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* Integer set + operands / affine if op canonicalizationUday Bondhugula2019-09-053-37/+113
| | | | | | | | | | | | | | | | | | | | | | - turn canonicalizeMapAndOperands into a template that works on both sets and maps, and use it to introduce a utility to canonicalize an affine integer set and its operands - add pattern to canonicalize affine if op's. - rename IntegerSet::getNumOperands -> IntegerSet::getNumInputs to be consistent with AffineMap - add missing accessors for IntegerSet Doesn't need extensive testing since canonicalizeSetAndOperands just reuses canonicalizeMapAndOperands' logic, and the latter is tested on affine.apply map + operands; the new method works the same way on an integer set + operands of an affine if op for example. Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Closes tensorflow/mlir#112 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/112 from bondhugula:set-canonicalize eff72f23250b96fa7d9f5caff3877440f5de2cec PiperOrigin-RevId: 267532876
* Add support for conservatively inlining Affine operations.River Riddle2019-09-051-0/+39
| | | | | | This commit defines an initial implementation of the DialectInlinerInterface for the AffineOps dialect. This change allows for affine operations to be inlined into any region that is not an affine region. Inlining into affine regions requires special handling for dimension/symbol identifiers that will be added in followups. PiperOrigin-RevId: 267467078
* [spirv] Add spv.loopLei Zhang2019-09-051-0/+137
| | | | | | | | | | | | | | | | | | | | SPIR-V can explicitly declare structured control-flow constructs using merge instructions. These explicitly declare a header block before the control flow diverges and a merge block where control flow subsequently converges. These blocks delimit constructs that must nest, and can only be entered and exited in structured ways. Instead of having a `spv.LoopMerge` op to directly model loop merge instruction for indicating the merge and continue target, we use regions to delimit the boundary of the loop: the merge target is the next op following the `spv.loop` op and the continue target is the block that has a back-edge pointing to the entry block inside the `spv.loop`'s region. This way it's easier to discover all blocks belonging to a construct and it plays nicer with the MLIR system. Updated the SPIR-V.md doc. PiperOrigin-RevId: 267431010
* Add the initial inlining infrastructure.River Riddle2019-09-055-1/+398
| | | | | | | | | | | | | | | | | | This defines a set of initial utilities for inlining a region(or a FuncOp), and defines a simple inliner pass for testing purposes. A new dialect interface is defined, DialectInlinerInterface, that allows for dialects to override hooks controlling inlining legality. The interface currently provides the following hooks, but these are just premilinary and should be changed/added to/modified as necessary: * isLegalToInline - Determine if a region can be inlined into one of this dialect, *or* if an operation of this dialect can be inlined into a given region. * shouldAnalyzeRecursively - Determine if an operation with regions should be analyzed recursively for legality. This allows for child operations to be closed off from the legality checks for operations like lambdas. * handleTerminator - Process a terminator that has been inlined. This cl adds support for inlining StandardOps, but other dialects will be added in followups as necessary. PiperOrigin-RevId: 267426759
* Use transform function on llvm::Module in the ExecutionEngineNicolas Vasilache2019-09-041-0/+3
