[Mlir-commits] [mlir] c01e622 - [mlir][sparse]Add more test cases for sparse reshape
Anlun Xu
llvmlistbot at llvm.org
Fri Jul 29 16:43:16 PDT 2022
Author: Anlun Xu
Date: 2022-07-29T16:42:48-07:00
New Revision: c01e6221201bb091f913b110132413ad52437e31
URL: https://github.com/llvm/llvm-project/commit/c01e6221201bb091f913b110132413ad52437e31
DIFF: https://github.com/llvm/llvm-project/commit/c01e6221201bb091f913b110132413ad52437e31.diff
LOG: [mlir][sparse]Add more test cases for sparse reshape
Add more test cases for sparse reshape
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D130603
Added:
Modified:
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir
Removed:
################################################################################
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir
index 6e62c4f39da7..2c85f19bdd9a 100755
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir
@@ -11,6 +11,14 @@
dimLevelType = ["compressed", "compressed"]
}>
+#Sparse3dTensor = #sparse_tensor.encoding<{
+ dimLevelType = ["compressed", "compressed", "compressed"]
+}>
+
+#Sparse4dTensor = #sparse_tensor.encoding<{
+ dimLevelType = ["compressed", "compressed", "compressed", "compressed"]
+}>
+
//
// Test with various forms of the two most elementary reshape
// operations: expand/collapse.
@@ -57,6 +65,75 @@ module {
return %0 : tensor<12xf64, #SparseVector>
}
+ func.func @expand_dense_3x2x2(%arg0: tensor<3x4xf64>) -> tensor<3x2x2xf64> {
+ %0 = tensor.expand_shape %arg0 [[0], [1, 2]] : tensor<3x4xf64> into tensor<3x2x2xf64>
+ return %0 : tensor<3x2x2xf64>
+ }
+
+ func.func @expand_from_sparse_3x2x2(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<3x2x2xf64> {
+ %0 = tensor.expand_shape %arg0 [[0], [1, 2]] : tensor<3x4xf64, #SparseMatrix> into tensor<3x2x2xf64>
+ return %0 : tensor<3x2x2xf64>
+ }
+
+ func.func @expand_to_sparse_3x2x2(%arg0: tensor<3x4xf64>) -> tensor<3x2x2xf64, #Sparse3dTensor> {
+ %0 = tensor.expand_shape %arg0 [[0], [1, 2]] : tensor<3x4xf64> into tensor<3x2x2xf64, #Sparse3dTensor>
+ return %0 : tensor<3x2x2xf64, #Sparse3dTensor>
+ }
+
+ func.func @expand_sparse2sparse_3x2x2(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<3x2x2xf64, #Sparse3dTensor> {
+ %0 = tensor.expand_shape %arg0 [[0], [1, 2]] : tensor<3x4xf64, #SparseMatrix> into tensor<3x2x2xf64, #Sparse3dTensor>
+ return %0 : tensor<3x2x2xf64, #Sparse3dTensor>
+ }
+
+ func.func @collapse_dense_6x10(%arg0: tensor<2x3x5x2xf64>) -> tensor<6x10xf64> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : tensor<2x3x5x2xf64> into tensor<6x10xf64>
+ return %0 : tensor<6x10xf64>
+ }
+
+ func.func @collapse_from_sparse_6x10(%arg0: tensor<2x3x5x2xf64, #Sparse4dTensor>) -> tensor<6x10xf64> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : tensor<2x3x5x2xf64, #Sparse4dTensor> into tensor<6x10xf64>
+ return %0 : tensor<6x10xf64>
+ }
+
+ func.func @collapse_to_sparse_6x10(%arg0: tensor<2x3x5x2xf64>) -> tensor<6x10xf64, #SparseMatrix> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : tensor<2x3x5x2xf64> into tensor<6x10xf64, #SparseMatrix>
