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Sep 14, 2023
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[mlir][sparse] Migrate more tests to new syntax #66309

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2 changes: 1 addition & 1 deletion mlir/test/Dialect/Bufferization/ops.mlir
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Expand Up @@ -2,7 +2,7 @@
// RUN: mlir-opt %s --mlir-print-op-generic | mlir-opt | FileCheck %s

#CSR = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"]
map = (d0, d1) -> (d0 : dense, d1 : compressed)
}>

// CHECK-LABEL: func @test_clone
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/Linalg/drop-unit-extent-dims.mlir
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Expand Up @@ -854,7 +854,7 @@ func.func @input_stays_same(%arg0 : memref<?x1x?xf32, strided<[?, 1, 1]>>, %arg1
iterator_types = ["parallel", "reduction"]
}

#CSR = #sparse_tensor.encoding<{ lvlTypes = ["dense", "compressed"] }>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>

func.func @sparse_case(%arg0: tensor<8x8xf32, #CSR>, %arg1: tensor<8xf32>) -> tensor<8xf32> {
%0 = tensor.empty() : tensor<8xf32>
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/GPU/gpu_combi.mlir
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Expand Up @@ -3,7 +3,7 @@
// RUN: --sparsification="parallelization-strategy=dense-outer-loop" \
// RUN: --sparse-gpu-codegen | FileCheck %s

#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>

//
// CHECK-LABEL: gpu.module @sparse_kernels
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2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/GPU/gpu_matmul.mlir
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Expand Up @@ -3,7 +3,7 @@
// RUN: --sparsification="parallelization-strategy=dense-outer-loop" \
// RUN: --sparse-gpu-codegen | FileCheck %s

#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>

//
// Compute matrix matrix C = AB
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2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib.mlir
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@@ -1,7 +1,7 @@
// RUN: mlir-opt %s --linalg-generalize-named-ops \
// RUN: --sparsification="enable-gpu-libgen" | FileCheck %s

#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>

//
// Compute matrix matrix C = AB
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2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/GPU/gpu_matvec.mlir
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Expand Up @@ -3,7 +3,7 @@
// RUN: --sparsification="parallelization-strategy=dense-outer-loop" \
// RUN: --sparse-gpu-codegen | FileCheck %s

#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>

//
// Compute matrix vector y = Ax
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2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir
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Expand Up @@ -19,7 +19,7 @@
iterator_types = ["parallel", "parallel"]
}

#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>

// CHECK-LABEL: func.func @sparse_sampled_dd(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>>,
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2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/GPU/gpu_spgemm_lib.mlir
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@@ -1,7 +1,7 @@
// RUN: mlir-opt %s --linalg-generalize-named-ops \
// RUN: --sparsification="enable-gpu-libgen" | FileCheck %s

#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>

// CHECK-LABEL: func.func @matmulCSR(
// CHECK-SAME: %[[VAL_0:.*0]]: tensor<8x8xf32, #{{.*}}>,
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5 changes: 2 additions & 3 deletions mlir/test/Dialect/SparseTensor/codegen.mlir
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Expand Up @@ -21,7 +21,7 @@
}>

#CSR = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ],
map = (d0, d1) -> (d0 : dense, d1 : compressed),
crdWidth = 64,
posWidth = 32
}>
Expand All @@ -31,8 +31,7 @@
}>

#CSC = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ],
dimToLvl = affine_map<(i, j) -> (j, i)>
map = (d0, d1) -> (d1 : dense, d0 : compressed)
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And this is where it gets interesting ;-)
Neat!

}>

#DCSR = #sparse_tensor.encoding<{
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2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/codegen_sparse_alloc.mlir
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@@ -1,6 +1,6 @@
// RUN: mlir-opt %s --sparse-tensor-codegen --canonicalize --cse | FileCheck %s

#CSR = #sparse_tensor.encoding<{ lvlTypes = ["dense", "compressed"]}>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
#COO = #sparse_tensor.encoding<{ lvlTypes = ["compressed_nu", "singleton"]}>

// CHECK-LABEL: func.func @sparse_alloc_copy_CSR(
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5 changes: 2 additions & 3 deletions mlir/test/Dialect/SparseTensor/codegen_sparse_dealloc.mlir
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Expand Up @@ -6,10 +6,9 @@
// RUN: --sparse-tensor-codegen=create-sparse-deallocs=true \
// RUN: --canonicalize --cse | FileCheck %s -check-prefix=CHECK-DEALLOC