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | The refactoring of ExecutionEngine dropped the usage of the irTransform function used to pass -O3 and other options to LLVM. As a consequence, the proper optimizations do not kick in in LLMV-land. This CL makes use of the transform function and allows producing avx512 instructions, on an internal example, when using: `mlir-cpu-runner -dump-object-file=1 -object-filename=foo.o` combined with `objdump -D foo.o`. Assembly produced resembles: ``` 2b2e: 62 72 7d 48 18 04 0e vbroadcastss (%rsi,%rcx,1),%zmm8 2b35: 62 71 7c 48 28 ce vmovaps %zmm6,%zmm9 2b3b: 62 72 3d 48 a8 c9 vfmadd213ps %zmm1,%zmm8,%zmm9 2b41: 62 f1 7c 48 28 cf vmovaps %zmm7,%zmm1 2b47: 62 f2 3d 48 a8 c8 vfmadd213ps %zmm0,%zmm8,%zmm1 2b4d: 62 f2 7d 48 18 44 0e vbroadcastss 0x4(%rsi,%rcx,1),%zmm0 2b54: 01 2b55: 62 71 7c 48 28 c6 vmovaps %zmm6,%zmm8 2b5b: 62 72 7d 48 a8 c3 vfmadd213ps %zmm3,%zmm0,%zmm8 2b61: 62 f1 7c 48 28 df vmovaps %zmm7,%zmm3 2b67: 62 f2 7d 48 a8 da vfmadd213ps %zmm2,%zmm0,%zmm3 2b6d: 62 f2 7d 48 18 44 0e vbroadcastss 0x8(%rsi,%rcx,1),%zmm0 2b74: 02 2b75: 62 f2 7d 48 a8 f5 vfmadd213ps %zmm5,%zmm0,%zmm6 2b7b: 62 f2 7d 48 a8 fc vfmadd213ps %zmm4,%zmm0,%zmm7 ``` etc. Fixes tensorflow/mlir#120 PiperOrigin-RevId: 267281097
* Retain address space during MLIR > LLVM conversion.MLIR Team2019-09-041-12/+9
| | | | PiperOrigin-RevId: 267206460
* Make isIsolatedAbove robuster to invalid IRJacques Pienaar2019-09-041-0/+9
| | | | | | This function is only called from the verifier. PiperOrigin-RevId: 267145495
* pipeline-data-transfer: remove dead tag alloc's and improve test coverage ↵Uday Bondhugula2019-09-043-12/+20
| | | | | | | | | | | | | | | for replaceMemRefUsesWith / pipeline-data-transfer - address remaining comments from PR tensorflow/mlir#87 for better test coverage for pipeline-data-transfer/replaceAllMemRefUsesWith - remove dead tag allocs the same way they are removed for the replaced buffers Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Closes tensorflow/mlir#106 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/106 from bondhugula:followup 9e868666d047e8d43e5f82f43e4093b838c710fa PiperOrigin-RevId: 267144774
* Make GPU kernel outlining inline constants.Stephan Herhut2019-09-041-2/+40
| | | | | | | It is generally beneficial to pass less arguments to a kernel, so cloning constants into the kernel is beneficial. PiperOrigin-RevId: 267139084
* Add support for array-typed constants.MLIR Team2019-09-041-9/+21
| | | | PiperOrigin-RevId: 267121729
* Properly clone Linalg ops with regionsNicolas Vasilache2019-09-032-12/+12
| | | | | | This CL adds support for proper cloning of Linalg ops that have regions (i.e. the generic linalg op). This is used to properly implement tiling and fusion for such ops. Adequate tests are added. PiperOrigin-RevId: 267027176
* Utility to normalize memrefs with non-identity layout mapsUday Bondhugula2019-09-033-9/+159
| | | | | | | | | | | | | | | | - introduce utility to convert memrefs with non-identity layout maps to ones with identity layout maps: convert the type and rewrite/remap all its uses - add this utility to -simplify-affine-structures pass for testing purposes Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Closes tensorflow/mlir#104 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/104 from bondhugula:memref-normalize f2c914aa1890e8860326c9e33f9aa160b3d65e6d PiperOrigin-RevId: 266985317
* Add folding rule and dialect materialization hook for spv.constantLei Zhang2019-09-034-11/+43
| | | | | | | | | This will allow us to use MLIR's folding infrastructure to deduplicate SPIR-V constants. This CL also changed isValidSPIRVType in SPIRVDialect to a static method. PiperOrigin-RevId: 266984403
* Fix affine data copy generation corner cases/bugsUday Bondhugula2019-09-031-79/+110
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - the [begin, end) range identified for copying could end in between the block, which makes hoisting invalid in some cases. Change the range identification to always end with end of block. - add test case to exercise these (with fast mem capacity set to minimal so that single element memref buffers are generated at the innermost loop) - the location of begin/end of the block range for data copying was being confused with the insert points for copy in and copy out code. In cases, where we choose to hoist transfers, these are separate. - when copy loops are single iteration ones, promote their bodies at the end of the pass. - change default fast mem space to 1 (setting it to zero made it generate DMA op's that won't verify in the default case - since the DMA ops have a check for src/dest memref spaces being different). Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Co-Authored-By: Mehdi Amini <joker.eph@gmail.com> Closes tensorflow/mlir#88 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/88 from bondhugula:datacopy 88697267c45e850c3ced87671e16e4a930c02a42 PiperOrigin-RevId: 266980911