+ return %0 : tensor<6x10xf64, #SparseMatrix>
+ }
+
+ func.func @collapse_sparse2sparse_6x10(%arg0: tensor<2x3x5x2xf64, #Sparse4dTensor>) -> tensor<6x10xf64, #SparseMatrix> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : tensor<2x3x5x2xf64, #Sparse4dTensor> into tensor<6x10xf64, #SparseMatrix>
+ return %0 : tensor<6x10xf64, #SparseMatrix>
+ }
+
+ func.func @expand_dense_dyn(%arg0: tensor<?x?xf64>) -> tensor<?x2x?xf64> {
+ %0 = tensor.expand_shape %arg0 [[0], [1, 2]] : tensor<?x?xf64> into tensor<?x2x?xf64>
+ return %0 : tensor<?x2x?xf64>
+ }
+
+ func.func @expand_from_sparse_dyn(%arg0: tensor<?x?xf64, #SparseMatrix>) -> tensor<?x2x?xf64> {
+ %0 = tensor.expand_shape %arg0 [[0], [1, 2]] : tensor<?x?xf64, #SparseMatrix> into tensor<?x2x?xf64>
+ return %0 : tensor<?x2x?xf64>
+ }
+
+ func.func @expand_to_sparse_dyn(%arg0: tensor<?x?xf64>) -> tensor<?x2x?xf64, #Sparse3dTensor> {
+ %0 = tensor.expand_shape %arg0 [[0], [1, 2]] : tensor<?x?xf64> into tensor<?x2x?xf64, #Sparse3dTensor>
+ return %0 : tensor<?x2x?xf64, #Sparse3dTensor>
+ }
+
+ func.func @collapse_dense_dyn(%arg0: tensor<?x?x?x?xf64>) -> tensor<?x?xf64> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : tensor<?x?x?x?xf64> into tensor<?x?xf64>
+ return %0 : tensor<?x?xf64>
+ }
+
+ func.func @collapse_from_sparse_dyn(%arg0: tensor<?x?x?x?xf64, #Sparse4dTensor>) -> tensor<?x?xf64> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : tensor<?x?x?x?xf64, #Sparse4dTensor> into tensor<?x?xf64>
+ return %0 : tensor<?x?xf64>
+ }
+
+ func.func @collapse_to_sparse_dyn(%arg0: tensor<?x?x?x?xf64>) -> tensor<?x?xf64, #SparseMatrix> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : tensor<?x?x?x?xf64> into tensor<?x?xf64, #SparseMatrix>
+ return %0 : tensor<?x?xf64, #SparseMatrix>
+ }
//
// Main driver.
@@ -71,33 +148,64 @@ module {
%m = arith.constant dense <[ [ 1.1, 1.2, 1.3, 1.4 ],
[ 2.1, 2.2, 2.3, 2.4 ],
[ 3.1, 3.2, 3.3, 3.4 ]]> : tensor<3x4xf64>
+ %n = arith.constant dense <[
+ [ [[1.0, 2.0], [3.0, 4.0], [5.0, 6.0], [7.0, 8.0], [9.0, 10.0]],
+ [[11.0, 12.0], [13.0, 14.0], [15.0, 16.0], [17.0, 18.0], [19.0, 20.0]],
+ [[21.0, 22.0], [23.0, 24.0], [25.0, 26.0], [27.0, 28.0], [29.0, 30.0]] ],
+ [ [[31.0, 32.0], [33.0, 34.0], [35.0, 36.0], [37.0, 38.0], [39.0, 40.0]],
+ [[41.0, 42.0], [43.0, 44.0], [45.0, 26.0], [47.0, 48.0], [49.0, 50.0]],
+ [[51.0, 52.0], [53.0, 54.0], [55.0, 56.0], [57.0, 58.0], [59.0, 60.0]] ] ]> : tensor<2x3x5x2xf64>
%sv = sparse_tensor.convert %v : tensor<12xf64> to tensor<12xf64, #SparseVector>
%sm = sparse_tensor.convert %m : tensor<3x4xf64> to tensor<3x4xf64, #SparseMatrix>
+ %sn = sparse_tensor.convert %n : tensor<2x3x5x2xf64> to tensor<2x3x5x2xf64, #Sparse4dTensor>
+
+ %dm = tensor.cast %m : tensor<3x4xf64> to tensor<?x?xf64>
+ %sdm = sparse_tensor.convert %dm : tensor<?x?xf64> to tensor<?x?xf64, #SparseMatrix>
+ %dn = tensor.cast %n : tensor<2x3x5x2xf64> to tensor<?x?x?x?xf64>
+ %sdn = sparse_tensor.convert %dn : tensor<?x?x?x?xf64> to tensor<?x?x?x?xf64, #Sparse4dTensor>
// Call the kernels.