#CSR = #sparse_tensor.encoding<{ lvlTypes = ["dense", "compressed"]}>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
#CSC = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"],
dimToLvl = affine_map<(i,j) -> (j,i)>
map = (d0, d1) -> (d1 : dense, d0 : compressed),
}>

//
Expand Down
5 changes: 2 additions & 3 deletions mlir/test/Dialect/SparseTensor/conversion.mlir
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Expand Up @@ -17,12 +17,11 @@
}>

#CSR = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"]
map = (d0, d1) -> (d0 : dense, d1 : compressed)
}>

#CSC = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"],
dimToLvl = affine_map<(i,j) -> (j,i)>
map = (d0, d1) -> (d1 : dense, d0 : compressed)
}>

#SparseTensor = #sparse_tensor.encoding<{
Expand Down
5 changes: 2 additions & 3 deletions mlir/test/Dialect/SparseTensor/convert_dense2sparse.mlir
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Expand Up @@ -7,12 +7,11 @@
}>

#CSR = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"]
map = (d0, d1) -> (d0 : dense, d1 : compressed)
}>

#CSC = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ],
dimToLvl = affine_map<(i, j) -> (j, i)>
map = (d0, d1) -> (d1 : dense, d0 : compressed)
}>

#SparseTensor = #sparse_tensor.encoding<{
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/convert_sparse2dense.mlir
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Expand Up @@ -8,7 +8,7 @@
}>

#SparseMatrix = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"]
map = (d0, d1) -> (d0 : dense, d1 : compressed)
}>

#SparseTensor = #sparse_tensor.encoding<{
Expand Down
24 changes: 12 additions & 12 deletions mlir/test/Dialect/SparseTensor/invalid.mlir
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Expand Up @@ -44,7 +44,7 @@ func.func @invalid_pack_type(%values: tensor<6xf64>, %pos: tensor<2xi32>, %coord

// -----

#CSR = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"], posWidth=32, crdWidth=32}>
#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed), posWidth=32, crdWidth=32}>

func.func @invalid_pack_mis_position(%values: tensor<6xf64>, %coordinates: tensor<6xi32>)
-> tensor<2x100xf64, #CSR> {
Expand Down Expand Up @@ -80,7 +80,7 @@ func.func @invalid_unpack_type(%sp: tensor<100x2xf64, #SparseVector>, %values: t

// -----

#CSR = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"], posWidth=32, crdWidth=32}>
#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed), posWidth=32, crdWidth=32}>

func.func @invalid_unpack_mis_position(%sp: tensor<2x100xf64, #CSR>, %values: tensor<6xf64>, %coordinates: tensor<6xi32>) {
// expected-error@+1 {{inconsistent number of fields between input/output}}
Expand Down Expand Up @@ -297,7 +297,7 @@ func.func @sparse_unannotated_insert(%arg0: tensor<128xf64>, %arg1: index, %arg2

// -----

#CSR = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>

func.func @sparse_wrong_arity_insert(%arg0: tensor<128x64xf64, #CSR>, %arg1: index, %arg2: f64) {
// expected-error@+1 {{'sparse_tensor.insert' op incorrect number of coordinates}}
Expand Down Expand Up @@ -347,7 +347,7 @@ func.func @sparse_unannotated_compression(%arg0: memref<?xf64>,

// -----

#CSR = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>

func.func @sparse_wrong_arity_compression(%arg0: memref<?xf64>,
%arg1: memref<?xi1>,
Expand Down Expand Up @@ -381,7 +381,7 @@ func.func @sparse_convert_rank_mismatch(%arg0: tensor<10x10xf64, #DCSR>) -> tens

// -----

#CSR = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>

func.func @sparse_convert_dim_mismatch(%arg0: tensor<10x?xf32>) -> tensor<10x10xf32, #CSR> {
// expected-error@+1 {{unexpected conversion mismatch in dimension 1}}
Expand Down Expand Up @@ -632,7 +632,7 @@ func.func @invalid_select_wrong_yield(%arg0: f64) -> f64 {

// -----

#DC = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#DC = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
func.func @invalid_concat_less_inputs(%arg: tensor<9x4xf64, #DC>) -> tensor<9x4xf64, #DC> {
// expected-error@+1 {{Need at least two tensors to concatenate.}}
%0 = sparse_tensor.concatenate %arg {dimension = 1 : index}
Expand All @@ -642,7 +642,7 @@ func.func @invalid_concat_less_inputs(%arg: tensor<9x4xf64, #DC>) -> tensor<9x4x

