[Mlir-commits] [mlir] 0af5f84 - [mlir][sparse] split reshape.mlir into expand/collapse_shape.mlir.
Peiming Liu
llvmlistbot at llvm.org
Thu Feb 16 16:07:47 PST 2023
Author: Peiming Liu
Date: 2023-02-17T00:07:41Z
New Revision: 0af5f84a13bed75e0726f6dee5406c8805a11c4c
URL: https://github.com/llvm/llvm-project/commit/0af5f84a13bed75e0726f6dee5406c8805a11c4c
DIFF: https://github.com/llvm/llvm-project/commit/0af5f84a13bed75e0726f6dee5406c8805a11c4c.diff
LOG: [mlir][sparse] split reshape.mlir into expand/collapse_shape.mlir.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D144231
Added:
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_collapse_shape.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_expand_shape.mlir
Modified:
Removed:
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir
################################################################################
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_collapse_shape.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_collapse_shape.mlir
new file mode 100755
index 0000000000000..2591aefe120e5
--- /dev/null
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_collapse_shape.mlir
@@ -0,0 +1,238 @@
+// DEFINE: %{option} = enable-runtime-library=true
+// DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
+// DEFINE: %{run} = mlir-cpu-runner \
+// DEFINE: -e entry -entry-point-result=void \
+// DEFINE: -shared-libs=%mlir_c_runner_utils | \
+// DEFINE: FileCheck %s
+//
+// RUN: %{compile} | %{run}
+//
+// Do the same run, but now with direct IR generation.
+// REDEFINE: %{option} = enable-runtime-library=false
+// RUN: %{compile} | %{run}
+//
+// Do the same run, but now with direct IR generation and vectorization.
+// REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
+// RUN: %{compile} | %{run}
+
+// Do the same run, but now with direct IR generation and, if available, VLA
+// vectorization.
+// REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
+// REDEFINE: %{run} = %lli \
+// REDEFINE: --entry-function=entry_lli \
+// REDEFINE: --extra-module=%S/Inputs/main_for_lli.ll \
+// REDEFINE: %VLA_ARCH_ATTR_OPTIONS \
+// REDEFINE: --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext | \
+// REDEFINE: FileCheck %s
+// RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
+
+#SparseVector = #sparse_tensor.encoding<{
+ dimLevelType = ["compressed"]
+}>
+
+#SparseMatrix = #sparse_tensor.encoding<{
+ 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: collapse.
+//
+module {
+
+ func.func @collapse_dense(%arg0: tensor<3x4xf64>) -> tensor<12xf64> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64> into tensor<12xf64>
+ return %0 : tensor<12xf64>
+ }
+
+ func.func @collapse_from_sparse(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64, #SparseMatrix> into tensor<12xf64>
+ return %0 : tensor<12xf64>
+ }
+
+ func.func @collapse_to_sparse(%arg0: tensor<3x4xf64>) -> tensor<12xf64, #SparseVector> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64> into tensor<12xf64, #SparseVector>
+ return %0 : tensor<12xf64, #SparseVector>
+ }
+
+ func.func @collapse_sparse2sparse(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64, #SparseVector> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64, #SparseMatrix> into tensor<12xf64, #SparseVector>
+ return %0 : tensor<12xf64, #SparseVector>
+ }
+
+ 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 @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>
+ }
+
+ func.func @collapse_sparse2sparse_dyn(%arg0: tensor<?x?x?x?xf64, #Sparse4dTensor>) -> tensor<?x?xf64, #SparseMatrix> {
+ %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : tensor<?x?x?x?xf64, #Sparse4dTensor> into tensor<?x?xf64, #SparseMatrix>
+ return %0 : tensor<?x?xf64, #SparseMatrix>
+ }
+
+ //
+ // Main driver.
+ //
+ func.func @entry() {
+ %c0 = arith.constant 0 : index
+ %df = arith.constant -1.0 : f64
+
+ // Setup test vectors and matrices..