%expand0 = call @expand_dense(%v) : (tensor<12xf64>) -> tensor<3x4xf64>
%expand1 = call @expand_from_sparse(%sv) : (tensor<12xf64, #SparseVector>) -> tensor<3x4xf64>
%expand2 = call @expand_to_sparse(%v) : (tensor<12xf64>) -> tensor<3x4xf64, #SparseMatrix>
%expand3 = call @expand_sparse2sparse(%sv) : (tensor<12xf64, #SparseVector>) -> tensor<3x4xf64, #SparseMatrix>
+ %expand4 = call @expand_dense_3x2x2(%m) : (tensor<3x4xf64>) -> tensor<3x2x2xf64>
+ %expand5 = call @expand_from_sparse_3x2x2(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<3x2x2xf64>
+ %expand6 = call @expand_to_sparse_3x2x2(%m) : (tensor<3x4xf64>) -> tensor<3x2x2xf64, #Sparse3dTensor>
+ %expand7 = call @expand_sparse2sparse_3x2x2(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<3x2x2xf64, #Sparse3dTensor>
+ %expand8 = call @expand_dense_dyn(%dm) : (tensor<?x?xf64>) -> tensor<?x2x?xf64>
+ %expand9 = call @expand_from_sparse_dyn(%sdm) : (tensor<?x?xf64, #SparseMatrix>) -> tensor<?x2x?xf64>
+ %expand10 = call @expand_to_sparse_dyn(%dm) : (tensor<?x?xf64>) -> tensor<?x2x?xf64, #Sparse3dTensor>
%collapse0 = call @collapse_dense(%m) : (tensor<3x4xf64>) -> tensor<12xf64>
%collapse1 = call @collapse_from_sparse(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64>
%collapse2 = call @collapse_to_sparse(%m) : (tensor<3x4xf64>) -> tensor<12xf64, #SparseVector>
%collapse3 = call @collapse_sparse2sparse(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64, #SparseVector>
+ %collapse4 = call @collapse_dense_6x10(%n) : (tensor<2x3x5x2xf64>) -> tensor<6x10xf64>
+ %collapse5 = call @collapse_from_sparse_6x10(%sn) : (tensor<2x3x5x2xf64, #Sparse4dTensor>) -> tensor<6x10xf64>
+ %collapse6 = call @collapse_to_sparse_6x10(%n) : (tensor<2x3x5x2xf64>) -> tensor<6x10xf64, #SparseMatrix>
+ %collapse7 = call @collapse_sparse2sparse_6x10(%sn) : (tensor<2x3x5x2xf64, #Sparse4dTensor>) -> tensor<6x10xf64, #SparseMatrix>
+ %collapse8 = call @collapse_dense_dyn(%dn) : (tensor<?x?x?x?xf64>) -> tensor<?x?xf64>
+ %collapse9 = call @collapse_from_sparse_dyn(%sdn) : (tensor<?x?x?x?xf64, #Sparse4dTensor>) -> tensor<?x?xf64>
+ %collapse10 = call @collapse_to_sparse_dyn(%dn) : (tensor<?x?x?x?xf64>) -> tensor<?x?xf64, #SparseMatrix>
//
- // Verify result.
