From: Stella Stamenova Date: Mon, 7 Nov 2022 17:34:10 +0000 (-0800) Subject: Revert "[mlir][sparse] extend foreach operation to accept reduction arguments." X-Git-Tag: upstream/17.0.6~28310 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=99171078bb9bea3f31be948e124ec945a50e1fe1;p=platform%2Fupstream%2Fllvm.git Revert "[mlir][sparse] extend foreach operation to accept reduction arguments." This reverts commit 53d5d3401120f2aa741a73a5a9ba0ce012ca532c. This is causing a build failure on the windows mlir bot that was previously hidden by another sparse tensor change that caused failures: https://lab.llvm.org/buildbot/#/builders/13/builds/28006 --- diff --git a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td index 52a6aff..5d66744 100644 --- a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td +++ b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td @@ -896,44 +896,21 @@ def SparseTensor_YieldOp : SparseTensor_Op<"yield", [Pure, Terminator]>, def SparseTensor_ForeachOp : SparseTensor_Op<"foreach", [SingleBlockImplicitTerminator<"YieldOp">]>, - Arguments<(ins AnyTensor:$tensor, - Variadic:$initArgs)>, - Results<(outs Variadic:$results)> { + Arguments<(ins AnyTensor:$tensor)>{ let summary = "Iterates over elements in a tensor"; let description = [{ Iterates over stored elements in a tensor (which are typically, but not always, non-zero for sparse tensors) and executes the block. - For an input tensor with rank n, the block must take n + 1 (and additional loop - carried variables as described below) arguments. The first n arguments must be - Index type, together indicating the current coordinates of the element being visited. - The last argument must have the same type as the + For an input tensor with rank n, the block must take n + 1 arguments. The + first n arguments must be Index type, together indicating the current coordinates + of the element being visited. The last argument must have the same type as the tensor's element type, representing the actual value loaded from the input tensor at the given coordinates. - `sparse_tensor.foreach` can also operate on loop-carried variables and returns - the final values after loop termination. The initial values of the variables are - passed as additional SSA operands to the "sparse_tensor.foreach" following the n + 1 - SSA values mentioned above (n coordinate and 1 value). - - The region must terminate with a "sparse_tensor.yield" that passes the current - values of all loop-carried variables to the next iteration, or to the - result, if at the last iteration. The number and static types of loop-carried - variables may not change with iterations. - - For example: - ```mlir - %c0 = arith.constant 0 : i32 - %ret = sparse_tensor.foreach in %0 init(%c0): tensor, i32 -> i32 do { - ^bb0(%arg1: index, %arg2: index, %arg3: i32, %iter: i32): - %sum = arith.add %iter, %arg3 - sparse_tensor.yield %sum - } - ``` - - It is important to note that foreach generated loop iterates over the stored elements - in the storage order. However, no matter what storage order is used, the indices passed - to the block always obey the original dimension order. + Note that foreach generated loop iterates over the stored elements in the storage + order. However, no matter what storage order is used, the indices passed to the block + always obey the original dimension order. For example: ```mlir @@ -941,10 +918,10 @@ def SparseTensor_ForeachOp : SparseTensor_Op<"foreach", dimLevelType = [ "compressed", "compressed" ], dimOrdering = affine_map<(i,j) -> (j,i)> }> - + // foreach on a column-major sparse tensor sparse_tensor.foreach in %0 : tensor<2x3xf64, #COL_MAJOR> do { - ^bb0(%row: index, %col: index, %arg3: f64): + ^bb0(%row: index, %col: index, %arg3: f64): // [%row, %col] -> [0, 0], [1, 0], [2, 0], [0, 1], [1, 1], [2, 1] } @@ -954,25 +931,30 @@ def SparseTensor_ForeachOp : SparseTensor_Op<"foreach", // foreach on a row-major sparse tensor sparse_tensor.foreach in %0 : tensor<2x3xf64, #ROW_MAJOR> do { - ^bb0(%row: index, %col: index, %arg3: f64): + ^bb0(%row: index, %col: index, %arg3: f64): // [%row, %col] -> [0, 0], [0, 1], [1, 0], [1, 1], [2, 0], [2, 1] } ``` + + Example: + + ```mlir + sparse_tensor.foreach in %0 : tensor do { + ^bb0(%arg1: index, %arg2: index, %arg3: f64): + do something... + } + ``` }]; let builders = [ - OpBuilder<(ins "Value":$tensor, - "function_ref")>, - OpBuilder<(ins "Value":$tensor, - "ValueRange":$iterArgs, - "function_ref")> + OpBuilder<( + ins "Value":$tensor, + "function_ref")> ]; - let regions = (region SizedRegion<1>:$region); - let assemblyFormat = "`in` $tensor (`init``(`$initArgs^`)`)? attr-dict" - " `:` type($tensor) (`,` type($initArgs)^)?" - " (`->` type($results)^)? `do` $region"; + let regions = (region AnyRegion:$region); + let assemblyFormat = "`in` $tensor attr-dict `:` type($tensor) `do` $region"; let hasVerifier = 1; } diff --git a/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp b/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp index bfd38e1..b0c88e1 100644 --- a/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp +++ b/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp @@ -581,20 +581,11 @@ LogicalResult CompressOp::verify() { void ForeachOp::build( OpBuilder &builder, OperationState &result, Value tensor, - function_ref - bodyBuilder) { - build(builder, result, tensor, llvm::None, bodyBuilder); -} - -void ForeachOp::build( - OpBuilder &builder, OperationState &result, Value tensor, - ValueRange initArgs, - function_ref - bodyBuilder) { - build(builder, result, initArgs.getTypes(), tensor, initArgs); - // Builds foreach body. + function_ref bodyBuilder) { + build(builder, result, tensor); if (!bodyBuilder) return; + auto rtp = tensor.getType().cast(); int64_t rank = rtp.getRank(); @@ -611,38 +602,23 @@ void ForeachOp::build( auto ®ion = *result.regions.front(); Block *bodyBlock = builder.createBlock(®ion, region.end(), blockArgTypes, blockArgLocs); - bodyBuilder(builder, result.location, - bodyBlock->getArguments().slice(0, rank), - bodyBlock->getArguments()[rank], - bodyBlock->getArguments().drop_front(rank + 1)); + bodyBuilder(builder, result.location, bodyBlock->getArguments()); } LogicalResult ForeachOp::verify() { auto t = getTensor().getType().cast(); auto args = getBody()->getArguments(); - if (static_cast(t.getRank()) + 1 + getInitArgs().size() != - args.size()) + if (static_cast(t.getRank()) + 1 != args.size()) return emitError("Unmatched number of arguments in the block"); - if (getNumResults() != getInitArgs().size()) - return emitError("Mismatch in number of init arguments and results"); - - if (getResultTypes() != getInitArgs().getTypes()) - return emitError("Mismatch in types of init arguments and results"); - - auto yield = cast(getBody()->getTerminator()); - if (yield.getNumOperands() != getNumResults() || - yield.getOperands().getTypes() != getResultTypes()) - return emitError("Mismatch in types of yield values and results"); - for (int64_t i = 0, e = t.getRank(); i < e; i++) if (args[i].getType() != IndexType::get(getContext())) emitError( llvm::formatv("Expecting Index type for argument at index {0}", i)); auto elemTp = t.getElementType(); - auto valueTp = args[t.getRank()].getType(); + auto valueTp = args.back().getType(); if (elemTp != valueTp) emitError(llvm::formatv("Unmatched element type between input tensor and " "block argument, expected:{0}, got: {1}", diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp index 7747fd7..9c002f1 