// -----

#DC = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#DC = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
func.func @invalid_concat_dim(%arg0: tensor<2x4xf64, #DC>,
%arg1: tensor<3x4xf64, #DC>,
%arg2: tensor<4x4xf64, #DC>) -> tensor<9x4xf64, #DC> {
Expand All @@ -657,7 +657,7 @@ func.func @invalid_concat_dim(%arg0: tensor<2x4xf64, #DC>,
// -----

#C = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed)}>
#DC = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#DC = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
#DCC = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed", "compressed"]}>
func.func @invalid_concat_rank_mismatch(%arg0: tensor<2xf64, #C>,
%arg1: tensor<3x4xf64, #DC>,
Expand All @@ -672,7 +672,7 @@ func.func @invalid_concat_rank_mismatch(%arg0: tensor<2xf64, #C>,

// -----

#DC = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#DC = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
func.func @invalid_concat_size_mismatch_dyn(%arg0: tensor<?x4xf64, #DC>,
%arg1: tensor<5x4xf64, #DC>,
%arg2: tensor<4x4xf64, #DC>) -> tensor<9x4xf64, #DC> {
Expand All @@ -686,7 +686,7 @@ func.func @invalid_concat_size_mismatch_dyn(%arg0: tensor<?x4xf64, #DC>,

// -----

#DC = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#DC = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
func.func @invalid_concat_size_mismatch(%arg0: tensor<3x4xf64, #DC>,
%arg1: tensor<5x4xf64, #DC>,
%arg2: tensor<4x4xf64, #DC>) -> tensor<9x4xf64, #DC> {
Expand All @@ -700,7 +700,7 @@ func.func @invalid_concat_size_mismatch(%arg0: tensor<3x4xf64, #DC>,

// -----

#DC = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#DC = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
func.func @invalid_concat_size_mismatch(%arg0: tensor<2x4xf64, #DC>,
%arg1: tensor<3x3xf64, #DC>,
%arg2: tensor<4x4xf64, #DC>) -> tensor<9x4xf64, #DC> {
Expand Down Expand Up @@ -844,7 +844,7 @@ func.func @sparse_sort_coo_y_too_small(%arg0: memref<60xindex>, %arg1: memref<10

// -----

#CSR = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>

func.func @sparse_alloc_escapes(%arg0: index) -> tensor<10x?xf64, #CSR> {
// expected-error@+1 {{sparse tensor allocation should not escape function}}
Expand Down
8 changes: 4 additions & 4 deletions mlir/test/Dialect/SparseTensor/invalid_encoding.mlir
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Expand Up @@ -7,13 +7,13 @@ func.func private @scalar(%arg0: tensor<f64, #a>) -> ()
// -----

// expected-error@+2 {{dimension-rank mismatch between encoding and tensor shape: 2 != 1}}
#a = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"]}>
#a = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
func.func private @tensor_dimlevel_size_mismatch(%arg0: tensor<8xi32, #a>) -> ()

// -----

// expected-error@+1 {{level-rank mismatch between dimToLvl and lvlTypes: 1 != 2}}
#a = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"], dimToLvl = affine_map<(i) -> (i)>}>
// expected-error@+1 {{use of undeclared identifier}}
#a = #sparse_tensor.encoding<{map = (d0) -> (d0 : dense, d1 : compressed)}>
func.func private @tensor_sizes_mismatch(%arg0: tensor<8xi32, #a>) -> ()

// -----
Expand All @@ -34,7 +34,7 @@ func.func private @tensor_dimtolvl_mismatch(%arg0: tensor<8xi32, #a>) -> ()
// -----

// expected-error@+1 {{expected a permutation affine map for dimToLvl}}
#a = #sparse_tensor.encoding<{lvlTypes = ["dense", "compressed"], dimToLvl = affine_map<(i,j) -> (i,i)>}>
#a = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d0 : compressed)}>
func.func private @tensor_no_permutation(%arg0: tensor<16x32xf32, #a>) -> ()

// -----
Expand Down
3 changes: 1 addition & 2 deletions mlir/test/Dialect/SparseTensor/pack_copy.mlir
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@@ -1,8 +1,7 @@
// RUN: mlir-opt %s --sparsification-and-bufferization | FileCheck %s