+ %m = arith.constant dense <[ [ 1.1, 0.0, 1.3, 0.0 ],
+ [ 2.1, 0.0, 2.3, 0.0 ],
+ [ 3.1, 0.0, 3.3, 0.0 ]]> : tensor<3x4xf64>
+ %n = arith.constant dense <[
+ [ [[ 1.0, 0.0], [ 3.0, 0.0], [ 5.0, 0.0], [ 7.0, 0.0], [ 9.0, 0.0]],
+ [[ 0.0, 0.0], [ 0.0, 0.0], [ 0.0, 0.0], [ 0.0, 0.0], [ 0.0, 0.0]],
+ [[21.0, 0.0], [23.0, 0.0], [25.0, 0.0], [27.0, 0.0], [29.0, 0.0]] ],
+ [ [[ 0.0, 0.0], [ 0.0, 0.0], [ 0.0, 0.0], [ 0.0, 0.0], [ 0.0, 0.0]],
+ [[41.0, 0.0], [43.0, 0.0], [45.0, 0.0], [47.0, 0.0], [49.0, 0.0]],
+ [[ 0.0, 0.0], [ 0.0, 0.0], [ 0.0, 0.0], [ 0.0, 0.0], [ 0.0, 0.0]] ] ]> : tensor<2x3x5x2xf64>
+ %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>
+
+ %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.
+ %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>
+ %collapse11 = call @collapse_sparse2sparse_dyn(%sdn) : (tensor<?x?x?x?xf64, #Sparse4dTensor>) -> tensor<?x?xf64, #SparseMatrix>
+
+ //
+ // Verify results of collapse
+ //
+ // CHECK: ( 1.1, 0, 1.3, 0, 2.1, 0, 2.3, 0, 3.1, 0, 3.3, 0 )
+ // CHECK-NEXT: ( 1.1, 0, 1.3, 0, 2.1, 0, 2.3, 0, 3.1, 0, 3.3, 0 )
+ // CHECK-NEXT: ( 1.1, 1.3, 2.1, 2.3, 3.1, 3.3
+ // CHECK-NEXT: ( 1.1, 1.3, 2.1, 2.3, 3.1, 3.3
+ // CHECK-NEXT: ( ( 1, 0, 3, 0, 5, 0, 7, 0, 9, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ),
+ // CHECK-SAME: ( 21, 0, 23, 0, 25, 0, 27, 0, 29, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ),
+ // CHECK-SAME: ( 41, 0, 43, 0, 45, 0, 47, 0, 49, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ) )
+ // CHECK-NEXT: ( ( 1, 0, 3, 0, 5, 0, 7, 0, 9, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ),
+ // CHECK-SAME: ( 21, 0, 23, 0, 25, 0, 27, 0, 29, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ),
+ // CHECK-SAME: ( 41, 0, 43, 0, 45, 0, 47, 0, 49, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ) )
+ // CHECK-NEXT: ( 1, 3, 5, 7, 9, 21, 23, 25, 27, 29, 41, 43, 45, 47
+ // CHECK-NEXT: ( 1, 3, 5, 7, 9, 21, 23, 25, 27, 29, 41, 43, 45, 47
+ // CHECK-NEXT: ( ( 1, 0, 3, 0, 5, 0, 7, 0, 9, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ),
+ // CHECK-SAME: ( 21, 0, 23, 0, 25, 0, 27, 0, 29, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ),
+ // CHECK-SAME: ( 41, 0, 43, 0, 45, 0, 47, 0, 49, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ) )
+ // CHECK-NEXT: ( ( 1, 0, 3, 0, 5, 0, 7, 0, 9, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ),
+ // CHECK-SAME: ( 21, 0, 23, 0, 25, 0, 27, 0, 29, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ),
+ // CHECK-SAME: ( 41, 0, 43, 0, 45, 0, 47, 0, 49, 0 ),
+ // CHECK-SAME: ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ) )
+ // CHECK-NEXT: ( 1, 3, 5, 7, 9, 21, 23, 25, 27, 29, 41, 43, 45, 47, 49
+ // CHECK-NEXT: ( 1, 3, 5, 7, 9, 21, 23, 25, 27, 29, 41, 43, 45, 47, 49
+
+ %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>
+ vector.print %v1 : vector<12xf64>
+ %b2 = sparse_tensor.values %collapse2 : tensor<12xf64, #SparseVector> to memref<?xf64>
+ %v2 = vector.transfer_read %b2[%c0], %df: memref<?xf64>, vector<12xf64>
+ vector.print %v2 : vector<12xf64>
+ %b3 = sparse_tensor.values %collapse3 : tensor<12xf64, #SparseVector> to memref<?xf64>
+ %v3 = vector.transfer_read %b3[%c0], %df: memref<?xf64>, vector<12xf64>
+ vector.print %v3 : vector<12xf64>
+
+ %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<60xf64>
+ vector.print %v6 : vector<60xf64>
+ %b7 = sparse_tensor.values %collapse7 : tensor<6x10xf64, #SparseMatrix> to memref<?xf64>
+ %v7 = vector.transfer_read %b7[%c0], %df: memref<?xf64>, vector<60xf64>
+ vector.print %v7 : vector<60xf64>
+
+ %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<60xf64>
+ vector.print %v10 : vector<60xf64>
+ %b11 = sparse_tensor.values %collapse11 : tensor<?x?xf64, #SparseMatrix> to memref<?xf64>