* Fix an invalid assert when processing escaped strings.River Riddle2019-09-031-1/+1
| | | | | | | | The assert assumed that the escaped character could not appear at the end of the string. Fixes tensorflow/mlir#117 PiperOrigin-RevId: 266975471
* Remove unused variablesAlex Torres2019-09-031-13/+7
| | | | | | | | | | Remove unused variables and attributes from BaseViewConversionHelper on mlir/lib/Dialect/Linalg/Transforms/LowerToLLVMDialect.cpp Closes tensorflow/mlir#116 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/116 from alexst07:fix-warnings 5f638e4677492cf71a9cc040eeb6b57427d32e06 PiperOrigin-RevId: 266972082
* LLVM dialect: prefix auxiliary operations with "mlir."Alex Zinenko2019-09-032-6/+8
| | | | | | | | | | 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
* Support bf16 in Builder::getZeroAttrSmit Hinsu2019-09-021-3/+2
| | | | PiperOrigin-RevId: 266863802
* Add Select operation to SPIR-V dialect.Mahesh Ravishankar2019-09-021-0/+58
| | | | | | The SelectOp models the semantics of OpSelect from SPIR-V spec. PiperOrigin-RevId: 266849559
* Refactor the pass manager to support operations other than FuncOp/ModuleOp.River Riddle2019-09-026-258/+252
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This change generalizes the structure of the pass manager to allow arbitrary nesting pass managers for other operations, at any level. The only user visible change to existing code is the fact that a PassManager must now provide an MLIRContext on construction. A new class `OpPassManager` has been added that represents a pass manager on a specific operation type. `PassManager` will remain the top-level entry point into the pipeline, with OpPassManagers being nested underneath. OpPassManagers will still be implicitly nested if the operation type on the pass differs from the pass manager. To explicitly build a pipeline, the 'nest' methods on OpPassManager may be used: // Pass manager for the top-level module. PassManager pm(ctx); // Nest a pipeline operating on FuncOp. OpPassManager &fpm = pm.nest<FuncOp>(); fpm.addPass(...); // Nest a pipeline under the FuncOp pipeline that operates on spirv::ModuleOp OpPassManager &spvModulePM = pm.nest<spirv::ModuleOp>(); // Nest a pipeline on FuncOps inside of the spirv::ModuleOp. OpPassManager &spvFuncPM = spvModulePM.nest<FuncOp>(); To help accomplish this a new general OperationPass is added that operates on opaque Operations. This pass can be inserted in a pass manager of any type to operate on any operation opaquely. An example of this opaque OperationPass is a VerifierPass, that simply runs the verifier opaquely on the current operation. /// Pass to verify an operation and signal failure if necessary. class VerifierPass : public OperationPass<VerifierPass> { void runOnOperation() override { Operation *op = getOperation(); if (failed(verify(op))) signalPassFailure(); markAllAnalysesPreserved(); } }; PiperOrigin-RevId: 266840344
* Add a new dialect interface for the OperationFolder `OpFolderDialectInterface`.River Riddle2019-09-015-10/+18
| | | | | | This interface will allow for providing hooks to interrop with operation folding. The first hook, 'shouldMaterializeInto', will allow for controlling which region to insert materialized constants into. The folder will generally materialize constants into the top-level isolated region, this allows for materializing into a lower level ancestor region if it is more profitable/correct. PiperOrigin-RevId: 266702972
* Add a `getUsedValuesDefinedAbove()` overload that takes an `Operation` ↵Mehdi Amini2019-09-011-0/+6
| | | | | | | | | pointer (NFC) This is a convenient utility around the existing `getUsedValuesDefinedAbove()` that take two regions. PiperOrigin-RevId: 266686854
* Add missing lowering to CFG in mlir-cpu-runner + related cleanupMehdi Amini2019-09-013-6/+8