#CSR = #sparse_tensor.encoding<{
lvlTypes = ["dense","compressed"],
dimToLvl = affine_map<(i,j) -> (i,j)>,
map = (d0, d1) -> (d0 : dense, d1 : compressed),
crdWidth = 32,
posWidth = 32
}>
Expand Down
5 changes: 2 additions & 3 deletions mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir
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Expand Up @@ -2,12 +2,11 @@
// RUN: FileCheck %s

#CSR = #sparse_tensor.encoding<{
lvlTypes = ["dense", "compressed"]
map = (d0, d1) -> (d0 : dense, d1 : compressed)
}>

#CSC = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ],
dimToLvl = affine_map<(i, j) -> (j, i)>
map = (d0, d1) -> (d1 : dense, d0 : compressed)
}>

#COO = #sparse_tensor.encoding<{
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/semi_ring.mlir
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@@ -1,6 +1,6 @@
// RUN: mlir-opt %s -sparsification | FileCheck %s

#SM = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
#SM = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>

#trait = {
indexing_maps = [
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/sparse_2d.mlir
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Expand Up @@ -2,7 +2,7 @@
// RUN: mlir-opt %s -sparsification | FileCheck %s

#Tdd = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "dense" ] }>
#Tds = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
#Tds = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
#Tsd = #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "dense" ] }>
#Tss = #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed" ] }>

Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/sparse_affine.mlir
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Expand Up @@ -2,7 +2,7 @@
// RUN: mlir-opt %s -sparsification | FileCheck %s

#SpVec = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>
#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
#Row = #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "dense" ] }>
#EncDenseVec = #sparse_tensor.encoding<{ map = (d0) -> (d0 : dense) }>

Expand Down
5 changes: 2 additions & 3 deletions mlir/test/Dialect/SparseTensor/sparse_expand.mlir
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Expand Up @@ -8,12 +8,11 @@
// RUN: FileCheck %s --check-prefix=CHECK-CONVERT

#CSR = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ]
map = (d0, d1) -> (d0 : dense, d1 : compressed)
}>

#CSC = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ],
dimToLvl = affine_map<(i,j) -> (j,i)>
map = (d0, d1) -> (d1 : dense, d0 : compressed)
}>

#DCSC = #sparse_tensor.encoding<{
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/sparse_extract_slice.mlir
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@@ -1,7 +1,7 @@
// RUN: mlir-opt %s --sparse-tensor-codegen --cse | FileCheck %s

#CSR = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ]
map = (d0, d1) -> (d0 : dense, d1 : compressed)
}>

#CSR_SLICE = #sparse_tensor.encoding<{
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/sparse_lower.mlir
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Expand Up @@ -8,7 +8,7 @@
// RUN: --tensor-bufferize --finalizing-bufferize | \
// RUN: FileCheck %s --check-prefix=CHECK-LIR

#CSR = #sparse_tensor.encoding<{lvlTypes = [ "dense", "compressed" ]}>
#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>

#trait_matvec = {
indexing_maps = [
Expand Down
3 changes: 1 addition & 2 deletions mlir/test/Dialect/SparseTensor/sparse_lower_col.mlir
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Expand Up @@ -9,8 +9,7 @@
// RUN: FileCheck %s --check-prefix=CHECK-LIR

#CSC = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ],
dimToLvl = affine_map<(i,j) -> (j,i)>
map = (d0, d1) -> (d1 : dense, d0 : compressed)
}>

#trait_matvec = {
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/sparse_lower_inplace.mlir
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Expand Up @@ -8,7 +8,7 @@
// RUN: --tensor-bufferize --finalizing-bufferize | \
// RUN: FileCheck %s --check-prefix=CHECK-LIR

#CSR = #sparse_tensor.encoding<{lvlTypes = [ "dense", "compressed" ]}>
#CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>

#trait_matvec = {
indexing_maps = [
Expand Down
3 changes: 1 addition & 2 deletions mlir/test/Dialect/SparseTensor/sparse_matmul_codegen.mlir
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Expand Up @@ -5,8 +5,7 @@
// RUN: --canonicalize --cse | FileCheck %s

#CSR = #sparse_tensor.encoding<{
lvlTypes = [ "dense", "compressed" ],
dimToLvl = affine_map<(i,j) -> (i,j)>
map = (d0, d1) -> (d0 : dense, d1 : compressed)
}>

//
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