+ %v11 = vector.transfer_read %b11[%c0], %df: memref<?xf64>, vector<60xf64>
+ vector.print %v11 : vector<60xf64>
+
+ // Release sparse resources.
+ bufferization.dealloc_tensor %sm : tensor<3x4xf64, #SparseMatrix>
+ bufferization.dealloc_tensor %sn : tensor<2x3x5x2xf64, #Sparse4dTensor>
+ bufferization.dealloc_tensor %sdn : tensor<?x?x?x?xf64, #Sparse4dTensor>
+ 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>
+ bufferization.dealloc_tensor %collapse11 : tensor<?x?xf64, #SparseMatrix>
+
+ // Release dense resources.
+ bufferization.dealloc_tensor %collapse1 : tensor<12xf64>
+ bufferization.dealloc_tensor %collapse5 : tensor<6x10xf64>
+ bufferization.dealloc_tensor %collapse9: tensor<?x?xf64>
+
+ return
+ }
+}
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_expand_shape.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_expand_shape.mlir
new file mode 100644
index 0000000000000..37ec3de2d49be
--- /dev/null
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_expand_shape.mlir
@@ -0,0 +1,220 @@
+// DEFINE: %{option} = enable-runtime-library=true
+// DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
+// DEFINE: %{run} = mlir-cpu-runner \
+// DEFINE: -e entry -entry-point-result=void \
+// DEFINE: -shared-libs=%mlir_c_runner_utils | \
+// DEFINE: FileCheck %s
+//
+// RUN: %{compile} | %{run}
+//
+// Do the same run, but now with direct IR generation.
+// REDEFINE: %{option} = enable-runtime-library=false
+// RUN: %{compile} | %{run}
+//
+// Do the same run, but now with direct IR generation and vectorization.
+// REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
+// RUN: %{compile} | %{run}
+
+// Do the same run, but now with direct IR generation and, if available, VLA
+// vectorization.
+// REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
+// REDEFINE: %{run} = %lli \
+// REDEFINE: --entry-function=entry_lli \
+// REDEFINE: --extra-module=%S/Inputs/main_for_lli.ll \
+// REDEFINE: %VLA_ARCH_ATTR_OPTIONS \
+// REDEFINE: --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext | \
+// REDEFINE: FileCheck %s
+// RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
+
+#SparseVector = #sparse_tensor.encoding<{
+ dimLevelType = ["compressed"]
+}>
+
+#SparseMatrix = #sparse_tensor.encoding<{
+ 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
+//
+module {
+
+ func.func @expand_dense(%arg0: tensor<12xf64>) -> tensor<3x4xf64> {
+ %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64> into tensor<3x4xf64>
+ return %0 : tensor<3x4xf64>
+ }
+
+ func.func @expand_from_sparse(%arg0: tensor<12xf64, #SparseVector>) -> tensor<3x4xf64> {
+ %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64, #SparseVector> into tensor<3x4xf64>
+ return %0 : tensor<3x4xf64>
+ }
+
+ func.func @expand_to_sparse(%arg0: tensor<12xf64>) -> tensor<3x4xf64, #SparseMatrix> {
+ %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64> into tensor<3x4xf64, #SparseMatrix>
+ return %0 : tensor<3x4xf64, #SparseMatrix>
+ }
+
+ func.func @expand_sparse2sparse(%arg0: tensor<12xf64, #SparseVector>) -> tensor<3x4xf64, #SparseMatrix> {
+ %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64, #SparseVector> into tensor<3x4xf64, #SparseMatrix>
+ return %0 : tensor<3x4xf64, #SparseMatrix>
+ }
+
+ 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 @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 @expand_sparse2sparse_dyn(%arg0: tensor<?x?xf64, #SparseMatrix>) -> tensor<?x2x?xf64, #Sparse3dTensor> {
+ %0 = tensor.expand_shape %arg0 [[0], [1, 2]] : tensor<?x?xf64, #SparseMatrix> into tensor<?x2x?xf64, #Sparse3dTensor>
+ return %0 : tensor<?x2x?xf64, #Sparse3dTensor>
+ }
+
+ //
+ // Main driver.
