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[mlir][vector] Support scalable vectors when unrolling vector.bitcast (#94197)
Follow up to #94064.
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@@ -287,6 +287,8 @@ public:
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return getDynamicTileOffsets(linearIndex);
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}
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size_t getRank() const { return tileShape.size(); }
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private:
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/// The sub-shape that divides the larger outer shape (which is provided to
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/// the constructor).
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@@ -388,6 +390,9 @@ public:
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/// Returns the total number of tiles that fit in the larger shape.
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size_t size() const { return params.getMaxLinearIndex(); }
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/// Returns rank of the iterator's shape.
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size_t getRank() const { return params.getRank(); }
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private:
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const ParamsTy params;
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IteratorTy beginValue;
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@@ -56,17 +56,12 @@ public:
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if (!unrollIterator)
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return failure();
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// TODO: Support the scalable vector cases. It is not supported because
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// the final rank could be values other than `targetRank`. It makes creating
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// the result type of new vector.bitcast ops much harder.
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if (resultType.isScalable()) {
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return rewriter.notifyMatchFailure(op,
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"unrolling vector.bitcast on scalable "
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"vectors is not yet implemented");
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}
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ArrayRef<int64_t> shape = resultType.getShape().take_back(targetRank);
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auto bitcastResType = VectorType::get(shape, resultType.getElementType());
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auto unrollRank = unrollIterator->getRank();
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ArrayRef<int64_t> shape = resultType.getShape().drop_front(unrollRank);
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ArrayRef<bool> scalableDims =
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resultType.getScalableDims().drop_front(unrollRank);
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auto bitcastResType =
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VectorType::get(shape, resultType.getElementType(), scalableDims);
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Location loc = op.getLoc();
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Value result = rewriter.create<arith::ConstantOp>(
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@@ -38,7 +38,39 @@ func.func @vector_bitcast_4d_with_scalable_dim(%arg0: vector<1x2x[3]x4xi64>) ->
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return %0 : vector<1x2x[3]x8xi32>
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}
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// CHECK-LABEL: func.func @vector_bitcast_4d_with_scalable_dim
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// CHECK: vector.bitcast {{.+}} : vector<1x2x[3]x4xi64> to vector<1x2x[3]x8xi32>
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// CHECK-SAME: %[[IN:[a-zA-Z0-9]+]]
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// CHECK: %[[INIT:.+]] = arith.constant dense<0> : vector<1x2x[3]x8xi32>
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// CHECK: %[[V1:.+]] = vector.extract %[[IN]][0, 0] : vector<[3]x4xi64> from vector<1x2x[3]x4xi64>
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// CHECK: %[[B1:.+]] = vector.bitcast %[[V1]] : vector<[3]x4xi64> to vector<[3]x8xi32>
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// CHECK: %[[R1:.+]] = vector.insert %[[B1]], %[[INIT]] [0, 0] : vector<[3]x8xi32> into vector<1x2x[3]x8xi32>
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// CHECK: %[[V2:.+]] = vector.extract %[[IN]][0, 1] : vector<[3]x4xi64> from vector<1x2x[3]x4xi64>
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// CHECK: %[[B2:.+]] = vector.bitcast %[[V2]] : vector<[3]x4xi64> to vector<[3]x8xi32>
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// CHECK: %[[R2:.+]] = vector.insert %[[B2]], %[[R1]] [0, 1] : vector<[3]x8xi32> into vector<1x2x[3]x8xi32>
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// CHECK: return %[[R2]] : vector<1x2x[3]x8xi32>
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func.func @vector_bitcast_2d_trailing_scalable_dim(%arg0: vector<2x[2]xi64>) -> vector<2x[4]xi32> {
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%0 = vector.bitcast %arg0 : vector<2x[2]xi64> to vector<2x[4]xi32>
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return %0 : vector<2x[4]xi32>
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}
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// CHECK-LABEL: func.func @vector_bitcast_2d_trailing_scalable_dim
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// CHECK-SAME: %[[IN:[a-zA-Z0-9]+]]
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// CHECK: %[[INIT:.+]] = arith.constant dense<0> : vector<2x[4]xi32>
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// CHECK: %[[V1:.+]] = vector.extract %[[IN]][0] : vector<[2]xi64> from vector<2x[2]xi64>
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// CHECK: %[[B1:.+]] = vector.bitcast %[[V1]] : vector<[2]xi64> to vector<[4]xi32>
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// CHECK: %[[R1:.+]] = vector.insert %[[B1]], %[[INIT]] [0] : vector<[4]xi32> into vector<2x[4]xi32>
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// CHECK: %[[V2:.+]] = vector.extract %[[IN]][1] : vector<[2]xi64> from vector<2x[2]xi64>
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// CHECK: %[[B2:.+]] = vector.bitcast %[[V2]] : vector<[2]xi64> to vector<[4]xi32>
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// CHECK: %[[R2:.+]] = vector.insert %[[B2]], %[[R1]] [1] : vector<[4]xi32> into vector<2x[4]xi32>
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// CHECK: return %[[R2]] : vector<2x[4]xi32>
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func.func @negative_vector_bitcast_2d_leading_scalable_dim(%arg0: vector<[2]x2xi64>) -> vector<[2]x4xi32>
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{
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%0 = vector.bitcast %arg0 : vector<[2]x2xi64> to vector<[2]x4xi32>
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return %0 : vector<[2]x4xi32>
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}
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// CHECK-LABEL: func.func @negative_vector_bitcast_2d_leading_scalable_dim
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// CHECK-NOT: vector.extract
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// CHECK-NOT: vector.insert
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module attributes {transform.with_named_sequence} {
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transform.named_sequence @__transform_main(%module_op: !transform.any_op {transform.readonly}) {
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