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - the list of passes run by mlir-cpu-runner included -lower-affine and -lower-to-llvm but was missing -lower-to-cfg (because -lower-affine at some point used to lower straight to CFG); add -lower-to-cfg in between. IR with affine ops can now be run by mlir-cpu-runner. - update -lower-to-cfg to be consistent with other passes (create*Pass methods were changed to return unique ptrs, but -lower-to-cfg appears to have been missed). - mlir-cpu-runner was unable to parse custom form of affine op's - fix link options - drop unnecessary run options from test/mlir-cpu-runner/simple.mlir (none of the test cases had loops) - -convert-to-llvmir was changed to -lower-to-llvm at some point, but the create pass method name wasn't updated (this pass converts/lowers to LLVM dialect as opposed to LLVM IR). Fix this. (If we prefer "convert", the cmd-line options could be changed to "-convert-to-llvm/cfg" then.) Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Closes tensorflow/mlir#115 PiperOrigin-RevId: 266666909
* Add a canonicalization to erase empty AffineForOps.River Riddle2019-08-302-7/+16
| | | | | | AffineForOp themselves are pure and can be removed if there are no internal operations. PiperOrigin-RevId: 266481293
* Generalize the pass hierarchy by adding a general OpPass<PassT, OpT>.River Riddle2019-08-302-48/+13
| | | | | | This pass class generalizes the current functionality between FunctionPass and ModulePass, and allows for operating on any operation type. The pass manager currently only supports OpPasses operating on FuncOp and ModuleOp, but this restriction will be relaxed in follow-up changes. A utility class OpPassBase<OpT> allows for generically referring to operation specific passes: e.g. FunctionPassBase == OpPassBase<FuncOp>. PiperOrigin-RevId: 266442239
* Add mechanism to dump JIT-compiled objects to filesJacques Pienaar2019-08-302-9/+47
| | | | | | | | | | | This commit introduces the bits to be able to dump JIT-compile objects to external files by passing an object cache to OrcJit. The new functionality is tested in mlir-cpu-runner under the flag `dump-object-file`. Closes tensorflow/mlir#95 PiperOrigin-RevId: 266439265
* Added a TableGen generator for structured dataRob Suderman2019-08-301-0/+52
| | | | | | Similar to enum, added a generator for structured data. This provide Dictionary that stores a fixed set of values and guarantees the values are valid. It is intended to store a fixed number of values by a given name. PiperOrigin-RevId: 266437460
* Add support for early exit walk methods.River Riddle2019-08-303-30/+46
| | | | | | | | | | | | | | | This is done by providing a walk callback that returns a WalkResult. This result is either `advance` or `interrupt`. `advance` means that the walk should continue, whereas `interrupt` signals that the walk should stop immediately. An example is shown below: auto result = op->walk([](Operation *op) { if (some_invariant) return WalkResult::interrupt(); return WalkResult::advance(); }); if (result.wasInterrupted()) ...; PiperOrigin-RevId: 266436700
* Add spv.Branch and spv.BranchConditionalLei Zhang2019-08-301-0/+115
| | | | | | | | This CL just covers the op definition, its parsing, printing, and verification. (De)serialization is to be implemented in a subsequent CL. PiperOrigin-RevId: 266431077
* Change the parseSource* methods to return OwningModuleRef instead of ModuleOp.River Riddle2019-08-291-7/+10
| | | | | | This avoids potential memory leaks from misuse of the API. PiperOrigin-RevId: 266305750
* Refactor the 'walk' methods for operations.River Riddle2019-08-2918-56/+50
| | | | | | | | | | | | This change refactors and cleans up the implementation of the operation walk methods. After this refactoring is that the explicit template parameter for the operation type is no longer needed for the explicit op walks. For example: op->walk<AffineForOp>([](AffineForOp op) { ... }); is now accomplished via: op->walk([](AffineForOp op) { ... }); PiperOrigin-RevId: 266209552
* Make dumping using generic form more robust when IR ill-formedJacques Pienaar2019-08-291-0/+5
| | | | PiperOrigin-RevId: 266198057
* Add tests to verify 0.0 is quantized correctlyFeng Liu2019-08-291-1/+1
