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* Use "final" instead of marking method virtual in override (NFC)Mehdi Amini2019-09-071-1/+1
| | | | | | | | This is the only example for overriding this interface in the repo, let's try to make it right as it may be taken as a reference when implemented in other dialects PiperOrigin-RevId: 267811123
* Add custom builder for AffineIfOpNagy Mostafa2019-09-061-0/+36
| | | | | | | Closes tensorflow/mlir#109 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/109 from nmostafa:nmostafa/AffineIfOp 7dbf2115f0092ffab26381ea8704aa05a0253971 PiperOrigin-RevId: 267633077
* Simplify Linalg ABI integration with external function calls.Nicolas Vasilache2019-09-061-47/+31
| | | | | | | View descriptors are converted to *pointer to* LLVM struct to avoid ABI issues related to C struct packing. This creates unnecessary complexity and hampers unification with memrefs. Instead, this CL makes view descriptors convert to LLVM struct (as it was originally) and promotes all structs to pointers right before calling an external function. PiperOrigin-RevId: 267602693
* Integer set + operands / affine if op canonicalizationUday Bondhugula2019-09-051-0/+22
| | | | | | | | | | | | | | | | | | | | | | - 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/+69
| | | | | | 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/+184
| | | | | | | | | | | | | | | | | | | | 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 Riddle2019-09-056-1/+265
| | | | | | | | | | | | | | | | | | 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
* Make GPU kernel outlining test independent of value names.Stephan Herhut2019-09-051-24/+36
| | | | PiperOrigin-RevId: 267323604
* Generalize I32ElementsAttr definition and introduce I64ElementsAttrSmit Hinsu2019-09-042-1/+18
| | | | | | Also, fix constBuilderCall to return attribute of the storage class DenseIntElementsAttr PiperOrigin-RevId: 267305813
* Retain address space during MLIR > LLVM conversion.MLIR Team2019-09-041-0/+11
| | | | PiperOrigin-RevId: 267206460
* Move LLVMIR dialect tests from test/LLVMIR to test/Dialect and test/ConversionAlex Zinenko2019-09-0410-0/+0
| | | | | | | | | | | This follows up on the recent restructuring that moved the dialects under lib/Dialect and inter-dialect conversions to lib/Conversion. Originally, the tests for both the LLVMIR dialect itself and the conversion from Standard to LLVMIR dialect lived under test/LLVMIR. This no longer reflects the code structure. Move the tests to either test/Dialect/LLVMIR or test/Conversion/StandardToLLVM depending on the features they exercise. PiperOrigin-RevId: 267159219
* pipeline-data-transfer: remove dead tag alloc's and improve test coverage ↵Uday Bondhugula2019-09-041-23/+78
| | | | | | | | | | | | | | | 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
* Move Linalg dialect tests to test/Dialect/LinalgAlex Zinenko2019-09-0410-0/+0
| | | | | | This was missing from the commit that moved the Linalg dialect to lib/Dialect. PiperOrigin-RevId: 267141176
* Make GPU kernel outlining inline constants.Stephan Herhut2019-09-041-0/+20
| | | | | | | 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 Team2019-09-041-2/+8
| | | | PiperOrigin-RevId: 267121729
* Update the syntax of splat attribute in LLVM.mdAlex Zinenko2019-09-041-0/+2
| | | | | | | | | The syntax for splat attributes changed, but was not updated in the description of the LLVM dialect constant operations in LLVM.md. Update the document to use the correct syntax. Also add a dialect roundtrip test for such attribute, which was previously missing. PiperOrigin-RevId: 267116305
* Properly clone Linalg ops with regionsNicolas Vasilache2019-09-032-0/+91
| | | | | | 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 Bondhugula2019-09-031-0/+76
| | | | | | | | | | | | | | | | - 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 Zhang2019-09-032-1/+36
| | | | | | | | | 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 Bondhugula2019-09-031-1/+55
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - 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 Riddle2019-09-031-0/+3
| | | | | | | | The assert assumed that the escaped character could not appear at the end of the string. Fixes tensorflow/mlir#117 PiperOrigin-RevId: 266975471
* LLVM dialect: prefix auxiliary operations with "mlir."Alex Zinenko2019-09-0311-222/+222
| | | | | | | | | | 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
* Add Select operation to SPIR-V dialect.Mahesh Ravishankar2019-09-023-3/+127
| | | | | | 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 Riddle2019-09-021-14/+12
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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 Riddle2019-09-014-1/+40
| | | | | | 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 missing lowering to CFG in mlir-cpu-runner + related cleanupMehdi Amini2019-09-011-2/+11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - 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 Riddle2019-08-302-45/+33
| | | | | | AffineForOp themselves are pure and can be removed if there are no internal operations. PiperOrigin-RevId: 266481293
* Add TensorRankOf for ranked tensor types with specific ranksLogan Chien2019-08-302-9/+53
