// RUN: mlir-opt %s --stage-sparse-ops --lower-sparse-ops-to-foreach --canonicalize --cse | FileCheck %s
#SparseVector64 = #sparse_tensor.encoding<{
map = (d0) -> (d0 : compressed),
posWidth = 64,
crdWidth = 64
}>
#SparseVector32 = #sparse_tensor.encoding<{
map = (d0) -> (d0 : compressed),
posWidth = 32,
crdWidth = 32
}>
#SparseVector = #sparse_tensor.encoding<{
map = (d0) -> (d0 : compressed)
}>
#SortedCOO2D = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton),
}>
#SortedCOO3D = #sparse_tensor.encoding<{
map = (d0, d1, d2) -> (d0 : compressed(nonunique), d1 : singleton(nonunique), d2 : singleton)
}>
#TsssPermuted = #sparse_tensor.encoding<{
map = (d0, d1, d2) -> (d2 : compressed, d0 : compressed, d1 : compressed)
}>
#COOSlice = #sparse_tensor.encoding<{
map = (d0 : #sparse_tensor<slice(2, 2, 1)>, d1 : #sparse_tensor<slice(12, 13, 1)>) -> (d0 : compressed(nonunique), d1 : singleton)
}>
// CHECK-LABEL: func.func @sparse_nop_convert
// CHECK-NEXT: return
func.func @sparse_nop_convert(%arg0: tensor<64xf32, #SparseVector>) -> tensor<64xf32, #SparseVector> {
%0 = sparse_tensor.convert %arg0 : tensor<64xf32, #SparseVector> to tensor<64xf32, #SparseVector>
return %0 : tensor<64xf32, #SparseVector>
}
// CHECK-LABEL: func.func @sparse_hidden_nop_cast
// CHECK-NEXT: sparse_tensor.convert
// CHECK-NEXT: return
func.func @sparse_hidden_nop_cast(%arg0: tensor<32xf32, #SparseVector>) -> tensor<?xf32, #SparseVector> {
%0 = sparse_tensor.convert %arg0 : tensor<32xf32, #SparseVector> to tensor<?xf32, #SparseVector>
return %0 : tensor<?xf32, #SparseVector>
}
// CHECK-LABEL: func.func @sparse_convert_1d_ss(
// CHECK-NEXT: sparse_tensor.convert
// CHECK-NEXT: return
func.func @sparse_convert_1d_ss(%arg0: tensor<?xf32, #SparseVector64>) -> tensor<?xf32, #SparseVector32> {
%0 = sparse_tensor.convert %arg0 : tensor<?xf32, #SparseVector64> to tensor<?xf32, #SparseVector32>
return %0 : tensor<?xf32, #SparseVector32>
}
// CHECK-LABEL: func.func @sparse_convert(
// CHECK-NEXT: sparse_tensor.convert
// CHECK-NEXT: return
func.func @sparse_convert(%arg0: tensor<?xf32, #SparseVector64>) -> tensor<?xf32, #SparseVector32> {
%0 = sparse_tensor.convert %arg0 : tensor<?xf32, #SparseVector64> to tensor<?xf32, #SparseVector32>
return %0 : tensor<?xf32, #SparseVector32>
}
// CHECK-LABEL: func.func @sparse_convert_permuted
// CHECK: sparse_tensor.foreach
// CHECK: tensor.insert
// CHECK: sparse_tensor.load
// CHECK: sparse_tensor.reorder_coo
// CHECK: sparse_tensor.foreach
// CHECK: tensor.insert
// CHECK: sparse_tensor.load
// CHECK: return
func.func @sparse_convert_permuted(%arg0: tensor<?x?x?xf32, #SortedCOO3D>) -> tensor<?x?x?xf32, #TsssPermuted> {
%0 = sparse_tensor.convert %arg0 : tensor<?x?x?xf32, #SortedCOO3D> to tensor<?x?x?xf32, #TsssPermuted>
return %0 : tensor<?x?x?xf32, #TsssPermuted>
}
// CHECK-LABEL: func.func @sparse_convert_slice
// CHECK: sparse_tensor.foreach
// CHECK: tensor.insert
// CHECK: sparse_tensor.load
// CHECK-NOT: sparse_tensor.reorder_coo
// CHECK: return
func.func @sparse_convert_slice(%arg0: tensor<2x13xi32, #COOSlice>) -> (tensor<2x13xi32, #SortedCOO2D>) {
%0 = sparse_tensor.convert %arg0 : tensor<2x13xi32, #COOSlice> to tensor<2x13xi32, #SortedCOO2D>
return %0 : tensor<2x13xi32, #SortedCOO2D>
}