: f32 // matched %6 = mulf %5, %5: f32 // matched ``` Note that 0-ary matchers can be used as leaves in place of n-ary matchers. This alleviates from passing explicit `m_any()` leaves. In the future, we may add extra patterns to specify that operands may be matched in any order. PiperOrigin-RevId: 284469446
* Update the builder API to take ValueRange instead of ArrayRef<Value *>River Riddle2019-12-072-3/+2
| | | | | | 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
* Change inferReturnTypes to return LogicalResult and valuesJacques Pienaar2019-12-062-12/+15
| | | | | | | | 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
* Generate builder for ops that use InferTypeOpInterface trait in ODSJacques Pienaar2019-12-061-4/+15
| | | | | | | | | | 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
* Add include path to the TestDialect to fix broken build.River Riddle2019-12-051-0/+2
| | | | PiperOrigin-RevId: 284067891
* [Linalg] Add permutation information to tilingJose Ignacio Gomez2019-12-054-0/+127
| | | | | | | | | | | This patch closes issue tensorflow/mlir#271. It adds an optional permutation map to declarative tiling transformations. The map is expressed as a list of integers. Closes tensorflow/mlir#288 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/288 from tetuante:issue271 2df2938d6a1f01b3bc404ded08dea2dd1e10b588 PiperOrigin-RevId: 284064151
* Add support for instance specific pass statistics.River Riddle2019-12-051-0/+15
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Statistics are a way to keep track of what the compiler is doing and how effective various optimizations are. It is useful to see what optimizations are contributing to making a particular program run faster. Pass-instance specific statistics take this even further as you can see the effect of placing a particular pass at specific places within the pass pipeline, e.g. they could help answer questions like "what happens if I run CSE again here". Statistics can be added to a pass by simply adding members of type 'Pass::Statistics'. This class takes as a constructor arguments: the parent pass pointer, a name, and a description. Statistics can be dumped by the pass manager in a similar manner to how pass timing information is dumped, i.e. via PassManager::enableStatistics programmatically; or -pass-statistics and -pass-statistics-display via the command line pass manager options. Below is an example: struct MyPass : public OperationPass<MyPass> { Statistic testStat{this, "testStat", "A test statistic"}; void runOnOperation() { ... ++testStat; ... } }; $ mlir-opt -pass-pipeline='func(my-pass,my-pass)' foo.mlir -pass-statistics Pipeline Display: ===-------------------------------------------------------------------------=== ... Pass statistics report ... ===-------------------------------------------------------------------------=== 'func' Pipeline MyPass (S) 15 testStat - A test statistic MyPass (S) 6 testStat - A test statistic List Display: ===-------------------------------------------------------------------------=== ... Pass statistics report ... ===-------------------------------------------------------------------------=== MyPass (S) 21 testStat - A test statistic PiperOrigin-RevId: 284022014
* Move ModuleManager functionality into mlir::SymbolTable.Tres Popp2019-12-052-1/+23
| | | | | | | | | | Note for broken code, the following transformations occurred: ModuleManager::insert(Block::iterator, Operation*) - > SymbolTable::insert(Operation*, Block::iterator) ModuleManager::lookupSymbol -> SymbolTable::lookup ModuleManager::getModule() -> SymbolTable::getOp() ModuleManager::getContext() -> SymbolTable::getOp()->getContext() ModuleManager::* -> SymbolTable::* PiperOrigin-RevId: 283944635
* Refactor dependencies to expose Vector transformations as patterns - NFCNicolas Vasilache2019-12-034-11/+10
| | | | | | | | | This CL refactors some of the MLIR vector dependencies to allow decoupling VectorOps, vector analysis, vector transformations and vector conversions from each other. This makes the system more modular and allows extracting VectorToVector into VectorTransforms that do not depend on vector conversions. This refactoring exhibited a bunch of cyclic library dependencies that have been cleaned up. PiperOrigin-RevId: 283660308
* [DRR] Introduce `$_` to ignore op argument matchLei Zhang2019-12-021-0/+12
| | | | | | | | Right now op argument matching in DRR is position-based, meaning we need to specify N arguments for an op with N ODS-declared argument. This can be annoying when we don't want to capture all the arguments. `$_` is to remedy the situation. PiperOrigin-RevId: 283339992
* Implement Linalg to loops lowering as a patternNicolas Vasilache2019-11-271-0/+7
| | | | | | This CL rewrites the linalg ops to loops transformations as patterns that can be targeted directly from Tablegen. Reliance on OpFolder is removed and to cope with it we introduce local folding patterns that are applied greedily. PiperOrigin-RevId: 282765550
* Add support for AttrSizedOperandSegments/AttrSizedResultSegmentsLei Zhang2019-11-251-0/+24
| | | | | | | | | | | | | | | | | Certain operations can have multiple variadic operands and their size relationship is not always known statically. For such cases, we need a per-op-instance specification to divide the operands into logical groups or segments. This can be modeled by attributes. This CL introduces C++ trait AttrSizedOperandSegments for operands and AttrSizedResultSegments for results. The C++ trait just guarantees such size attribute has the correct type (1D vector) and values (non-negative), etc. It serves as the basis for ODS sugaring that with ODS argument declarations we can further verify the number of elements match the number of ODS-declared operands and we can generate handy getter methods. PiperOrigin-RevId: 282467075
* De-duplicate EnumAttr overrides by defining defaultsLei Zhang2019-11-254-1/+8
| | | | | | | EnumAttr should provide meaningful defaults so concrete instances do not need to duplicate the fields. PiperOrigin-RevId: 282398431
* NFC: Remove unnecessarily guarded tablegen includes.River Riddle2019-11-221-2/+0
| | | | | | 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
* Add support for using the ODS result names as the Asm result names for ↵River Riddle2019-11-212-18/+2
| | | | | | | | | | | | | | | multi-result operations. 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
* Split Linalg declarative patterns from specific test patterns - NFCNicolas Vasilache2019-11-216-0/+149
| | | | | | This will make it easier to scale out test patterns and build specific passes that do not interfere with independent testing. PiperOrigin-RevId: 281736335
* Merge DCE and unreachable block elimination into a new utility ↵River Riddle2019-11-201-0/+4
| | | | | | | | 'simplifyRegions'. This moves the different canonicalizations of regions into one place and invokes them in the fixed-point iteration of the canonicalizer. PiperOrigin-RevId: 281617072
* Implement unrolling of vector ops to finer-grained vector ops as a pattern.Nicolas Vasilache2019-11-203-1/+46
| | | | | | | | | This CL uses the pattern rewrite infrastructure to implement a simple VectorOps -> VectorOps legalization strategy to unroll coarse-grained vector operations into finer grained ones. The transformation is written using local pattern rewrites to allow composition with other rewrites. It proceeds by iteratively introducing fake cast ops and cleaning canonicalizing or lowering them away where appropriate. This is an example of writing transformations as compositions of local pattern rewrites that should enable us to make them significantly more declarative. PiperOrigin-RevId: 281555100
OpenPOWER on IntegriCloud