| | | | | | | | | This commit adds `TensorRankOf<types, typeNames, ranks>` to specify ranked tensor types with the specified types and ranks. For example, `TensorRankOf<[I32, F32], ["i32", "F32"], [0, 1]>` matches `tensor<i32>`, `tensor<?xi32>`, `tensor<f32>`, or `tensor<?xf32>`. PiperOrigin-RevId: 266461256
* Add mechanism to dump JIT-compiled objects to filesJacques Pienaar2019-08-301-0/+9
| | | | | | | | | | | 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
* Add spv.Branch and spv.BranchConditionalLei Zhang2019-08-301-0/+144
| | | | | | | | 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
* Refactor the 'walk' methods for operations.River Riddle2019-08-292-2/+2
| | | | | | | | | | | | 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
* Add tests to verify 0.0 is quantized correctlyFeng Liu2019-08-292-0/+93
| | | | | | We should consider both signed and narrow_range cases. PiperOrigin-RevId: 266167366
* Extend map canonicalization to propagate constant operandsUday Bondhugula2019-08-297-62/+64
| | | | | | | | | | | | | | | | | | | - 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 Bondhugula2019-08-281-48/+56
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - 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/+36
| | | | PiperOrigin-RevId: 266073204
* Tweak to the pretty type parser to recognize that `->` is a special token.Eric Schweitz2019-08-282-0/+5
| | | | | | | | | | | 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 Herhut2019-08-283-1/+56
| | | | | | This change adds definitions, parsing and verification for both ops. PiperOrigin-RevId: 265954051
* Refactor / improve replaceAllMemRefUsesWithUday Bondhugula2019-08-271-4/+33
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
* Update Ch.2 of the Toy tutorial.River Riddle2019-08-271-16/+15
| | | | | | | | The code and documentation for this chapter of the tutorial have been updated to follow the new flow. The toy 'array' type has been replaced by usages of the MLIR tensor type. The code has also been cleaned up and modernized. Closes tensorflow/mlir#101 PiperOrigin-RevId: 265744086
* Add 3 additional intrinsic ops to NVVM dialect, in preparation to implement ↵MLIR Team2019-08-272-24/+68
| | | | | | block-wide reduce. PiperOrigin-RevId: 265720077
* Enhance GPU To SPIR-V conversion to support builtins and load/store ops.Mahesh Ravishankar2019-08-272-0/+165
| | | | | | | | | | | | | | | | | 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
* NFC: Remove the explicit context from Operation::create and OperationState.River Riddle2019-08-261-2/+3
| | | | | | The context can easily be recovered from the Location in these situations. PiperOrigin-RevId: 265578574
* Add FPToSI/FPExt/FPTrunc cast ops to the LLVM dialect.Eric Schweitz2019-08-261-0/+10
| | | | | | Closes tensorflow/mlir#99 PiperOrigin-RevId: 265538731
* Support folding of ops with inner ops in GreedyPatternRewriteDriver.Andy Ly2019-08-263-8/+46
| | | | | | This fixes a bug when folding ops with inner ops and inner ops are still being visited. PiperOrigin-RevId: 265475780
* Lower linalg.copy to LLVM dialect in the presence of transposes.Nicolas Vasilache2019-08-231-0/+30
| | | | | | | | | | Add an extra RewritePattern that does not convert types to rewrite a CopyOp that has non-identity permutations into a sequence of TransposeOp followed by a CopyOp without such permutations. This RewitePattern is made to fail in the non-permutation case so that the conversion pattern can kick in to lower to LLVM. This is an instance of A->A->B lowering where A->A is done by a RewritePattern in case_1 and A->B is done by a ConversionPatternRewriter when not(case_1). PiperOrigin-RevId: 265171380
* Lower linalg.transpose to LLVM dialectNicolas Vasilache2019-08-231-0/+16
| | | | | | | | | | | | Add a conversion pattern that transforms a linalg.transpose op into: 1. A function entry `alloca` operation to allocate a ViewDescriptor. 2. A load of the ViewDescriptor from the pointer allocated in 1. 3. Updates to the ViewDescriptor to introduce the data ptr, offset, size and stride. Size and stride are permutations of the original values. 4. A store of the resulting ViewDescriptor to the alloca'ed pointer. The linalg.transpose op is replaced by the alloca'ed pointer. PiperOrigin-RevId: 265169112
* Add a linalg.transpose opNicolas Vasilache2019-08-232-2/+23
| | | | | | | | | | | | | | A linalg.transpose op is a pure metadata operation that takes a view + permutation map and produces another view of the same underlying data, with a different reindexing. This is a pure metadata operation that does not touch the underlying data. Example: ``` %t = linalg.transpose %v (i, j) -> (j, i) : !linalg.view<?x?xf32> ``` PiperOrigin-RevId: 265139429
* Add lowering of linalg.copy to an external C++ library and a test.Nicolas Vasilache2019-08-233-0/+40
| | | | | | This CL extends support for lowering of linalg to external C++ libraries with CopyOp. Currently this can only work when the permutation maps in the copies are identity. Future support for permutations will be added later. PiperOrigin-RevId: 265093025
* [spirv] NFC: move SPIR-V control flow ops to a separate fileLei Zhang2019-08-232-56/+56
| | | | | | This CL is also purely moving code around for better file organization. PiperOrigin-RevId: 265092566
* Introduce the ability for "isolated from above" ops to introduce shadowingChris Lattner2019-08-233-4/+24
| | | | | | names for the basic block arguments in their body. PiperOrigin-RevId: 265084627
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