+ //
+ func.func @entry() {
+ %c0 = arith.constant 0 : index
+ %df = arith.constant -1.0 : f64
+
+ // Setup test vectors and matrices..
+ %v = arith.constant dense <[ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0,
+ 7.0, 0.0, 9.0, 0.0, 11.0, 0.0]> : tensor<12xf64>
+ %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>
+
+ %sv = sparse_tensor.convert %v : tensor<12xf64> to tensor<12xf64, #SparseVector>
+ %sm = sparse_tensor.convert %m : tensor<3x4xf64> to tensor<3x4xf64, #SparseMatrix>
+
+ %dm = tensor.cast %m : tensor<3x4xf64> to tensor<?x?xf64>
+ %sdm = sparse_tensor.convert %dm : tensor<?x?xf64> to tensor<?x?xf64, #SparseMatrix>
+
+ // 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>
+ %expand11 = call @expand_sparse2sparse_dyn(%sdm) : (tensor<?x?xf64, #SparseMatrix>) -> tensor<?x2x?xf64, #Sparse3dTensor>
+
+ //
+ // Verify results of expand
+ //
+ // CHECK: ( ( 1, 0, 3, 0 ), ( 5, 0, 7, 0 ), ( 9, 0, 11, 0 ) )
+ // CHECK-NEXT: ( ( 1, 0, 3, 0 ), ( 5, 0, 7, 0 ), ( 9, 0, 11, 0 ) )
+ // CHECK-NEXT: ( 1, 3, 5, 7, 9,
+ // CHECK-NEXT: ( 1, 3, 5, 7, 9,
+ // 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 ) ) )
+ // 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: 12
+ // 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: 12
+ // 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 )
+ //
+
+ %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>
+ vector.print %m1 : vector<3x4xf64>
+ %a2 = sparse_tensor.values %expand2 : tensor<3x4xf64, #SparseMatrix> to memref<?xf64>
+ %m2 = vector.transfer_read %a2[%c0], %df: memref<?xf64>, vector<12xf64>
+ vector.print %m2 : vector<12xf64>
+ %a3 = sparse_tensor.values %expand3 : tensor<3x4xf64, #SparseMatrix> to memref<?xf64>
+ %m3 = vector.transfer_read %a3[%c0], %df: memref<?xf64>, vector<12xf64>
+ vector.print %m3 : vector<12xf64>
+
+ %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<12xf64>
+ vector.print %m6 : vector<12xf64>
+ %a7 = sparse_tensor.values %expand7 : tensor<3x2x2xf64, #Sparse3dTensor> to memref<?xf64>
+ %m7 = vector.transfer_read %a7[%c0], %df: memref<?xf64>, vector<12xf64>
+ vector.print %m7 : vector<12xf64>
+
+ %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>
+ %n10 = sparse_tensor.number_of_entries %expand10 : tensor<?x2x?xf64, #Sparse3dTensor>
+ vector.print %n10 : index
+ %a10 = sparse_tensor.values %expand10 : tensor<?x2x?xf64, #Sparse3dTensor> to memref<?xf64>
+ %m10 = vector.transfer_read %a10[%c0], %df: memref<?xf64>, vector<12xf64>
+ vector.print %m10 : vector<12xf64>
+ %n11 = sparse_tensor.number_of_entries %expand11 : tensor<?x2x?xf64, #Sparse3dTensor>
+ vector.print %n11 : index
+ %a11 = sparse_tensor.values %expand11 : tensor<?x2x?xf64, #Sparse3dTensor> to memref<?xf64>
+ %m11 = vector.transfer_read %a11[%c0], %df: memref<?xf64>, vector<12xf64>
+ vector.print %m11 : vector<12xf64>
+
+
+ // Release sparse resources.