+ // Verify results of expand
//
// CHECK: ( ( 1, 2, 3, 4 ), ( 5, 6, 7, 8 ), ( 9, 10, 11, 12 ) )
// CHECK-NEXT: ( ( 1, 2, 3, 4 ), ( 5, 6, 7, 8 ), ( 9, 10, 11, 12 ) )
// CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, -1, -1, -1, -1 )
// CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, -1, -1, -1, -1 )
- // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
- // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
+ // CHECK-NEXT: ( ( ( 1.1, 1.2 ), ( 1.3, 1.4 ) ), ( ( 2.1, 2.2 ), ( 2.3, 2.4 ) ), ( ( 3.1, 3.2 ), ( 3.3, 3.4 ) ) )
+ // CHECK-NEXT: ( ( ( 1.1, 1.2 ), ( 1.3, 1.4 ) ), ( ( 2.1, 2.2 ), ( 2.3, 2.4 ) ), ( ( 3.1, 3.2 ), ( 3.3, 3.4 ) ) )
+ // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
// CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
+ // CHECK-NEXT: ( ( ( 1.1, 1.2 ), ( 1.3, 1.4 ) ), ( ( 2.1, 2.2 ), ( 2.3, 2.4 ) ), ( ( 3.1, 3.2 ), ( 3.3, 3.4 ) ) )
+ // CHECK-NEXT: ( ( ( 1.1, 1.2 ), ( 1.3, 1.4 ) ), ( ( 2.1, 2.2 ), ( 2.3, 2.4 ) ), ( ( 3.1, 3.2 ), ( 3.3, 3.4 ) ) )
// CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
//
+
%m0 = vector.transfer_read %expand0[%c0, %c0], %df: tensor<3x4xf64>, vector<3x4xf64>
vector.print %m0 : vector<3x4xf64>
%m1 = vector.transfer_read %expand1[%c0, %c0], %df: tensor<3x4xf64>, vector<3x4xf64>
@@ -109,6 +217,41 @@ module {
%m3 = vector.transfer_read %a3[%c0], %df: memref<?xf64>, vector<16xf64>
vector.print %m3 : vector<16xf64>
+ %m4 = vector.transfer_read %expand4[%c0, %c0, %c0], %df: tensor<3x2x2xf64>, vector<3x2x2xf64>
+ vector.print %m4 : vector<3x2x2xf64>
+ %m5 = vector.transfer_read %expand5[%c0, %c0, %c0], %df: tensor<3x2x2xf64>, vector<3x2x2xf64>
+ vector.print %m5 : vector<3x2x2xf64>
+ %a6 = sparse_tensor.values %expand6 : tensor<3x2x2xf64, #Sparse3dTensor> to memref<?xf64>
+ %m6 = vector.transfer_read %a6[%c0], %df: memref<?xf64>, vector<16xf64>
+ vector.print %m6 : vector<16xf64>
+ %a7 = sparse_tensor.values %expand7 : tensor<3x2x2xf64, #Sparse3dTensor> to memref<?xf64>
+ %m7 = vector.transfer_read %a7[%c0], %df: memref<?xf64>, vector<16xf64>
+ vector.print %m7 : vector<16xf64>
+
+ %m8 = vector.transfer_read %expand8[%c0, %c0, %c0], %df: tensor<?x2x?xf64>, vector<3x2x2xf64>
+ vector.print %m8 : vector<3x2x2xf64>
+ %m9 = vector.transfer_read %expand9[%c0, %c0, %c0], %df: tensor<?x2x?xf64>, vector<3x2x2xf64>
+ vector.print %m9 : vector<3x2x2xf64>
+ %a10 = sparse_tensor.values %expand10 : tensor<?x2x?xf64, #Sparse3dTensor> to memref<?xf64>
+ %m10 = vector.transfer_read %a10[%c0], %df: memref<?xf64>, vector<16xf64>
+ vector.print %m10 : vector<16xf64>
+
+ //
+ // Verify results of collapse
+ //
+ // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
+ // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
+ // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
+ // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
+ // CHECK-NEXT: ( ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ), ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ), ( 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 ), ( 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 ), ( 41, 42, 43, 44, 45, 26, 47, 48, 49, 50 ), ( 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 ) )
+ // CHECK-NEXT: ( ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ), ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ), ( 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 ), ( 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 ), ( 41, 42, 43, 44, 45, 26, 47, 48, 49, 50 ), ( 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 ) )
+ // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, -1, -1, -1, -1 )
+ // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, -1, -1, -1, -1 )
