[mlir][Tensor] NFC: Move concat operation decomposition as a method of the concat operation.

Currently the implementation is within a pattern that cannot be used
without a pattern rewriter. Move the decomposition as a method of the
operation to make it usable outside of pattern rewrites.

Signed-off-by: MaheshRavishankar <[email protected]>

Author: MaheshRavishankar

mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td

@@ -178,6 +178,9 @@ def Tensor_ConcatOp : Tensor_Op<"concat",
     int64_t getRank() {
       return ::llvm::cast<RankedTensorType>(getResult().getType()).getRank();
     }
+
+    // Method to decompose the operation into a sequence of insert_slices.
+    FailureOr<SmallVector<Value>> decomposeOperation(OpBuilder &builder);
   }];
 
   let hasCanonicalizer = 1;

mlir/lib/Dialect/Tensor/IR/TensorOps.cpp

@@ -615,6 +615,51 @@ LogicalResult ConcatOp::verify() {
   return success();
 }
 
+FailureOr<SmallVector<Value>> ConcatOp::decomposeOperation(OpBuilder &builder) {
+  size_t numInputs = getInputs().size();
+  uint64_t concatDim = getDim();
+
+  SmallVector<SmallVector<OpFoldResult>> inputShapes;
+  inputShapes.reserve(numInputs);
+  SmallVector<OpFoldResult> concatOffsets;
+  concatOffsets.reserve(numInputs);
+  SmallVector<OpFoldResult> outputShape;
+
+  AffineExpr addExpr =
+      builder.getAffineSymbolExpr(0) + builder.getAffineSymbolExpr(1);
+  OpFoldResult zero = builder.getIndexAttr(0);
+  Location loc = getLoc();
+  for (auto [index, input] : llvm::enumerate(getInputs())) {
+    SmallVector<OpFoldResult> inputShape =
+        tensor::getMixedSizes(builder, input.getLoc(), input);
+    if (index == 0) {
+      outputShape = inputShape;
+      concatOffsets.push_back(zero);
+    } else {
+      concatOffsets.push_back(outputShape[concatDim]);
+      outputShape[concatDim] = affine::makeComposedFoldedAffineApply(
+          builder, loc, addExpr,
+          {outputShape[concatDim], inputShape[concatDim]});
+    }
+    inputShapes.emplace_back(std::move(inputShape));
+  }
+
+  Value replacement = builder.create<tensor::EmptyOp>(
+      loc, outputShape, getType().getElementType());
+
+  int64_t rank = getType().getRank();
+  OpFoldResult one = builder.getIndexAttr(1);
+  SmallVector<OpFoldResult> strides(rank, one);
+  SmallVector<OpFoldResult> offsets(rank, zero);
+  for (auto [index, input] : llvm::enumerate(getInputs())) {
+    offsets[concatDim] = concatOffsets[index];
+    auto insertSlice = builder.create<tensor::InsertSliceOp>(
+        loc, input, replacement, offsets, inputShapes[index], strides);
+    replacement = insertSlice.getResult();
+  }
+  return SmallVector<Value>{replacement};
+}
+
 LogicalResult
 ConcatOp::reifyResultShapes(OpBuilder &builder,
                             ReifiedRankedShapedTypeDims &reifiedReturnShapes) {

mlir/lib/Dialect/Tensor/Transforms/ConcatOpPatterns.cpp

@@ -33,54 +33,13 @@ struct DecomposeTensorConcatOp : public OpRewritePattern<ConcatOp> {
 
   LogicalResult matchAndRewrite(ConcatOp concatOp,
                                 PatternRewriter &rewriter) const override {
-    Location loc = concatOp.getLoc();
-    FailureOr<Value> dest =
-        tensor::getOrCreateDestination(rewriter, loc, concatOp->getResult(0));
-    if (failed(dest))
-      return failure();
-
-    auto empty = dest->getDefiningOp<tensor::EmptyOp>();
-    if (!empty)
-      return failure();
-
-    int64_t dim = concatOp.getDim();
-    Value dimValue =
-        rewriter.create<arith::ConstantOp>(loc, rewriter.getIndexAttr(dim));
-
-    int64_t rank = concatOp.getResultType().getRank();
-    SmallVector<OpFoldResult> strides(rank, rewriter.getIndexAttr(1));
-    SmallVector<OpFoldResult> offsets(rank, rewriter.getIndexAttr(0));
-
-    // Compute the partial sums for the slice offsets.
-    AffineExpr sum = rewriter.getAffineDimExpr(0);
-    SmallVector<AffineExpr> partialSums = {sum};
-    SmallVector<OpFoldResult> offsetStrides = {rewriter.getIndexAttr(0)};
-    for (auto [idx, input] :
-         llvm::enumerate(concatOp.getInputs().drop_back())) {
-      sum = sum + rewriter.getAffineDimExpr(idx + 1);
-      partialSums.push_back(sum);
-      offsetStrides.push_back(
-          rewriter.createOrFold<tensor::DimOp>(loc, input, dimValue));
+    FailureOr<SmallVector<Value>> decomposed =
+        concatOp.decomposeOperation(rewriter);
+    if (failed(decomposed)) {
+      return rewriter.notifyMatchFailure(
+          concatOp, "failed to get the decomposed insert slices");
     }
-    auto partialSumMap = AffineMap::get(concatOp.getInputs().size(), 0,
-                                        partialSums, rewriter.getContext());
-    SmallVector<OpFoldResult> dimOffsets =
-        affine::makeComposedFoldedMultiResultAffineApply(
-            rewriter, loc, partialSumMap, offsetStrides);
-
-    // Construct the chain of insert_slice ops into the destination.
-    Value result = *dest;
-    for (auto [input, offset] :
-         llvm::zip_equal(concatOp.getInputs(), dimOffsets)) {
-      SmallVector<OpFoldResult> sizes =
-          tensor::getMixedSizes(rewriter, loc, input);
-      offsets[dim] = offset;
-      result = rewriter.createOrFold<tensor::InsertSliceOp>(
-          loc, input, result, offsets, sizes, strides);
-    }
-
-    rewriter.replaceOpWithNewOp<tensor::CastOp>(
-        concatOp, concatOp.getResultType(), result);
+    rewriter.replaceOp(concatOp, decomposed.value()[0]);
     return success();
   }
 };