+ bufferization.dealloc_tensor %sv : tensor<12xf64, #SparseVector>
+ bufferization.dealloc_tensor %sm : tensor<3x4xf64, #SparseMatrix>
+ bufferization.dealloc_tensor %sdm : tensor<?x?xf64, #SparseMatrix>
+ 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 %expand11 : tensor<?x2x?xf64, #Sparse3dTensor>
+
+ // Release dense resources.
+ bufferization.dealloc_tensor %expand1 : tensor<3x4xf64>
+ bufferization.dealloc_tensor %expand5 : tensor<3x2x2xf64>
+ bufferization.dealloc_tensor %expand9 : tensor<?x2x?xf64>
+
+ return
+ }
+}
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir
deleted file mode 100755
index f3dc746769bf2..0000000000000
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir
+++ /dev/null
@@ -1,365 +0,0 @@
-// DEFINE: %{option} = enable-runtime-library=true
-// DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
-// DEFINE: %{run} = mlir-cpu-runner \
-// DEFINE: -e entry -entry-point-result=void \
-// DEFINE: -shared-libs=%mlir_c_runner_utils | \
-// DEFINE: FileCheck %s
-//
-// RUN: %{compile} | %{run}
-//
-// Do the same run, but now with direct IR generation.
-// REDEFINE: %{option} = enable-runtime-library=false
-// RUN: %{compile} | %{run}
-//
-// Do the same run, but now with direct IR generation and vectorization.
-// REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
-// RUN: %{compile} | %{run}
-
-// Do the same run, but now with direct IR generation and, if available, VLA
-// vectorization.
-// REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
-// REDEFINE: %{run} = %lli \
-// REDEFINE: --entry-function=entry_lli \
-// REDEFINE: --extra-module=%S/Inputs/main_for_lli.ll \
-// REDEFINE: %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE: --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext | \
-// REDEFINE: FileCheck %s
-// RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
-
-#SparseVector = #sparse_tensor.encoding<{
- dimLevelType = ["compressed"]
-}>
-
-#SparseMatrix = #sparse_tensor.encoding<{
- 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.
-//
-module {
-
- func.func @expand_dense(%arg0: tensor<12xf64>) -> tensor<3x4xf64> {
- %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64> into tensor<3x4xf64>
- return %0 : tensor<3x4xf64>
- }
-
- func.func @expand_from_sparse(%arg0: tensor<12xf64, #SparseVector>) -> tensor<3x4xf64> {
- %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64, #SparseVector> into tensor<3x4xf64>
- return %0 : tensor<3x4xf64>
- }
-
- func.func @expand_to_sparse(%arg0: tensor<12xf64>) -> tensor<3x4xf64, #SparseMatrix> {
- %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64> into tensor<3x4xf64, #SparseMatrix>
- return %0 : tensor<3x4xf64, #SparseMatrix>
- }
-
- func.func @expand_sparse2sparse(%arg0: tensor<12xf64, #SparseVector>) -> tensor<3x4xf64, #SparseMatrix> {
- %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64, #SparseVector> into tensor<3x4xf64, #SparseMatrix>
- return %0 : tensor<3x4xf64, #SparseMatrix>
- }
-
- func.func @collapse_dense(%arg0: tensor<3x4xf64>) -> tensor<12xf64> {
- %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64> into tensor<12xf64>
- return %0 : tensor<12xf64>
- }
-
- func.func @collapse_from_sparse(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64> {
- %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64, #SparseMatrix> into tensor<12xf64>
- return %0 : tensor<12xf64>
- }
-
- func.func @collapse_to_sparse(%arg0: tensor<3x4xf64>) -> tensor<12xf64, #SparseVector> {
- %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64> into tensor<12xf64, #SparseVector>
- return %0 : tensor<12xf64, #SparseVector>
- }
-