+ // CHECK-NEXT: ( ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ), ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ), ( 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 ), ( 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 ), ( 41, 42, 43, 44, 45, 26, 47, 48, 49, 50 ), ( 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 ) )
+ // CHECK-NEXT: ( ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ), ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ), ( 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 ), ( 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 ), ( 41, 42, 43, 44, 45, 26, 47, 48, 49, 50 ), ( 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 ) )
+ // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, -1, -1, -1, -1 )
+ //
+
%v0 = vector.transfer_read %collapse0[%c0], %df: tensor<12xf64>, vector<12xf64>
vector.print %v0 : vector<12xf64>
%v1 = vector.transfer_read %collapse1[%c0], %df: tensor<12xf64>, vector<12xf64>
@@ -120,17 +263,49 @@ module {
%v3 = vector.transfer_read %b3[%c0], %df: memref<?xf64>, vector<16xf64>
vector.print %v3 : vector<16xf64>
+ %v4 = vector.transfer_read %collapse4[%c0, %c0], %df: tensor<6x10xf64>, vector<6x10xf64>
+ vector.print %v4 : vector<6x10xf64>
+ %v5 = vector.transfer_read %collapse5[%c0, %c0], %df: tensor<6x10xf64>, vector<6x10xf64>
+ vector.print %v5 : vector<6x10xf64>
+ %b6 = sparse_tensor.values %collapse6 : tensor<6x10xf64, #SparseMatrix> to memref<?xf64>
+ %v6 = vector.transfer_read %b6[%c0], %df: memref<?xf64>, vector<64xf64>
+ vector.print %v6 : vector<64xf64>
+ %b7 = sparse_tensor.values %collapse7 : tensor<6x10xf64, #SparseMatrix> to memref<?xf64>
+ %v7 = vector.transfer_read %b7[%c0], %df: memref<?xf64>, vector<64xf64>
+ vector.print %v7 : vector<64xf64>
+
+ %v8 = vector.transfer_read %collapse8[%c0, %c0], %df: tensor<?x?xf64>, vector<6x10xf64>
+ vector.print %v8 : vector<6x10xf64>
+ %v9 = vector.transfer_read %collapse9[%c0, %c0], %df: tensor<?x?xf64>, vector<6x10xf64>
+ vector.print %v9 : vector<6x10xf64>
+ %b10 = sparse_tensor.values %collapse10 : tensor<?x?xf64, #SparseMatrix> to memref<?xf64>
+ %v10 = vector.transfer_read %b10[%c0], %df: memref<?xf64>, vector<64xf64>
+ vector.print %v10 : vector<64xf64>
+
// Release sparse resources.
bufferization.dealloc_tensor %sv : tensor<12xf64, #SparseVector>
bufferization.dealloc_tensor %sm : tensor<3x4xf64, #SparseMatrix>
+ bufferization.dealloc_tensor %sn : tensor<2x3x5x2xf64, #Sparse4dTensor>
+ bufferization.dealloc_tensor %sdm : tensor<?x?xf64, #SparseMatrix>
+ bufferization.dealloc_tensor %sdn : tensor<?x?x?x?xf64, #Sparse4dTensor>
bufferization.dealloc_tensor %expand2 : tensor<3x4xf64, #SparseMatrix>
bufferization.dealloc_tensor %expand3 : tensor<3x4xf64, #SparseMatrix>
+ bufferization.dealloc_tensor %expand6 : tensor<3x2x2xf64, #Sparse3dTensor>
+ bufferization.dealloc_tensor %expand7 : tensor<3x2x2xf64, #Sparse3dTensor>
+ bufferization.dealloc_tensor %expand10 : tensor<?x2x?xf64, #Sparse3dTensor>
bufferization.dealloc_tensor %collapse2 : tensor<12xf64, #SparseVector>
bufferization.dealloc_tensor %collapse3 : tensor<12xf64, #SparseVector>
+ bufferization.dealloc_tensor %collapse6 : tensor<6x10xf64, #SparseMatrix>
+ bufferization.dealloc_tensor %collapse7 : tensor<6x10xf64, #SparseMatrix>
+ bufferization.dealloc_tensor %collapse10 : tensor<?x?xf64, #SparseMatrix>
// Release dense resources.
bufferization.dealloc_tensor %expand1 : tensor<3x4xf64>
bufferization.dealloc_tensor %collapse1 : tensor<12xf64>
+ bufferization.dealloc_tensor %expand5 : tensor<3x2x2xf64>
+ bufferization.dealloc_tensor %collapse5 : tensor<6x10xf64>
+ bufferization.dealloc_tensor %expand9 : tensor<?x2x?xf64>
+ bufferization.dealloc_tensor %collapse9: tensor<?x?xf64>
return
}
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