100644 --- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp +++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp @@ -357,9 +357,7 @@ public: auto cooBuffer = rewriter.create(loc, cooTp, dstDynSizes).getResult(); rewriter.create( - loc, srcTensor, llvm::None, - [&](OpBuilder &builder, Location loc, ValueRange args, Value v, - ValueRange reduc) { + loc, srcTensor, [&](OpBuilder &builder, Location loc, ValueRange args) { SmallVector srcIndices; SmallVector dstIndices; for (int64_t i = 0, e = srcTp.getRank(); i < e; i++) { @@ -368,7 +366,7 @@ public: } translateIndicesArray(builder, loc, op.getReassociationIndices(), srcIndices, srcSizes, dstSizes, dstIndices); - builder.create(loc, v, cooBuffer, dstIndices); + builder.create(loc, args.back(), cooBuffer, dstIndices); builder.create(loc); }); @@ -448,9 +446,7 @@ struct ConcatenateRewriter : public OpRewritePattern { // Build a for op for each input tensor to append new values into the // output tensor. rewriter.create( - loc, input, llvm::None, - [&](OpBuilder &builder, Location loc, ValueRange args, Value v, - ValueRange reduc) { + loc, input, [&](OpBuilder &builder, Location loc, ValueRange args) { SmallVector indices; for (int64_t i = 0; i < rank; i++) { uint64_t dim = @@ -461,7 +457,7 @@ struct ConcatenateRewriter : public OpRewritePattern { idx = builder.create(loc, idx, offset); indices.push_back(idx); } - builder.create(loc, v, cooBuffer, indices); + builder.create(loc, args.back(), cooBuffer, indices); builder.create(loc); }); // Accumulates the offset. Note that only static-shaped inputs are allowed @@ -562,13 +558,12 @@ private: sizesForTensor(rewriter, sizes, loc, srcTp, src); Value dst = allocDenseTensor(rewriter, loc, dstTp, sizes); - rewriter.create(loc, src, llvm::None, - [&](OpBuilder &builder, Location loc, - ValueRange args, Value v, ValueRange reduc) { - builder.create(loc, v, dst, - args); - builder.create(loc); - }); + rewriter.create( + loc, src, [&](OpBuilder &builder, Location loc, ValueRange args) { + builder.create(loc, args.back(), dst, + args.drop_back()); + builder.create(loc); + }); rewriter.replaceOpWithNewOp(op, dstTp, dst); return success(); @@ -603,15 +598,13 @@ private: tmpCoo = rewriter.create(loc, srcTp, dynSrcSizes).getResult(); rewriter.create( - loc, src, llvm::None, - [&](OpBuilder &builder, Location loc, ValueRange args, Value v, - ValueRange reduc) { + loc, src, [&](OpBuilder &builder, Location loc, ValueRange args) { SmallVector indices; for (int64_t i = 0, e = srcTp.getRank(); i < e; i++) { uint64_t dim = toStoredDim(encSrc, i); indices.push_back(args[dim]); } - builder.create(loc, v, tmpCoo, indices); + builder.create(loc, args.back(), tmpCoo, indices); builder.create(loc); }); src = tmpCoo; @@ -653,18 +646,16 @@ private: getDynamicSizes(dstTp, srcSizes, dynDstSizes); Value dst = rewriter.create(loc, dstTp, dynDstSizes).getResult(); - rewriter.create(loc, src, llvm::None, - [&](OpBuilder &builder, Location loc, - ValueRange args, Value v, ValueRange reduc) { - SmallVector indices; - for (int64_t i = 0, e = srcTp.getRank(); i < e; - i++) { - uint64_t dim = toStoredDim(encDst, i); - indices.push_back(args[dim]); - } - builder.create(loc, v, dst, indices); - builder.create(loc); - }); + rewriter.create( + loc, src, [&](OpBuilder &builder, Location loc, ValueRange args) { + SmallVector indices; + for (int64_t i = 0, e = srcTp.getRank(); i < e; i++) { + uint64_t dim = toStoredDim(encDst, i); + indices.push_back(args[dim]); + } + builder.create(loc, args.back(), dst, indices); + builder.create(loc); + }); // Release the temporary COO if it is created. if (tmpCoo) @@ -875,14 +866,12 @@ struct OutRewriter : public OpRewritePattern { ModuleOp module = op->getParentOfType(); // For each