| | | | | | We should consider both signed and narrow_range cases. PiperOrigin-RevId: 266167366
* Extend map canonicalization to propagate constant operandsUday Bondhugula2019-08-291-11/+23
| | | | | | | | | | | | | | | | | | | - extend canonicalizeMapAndOperands to propagate constant operands into the map's expressions (and thus drop those operands). - canonicalizeMapAndOperands previously only dropped duplicate and unused operands; however, operands that were constants were retained. This change makes IR maps/expressions generated by various utilities/passes even simpler; also makes some of the test checks more accurate and simpler -- for eg., 0' instead of symbol(%{{.*}}). Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Closes tensorflow/mlir#107 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/107 from bondhugula:canonicalize-maps c889a51486d14fbf7db489f224f881e7e1ff7d72 PiperOrigin-RevId: 266085289
* fix loop unroll and jam - operand mapping - imperfect nest caseUday Bondhugula2019-08-281-8/+8
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - fix operand mapping while cloning sub-blocks to jam - was incorrect for imperfect nests where def/use was across sub-blocks - strengthen/generalize the first test case to cover the previously missed scenario - clean up the other cases while on this. Previously, unroll-jamming the following nest ``` affine.for %arg0 = 0 to 2048 { %0 = alloc() : memref<512x10xf32> affine.for %arg1 = 0 to 10 { %1 = affine.load %0[%arg0, %arg1] : memref<512x10xf32> } dealloc %0 : memref<512x10xf32> } ``` would yield ``` %0 = alloc() : memref<512x10xf32> %1 = affine.apply #map0(%arg0) %2 = alloc() : memref<512x10xf32> affine.for %arg1 = 0 to 10 { %4 = affine.load %0[%arg0, %arg1] : memref<512x10xf32> %5 = affine.apply #map0(%arg0) %6 = affine.load %0[%5, %arg1] : memref<512x10xf32> } dealloc %0 : memref<512x10xf32> %3 = affine.apply #map0(%arg0) dealloc %0 : memref<512x10xf32> ``` instead of ``` module { affine.for %arg0 = 0 to 2048 step 2 { %0 = alloc() : memref<512x10xf32> %1 = affine.apply #map0(%arg0) %2 = alloc() : memref<512x10xf32> affine.for %arg1 = 0 to 10 { %4 = affine.load %0[%arg0, %arg1] : memref<512x10xf32> %5 = affine.apply #map0(%arg0) %6 = affine.load %2[%5, %arg1] : memref<512x10xf32> } dealloc %0 : memref<512x10xf32> %3 = affine.apply #map0(%arg0) dealloc %2 : memref<512x10xf32> } ``` Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Closes tensorflow/mlir#98 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/98 from bondhugula:ujam ddbc853f69b5608b3e8ff9b5ac1f6a5a0bb315a4 PiperOrigin-RevId: 266073460
* Add verification for dimension attribute on GPUDialect index operations.Stephan Herhut2019-08-281-0/+7
| | | | PiperOrigin-RevId: 266073204
* Fix the equality check of two floating point valuesFeng Liu2019-08-281-3/+5
| | | | PiperOrigin-RevId: 266022088
* Generalize the analysis manager framework to work on any operation at any ↵River Riddle2019-08-282-47/+58
| | | | | | | | nesting. The pass manager is moving towards being able to run on operations at arbitrary nesting. An operation may have both parent and child operations, and the AnalysisManager must be able to handle this generalization. The AnalysisManager class now contains generic 'getCachedParentAnalysis' and 'getChildAnalysis/getCachedChildAnalysis' functions to query analyses on parent/child operations. This removes the hard coded nesting relationship between Module/Function. PiperOrigin-RevId: 266003636
* Tweak to the pretty type parser to recognize that `->` is a special token.Eric Schweitz2019-08-282-0/+13
| | | | | | | | | | | Tweak to the pretty type parser to recognize that `->` is a special token that shouldn't be split into two characters. This change allows dialect types to wrap function types as in `!my.ptr_type<(i32) -> i32>`. Closes tensorflow/mlir#105 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/105 from schweitzpgi:parse-arrow 8b2d768053f419daae5a1a864121a44c4319acbe PiperOrigin-RevId: 265986240
* Add implementation for tensor_load and tensor_store operations.Stephan Herhut2019-08-282-0/+89
