// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s --check-prefix=CHECK-HIR
//
// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification --sparse-tensor-conversion --cse | \
// RUN: FileCheck %s --check-prefix=CHECK-MIR
//
// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification --sparse-tensor-conversion --cse \
// RUN: --one-shot-bufferize="copy-before-write bufferize-function-boundaries function-boundary-type-conversion=identity-layout-map" | \
// RUN: FileCheck %s --check-prefix=CHECK-LIR
#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
#trait_matvec = {
indexing_maps = [
affine_map<(i,j) -> (i,j)>, // A
affine_map<(i,j) -> (j)>, // b
affine_map<(i,j) -> (i)> // x (out)
],
iterator_types = ["parallel","reduction"],
doc = "x(i) += A(i,j) * b(j)"
}
// CHECK-HIR-LABEL: func @matvec(
// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse{{[0-9]*}}>
// CHECK-HIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>,
// CHECK-HIR-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-HIR-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-HIR-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-HIR-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-HIR-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}>
// CHECK-HIR-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}>
// CHECK-HIR-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse{{[0-9]*}}>
// CHECK-HIR-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<64xf64>
// CHECK-HIR-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xf64>
// CHECK-HIR: scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
// CHECK-HIR-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_12]]] : memref<?xindex>
// CHECK-HIR-DAG: %[[VAL_14:.*]] = arith.addi %[[VAL_12]], %[[VAL_5]] : index
// CHECK-HIR-DAG: %[[VAL_15:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_14]]] : memref<?xindex>
// CHECK-HIR-DAG: %[[VAL_16:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_12]]] : memref<32xf64>
// CHECK-HIR: %[[VAL_17:.*]] = scf.for %[[VAL_18:.*]] = %[[VAL_13]] to %[[VAL_15]] step %[[VAL_5]] iter_args(%[[VAL_19:.*]] = %[[VAL_16]]) -> (f64) {
// CHECK-HIR: %[[VAL_20:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_18]]] : memref<?xindex>
// CHECK-HIR: %[[VAL_21:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_18]]] : memref<?xf64>
// CHECK-HIR: %[[VAL_22:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<64xf64>
// CHECK-HIR: %[[VAL_23:.*]] = arith.mulf %[[VAL_21]], %[[VAL_22]] : f64
// CHECK-HIR: %[[VAL_24:.*]] = arith.addf %[[VAL_19]], %[[VAL_23]] : f64
// CHECK-HIR: scf.yield %[[VAL_24]] : f64
// CHECK-HIR: }
// CHECK-HIR: memref.store %[[VAL_17]], %[[VAL_11]]{{\[}}%[[VAL_12]]] : memref<32xf64>
// CHECK-HIR: }
// CHECK-HIR: %[[VAL_26:.*]] = bufferization.to_tensor %[[VAL_11]] : memref<32xf64>
// CHECK-HIR: return %[[VAL_26]] : tensor<32xf64>
// CHECK-HIR: }
// CHECK-MIR-LABEL: func @matvec(
// CHECK-MIR-SAME: %[[VAL_0:.*]]: !llvm.ptr,
// CHECK-MIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>,
// CHECK-MIR-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-MIR-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-MIR-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-MIR-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-MIR-DAG: %[[VAL_6:.*]] = call @sparsePositions0(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr, index) -> memref<?xindex>
// CHECK-MIR-DAG: %[[VAL_7:.*]] = call @sparseCoordinates0(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr, index) -> memref<?xindex>
// CHECK-MIR-DAG: %[[VAL_8:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr) -> memref<?xf64>
// CHECK-MIR-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<64xf64>
// CHECK-MIR-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xf64>