element in the source tensor, output the element. rewriter.create( - loc, src, llvm::None, - [&](OpBuilder &builder, Location loc, ValueRange args, Value v, - ValueRange reduc) { + loc, src, [&](OpBuilder &builder, Location loc, ValueRange args) { for (uint64_t i = 0; i < rank; i++) { rewriter.create(loc, args[i], indices, constantIndex(builder, loc, i)); } - rewriter.create(loc, v, value); + rewriter.create(loc, args.back(), value); SmallVector operands{writer, rankValue, indices, value}; FlatSymbolRefAttr fn = getFunc(module, outNextFuncName, {}, operands, EmitCInterface::On); diff --git a/mlir/test/Dialect/SparseTensor/invalid.mlir b/mlir/test/Dialect/SparseTensor/invalid.mlir index 02fb97bc..dd27ce3 100644 --- a/mlir/test/Dialect/SparseTensor/invalid.mlir +++ b/mlir/test/Dialect/SparseTensor/invalid.mlir @@ -551,51 +551,6 @@ func.func @sparse_tensor_foreach(%arg0: tensor<2x4xf64, #DCSR>) -> () { // ----- -#DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> -func.func @sparse_tensor_foreach(%arg0: tensor<2x4xf64, #DCSR>) -> () { - // expected-error@+1 {{Unmatched element type between input tensor and block argument}} - sparse_tensor.foreach in %arg0 : tensor<2x4xf64, #DCSR> do { - ^bb0(%1: index, %2: index, %v: f32) : - } - return -} - -// ----- - -#DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> -func.func @sparse_tensor_foreach(%arg0: tensor<2x4xf64, #DCSR>, %arg1: f32) -> () { - // expected-error@+1 {{Mismatch in number of init arguments and results}} - sparse_tensor.foreach in %arg0 init(%arg1) : tensor<2x4xf64, #DCSR>, f32 do { - ^bb0(%1: index, %2: index, %v: f32, %r1 : i32) : - } - return -} - -// ----- - -#DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> -func.func @sparse_tensor_foreach(%arg0: tensor<2x4xf64, #DCSR>, %arg1: f32) -> () { - // expected-error@+1 {{Mismatch in types of init arguments and results}} - %1 = sparse_tensor.foreach in %arg0 init(%arg1) : tensor<2x4xf64, #DCSR>, f32 -> i32 do { - ^bb0(%1: index, %2: index, %v: f32, %r0 : f32) : - } - return -} - -// ----- - -#DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> -func.func @sparse_tensor_foreach(%arg0: tensor<2x4xf64, #DCSR>, %arg1: f32) -> () { - // expected-error@+1 {{Mismatch in types of yield values and results}} - %1 = sparse_tensor.foreach in %arg0 init(%arg1) : tensor<2x4xf64, #DCSR>, f32 -> f32 do { - ^bb0(%1: index, %2: index, %v: f32, %r0 : f32) : - sparse_tensor.yield %1 : index - } - return -} - -// ----- - // TODO: a test case with empty xs doesn't work due to some parser issues. func.func @sparse_sort_x_type( %arg0: index, %arg1: memref) { diff --git a/mlir/test/Dialect/SparseTensor/roundtrip.mlir b/mlir/test/Dialect/SparseTensor/roundtrip.mlir index bc664ae..0ef58db 100644 --- a/mlir/test/Dialect/SparseTensor/roundtrip.mlir +++ b/mlir/test/Dialect/SparseTensor/roundtrip.mlir @@ -411,26 +411,6 @@ func.func @sparse_tensor_foreach(%arg0: tensor<2x4xf64, #DCSR>) -> () { return } -// ----- - -#DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> - -// CHECK-LABEL: func @sparse_tensor_foreach( -// CHECK-SAME: %[[A0:.*]]: tensor<2x4xf64, #sparse_tensor.encoding<{{{.*}}}>>, -// CHECK-SAME: %[[A1:.*]]: f32 -// CHECK-NEXT: %[[RET:.*]] = sparse_tensor.foreach in %[[A0]] init(%[[A1]]) -// CHECK-NEXT: ^bb0(%[[TMP_1:.*]]: index, %[[TMP_2:.*]]: index, %[[TMP_v:.*]]: f64, %[[TMP_r:.*]]: f32) -// CHECK: sparse_tensor.yield %[[TMP_r]] : f32 -// CHECK: } -func.func @sparse_tensor_foreach(%arg0: tensor<2x4xf64, #DCSR>, %arg1: f32) -> () { - %ret = sparse_tensor.foreach in %arg0 init(%arg1): tensor<2x4xf64, #DCSR>, f32 -> f32 - do { - ^bb0(%1: index, %2: index, %v: f64, %r: f32) : - sparse_tensor.yield %r : f32 - } - return -} - // ---- // CHECK-LABEL: func @sparse_sort_1d0v(