| | | | | | This change adds definitions, parsing and verification for both ops. PiperOrigin-RevId: 265954051
* Port mlir-cuda-runner to use dialect conversion framework.Stephan Herhut2019-08-281-66/+98
| | | | | | | | | Instead of lowering the program in two steps (Standard->LLVM followed by GPU->NVVM), leading to invalid IR inbetween, the runner now uses one pattern based rewrite step to go directly from Standard+GPU to LLVM+NVVM. PiperOrigin-RevId: 265861934
* Refactor / improve replaceAllMemRefUsesWithUday Bondhugula2019-08-273-173/+214
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Refactor replaceAllMemRefUsesWith to split it into two methods: the new method does the replacement on a single op, and is used by the existing one. - make the methods return LogicalResult instead of bool - Earlier, when replacement failed (due to non-deferencing uses of the memref), the set of ops that had already been processed would have been replaced leaving the IR in an inconsistent state. Now, a pass is made over all ops to first check for non-deferencing uses, and then replacement is performed. No test cases were affected because all clients of this method were first checking for non-deferencing uses before calling this method (for other reasons). This isn't true for a use case in another upcoming PR (scalar replacement); clients can now bail out with consistent IR on failure of replaceAllMemRefUsesWith. Add test case. - multiple deferencing uses of the same memref in a single op is possible (we have no such use cases/scenarios), and this has always remained unsupported. Add an assertion for this. - minor fix to another test pipeline-data-transfer case. Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Closes tensorflow/mlir#87 PiperOrigin-RevId: 265808183
* Add 3 additional intrinsic ops to NVVM dialect, in preparation to implement ↵MLIR Team2019-08-272-10/+52
| | | | | | block-wide reduce. PiperOrigin-RevId: 265720077
* [spirv] Fix the entry block to start with OpLabelLei Zhang2019-08-272-2/+51
| | | | | | | | Each basic block in SPIR-V must start with an OpLabel instruction. We don't support control flow yet, so this CL just makes sure that the entry block follows this rule and is valid. PiperOrigin-RevId: 265718841
* Enhance GPU To SPIR-V conversion to support builtins and load/store ops.Mahesh Ravishankar2019-08-274-23/+179
| | | | | | | | | | | | | | | | | To support a conversion of a simple load-compute-store kernel from GPU dialect to SPIR-V dialect, the conversion of operations like "gpu.block_dim", "gpu.thread_id" which allow threads to get the launch conversion is needed. In SPIR-V these are specified as global variables with builin attributes. This CL adds support to specify builtin variables in SPIR-V conversion framework. This is used to convert the relevant operations from GPU dialect to SPIR-V dialect. Also add support for conversion of load/store operation in Standard dialect to SPIR-V dialect. To simplify the conversion add a method to build a spv.AccessChain operation that automatically determines the return type based on the base pointer type and the indices provided. PiperOrigin-RevId: 265718525
* [spirv] Add Block decoration for spv.struct.Denis Khalikov2019-08-272-0/+38
| | | | | | | | Add Block decoration for top-level spv.struct. Closes tensorflow/mlir#102 PiperOrigin-RevId: 265716241
* NFC: Remove the explicit context from Operation::create and OperationState.River Riddle2019-08-264-20/+16
| | | | | | The context can easily be recovered from the Location in these situations. PiperOrigin-RevId: 265578574
* NFC: Remove unnecessary context parameters from several Location getters.River Riddle2019-08-262-16/+13
| | | | | | The context can be recovered by other means in these methods and doesn't need to be passed explicitly. PiperOrigin-RevId: 265532956
* Support folding of ops with inner ops in GreedyPatternRewriteDriver.Andy Ly2019-08-261-8/+7
| | | | | | This fixes a bug when folding ops with inner ops and inner ops are still being visited. PiperOrigin-RevId: 265475780
* NFC: Add doc for id-punctAlina Sbirlea2019-08-231-0/+1
| | | | PiperOrigin-RevId: 265190168
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