// CHECK-MIR: scf.for %[[VAL_14:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
// CHECK-MIR-DAG: %[[VAL_15:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_14]]] : memref<?xindex>
// CHECK-MIR-DAG: %[[VAL_16:.*]] = arith.addi %[[VAL_14]], %[[VAL_5]] : index
// CHECK-MIR-DAG: %[[VAL_17:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_16]]] : memref<?xindex>
// CHECK-MIR-DAG: %[[VAL_18:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_14]]] : memref<32xf64>
// CHECK-MIR: %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_15]] to %[[VAL_17]] step %[[VAL_5]] iter_args(%[[VAL_21:.*]] = %[[VAL_18]]) -> (f64) {
// CHECK-MIR: %[[VAL_22:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_20]]] : memref<?xindex>
// CHECK-MIR: %[[VAL_23:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_20]]] : memref<?xf64>
// CHECK-MIR: %[[VAL_24:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_22]]] : memref<64xf64>
// CHECK-MIR: %[[VAL_25:.*]] = arith.mulf %[[VAL_23]], %[[VAL_24]] : f64
// CHECK-MIR: %[[VAL_26:.*]] = arith.addf %[[VAL_21]], %[[VAL_25]] : f64
// CHECK-MIR: scf.yield %[[VAL_26]] : f64
// CHECK-MIR: }
// CHECK-MIR: memref.store %[[VAL_19]], %[[VAL_11]]{{\[}}%[[VAL_14]]] : memref<32xf64>
// CHECK-MIR: }
// CHECK-MIR: %[[VAL_28:.*]] = bufferization.to_tensor %[[VAL_11]] : memref<32xf64>
// CHECK-MIR: return %[[VAL_28]] : tensor<32xf64>
// CHECK-MIR: }
// CHECK-LIR-LABEL: func @matvec(
// CHECK-LIR-SAME: %[[VAL_0:.*]]: !llvm.ptr,
// CHECK-LIR-SAME: %[[VAL_1:.*]]: memref<64xf64>,
// CHECK-LIR-SAME: %[[VAL_2:.*]]: memref<32xf64>) -> memref<32xf64> {
// CHECK-LIR-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-LIR-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-LIR-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-LIR-DAG: %[[VAL_6:.*]] = call @sparsePositions0(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr, index) -> memref<?xindex>
// CHECK-LIR-DAG: %[[VAL_7:.*]] = call @sparseCoordinates0(%[[VAL_0]], %[[VAL_5]]) : (!llvm.ptr, index) -> memref<?xindex>
// CHECK-LIR-DAG: %[[VAL_8:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr) -> memref<?xf64>
// CHECK-LIR: scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
// CHECK-LIR-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_12]]] : memref<?xindex>
// CHECK-LIR-DAG: %[[VAL_14:.*]] = arith.addi %[[VAL_12]], %[[VAL_5]] : index
// CHECK-LIR-DAG: %[[VAL_15:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_14]]] : memref<?xindex>
// CHECK-LIR-DAG: %[[VAL_16:.*]] = memref.load %[[VAL_2]]{{\[}}%[[VAL_12]]] : memref<32xf64>
// CHECK-LIR: %[[VAL_17:.*]] = scf.for %[[VAL_18:.*]] = %[[VAL_13]] to %[[VAL_15]] step %[[VAL_5]] iter_args(%[[VAL_19:.*]] = %[[VAL_16]]) -> (f64) {
// CHECK-LIR: %[[VAL_20:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_18]]] : memref<?xindex>
// CHECK-LIR: %[[VAL_21:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_18]]] : memref<?xf64>
// CHECK-LIR: %[[VAL_22:.*]] = memref.load %[[VAL_1]]{{\[}}%[[VAL_20]]] : memref<64xf64>
// CHECK-LIR: %[[VAL_23:.*]] = arith.mulf %[[VAL_21]], %[[VAL_22]] : f64
// CHECK-LIR: %[[VAL_24:.*]] = arith.addf %[[VAL_19]], %[[VAL_23]] : f64
// CHECK-LIR: scf.yield %[[VAL_24]] : f64
// CHECK-LIR: }
// CHECK-LIR: memref.store %[[VAL_17]], %[[VAL_2]]{{\[}}%[[VAL_12]]] : memref<32xf64>
// CHECK-LIR: }
// CHECK-LIR: return %[[VAL_2]] : memref<32xf64>
// CHECK-LIR: }
func.func @matvec(%arga: tensor<32x64xf64, #CSR>,
%argb: tensor<64xf64>,
%argx: tensor<32xf64>) -> tensor<32xf64> {
%0 = linalg.generic #trait_matvec
ins(%arga, %argb : tensor<32x64xf64, #CSR>, tensor<64xf64>)
outs(%argx: tensor<32xf64>) {
^bb(%A: f64, %b: f64, %x: f64):
%0 = arith.mulf %A, %b : f64
%1 = arith.addf %x, %0 : f64
linalg.yield %1 : f64
} -> tensor<32xf64>
return %0 : tensor<32xf64>
}
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