- func.func @collapse_sparse2sparse(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64, #SparseVector> {
- %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64, #SparseMatrix> into tensor<12xf64, #SparseVector>
- 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 @expand_sparse2sparse_dyn(%arg0: tensor<?x?xf64, #SparseMatrix>) -> tensor<?x2x?xf64, #Sparse3dTensor> {
- %0 = tensor.expand_shape %arg0 [[0], [1, 2]] : tensor<?x?xf64, #SparseMatrix> 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>
- }
-
- func.func @collapse_sparse2sparse_dyn(%arg0: tensor<?x?x?x?xf64, #Sparse4dTensor>) -> tensor<?x?xf64, #SparseMatrix> {
- %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : tensor<?x?x?x?xf64, #Sparse4dTensor> into tensor<?x?xf64, #SparseMatrix>
- return %0 : tensor<?x?xf64, #SparseMatrix>
- }
-
- //
- // Main driver.
- //
- func.func @entry() {
- %c0 = arith.constant 0 : index
- %df = arith.constant -1.0 : f64
-
- // Setup test vectors and matrices..
- %v = 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]> : tensor<12xf64>
- %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>
- %expand11 = call @expand_sparse2sparse_dyn(%sdm) : (tensor<?x?xf64, #SparseMatrix>) -> 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>
- %collapse11 = call @collapse_sparse2sparse_dyn(%sdn) : (tensor<?x?x?x?xf64, #Sparse4dTensor>) -> tensor<?x?xf64, #SparseMatrix>
-
- //
- // 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 )
- // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 )
- // 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 ) ) )
- // 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: 12
- // 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: 12
- // 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 )
- //
-
- %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>
- vector.print %m1 : vector<3x4xf64>
- %a2 = sparse_tensor.values %expand2 : tensor<3x4xf64, #SparseMatrix> to memref<?xf64>
- %m2 = vector.transfer_read %a2[%c0], %df: memref<?xf64>, vector<12xf64>
- vector.print %m2 : vector<12xf64>
- %a3 = sparse_tensor.values %expand3 : tensor<3x4xf64, #SparseMatrix> to memref<?xf64>
- %m3 = vector.transfer_read %a3[%c0], %df: memref<?xf64>, vector<12xf64>
- vector.print %m3 : vector<12xf64>
-
- %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<12xf64>
- vector.print %m6 : vector<12xf64>
- %a7 = sparse_tensor.values %expand7 : tensor<3x2x2xf64, #Sparse3dTensor> to memref<?xf64>
- %m7 = vector.transfer_read %a7[%c0], %df: memref<?xf64>, vector<12xf64>
- vector.print %m7 : vector<12xf64>
-
- %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>
- %n10 = sparse_tensor.number_of_entries %expand10 : tensor<?x2x?xf64, #Sparse3dTensor>
- vector.print %n10 : index
- %a10 = sparse_tensor.values %expand10 : tensor<?x2x?xf64, #Sparse3dTensor> to memref<?xf64>
- %m10 = vector.transfer_read %a10[%c0], %df: memref<?xf64>, vector<12xf64>
- vector.print %m10 : vector<12xf64>
- %n11 = sparse_tensor.number_of_entries %expand11 : tensor<?x2x?xf64, #Sparse3dTensor>
- vector.print %n11 : index
- %a11 = sparse_tensor.values %expand11 : tensor<?x2x?xf64, #Sparse3dTensor> to memref<?xf64>
- %m11 = vector.transfer_read %a11[%c0], %df: memref<?xf64>, vector<12xf64>
- vector.print %m11 : vector<12xf64>
-
-
- //
- // 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 )
- // 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, 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 )
- // 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 ) )
- // 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 )
- //
-
- %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>
- vector.print %v1 : vector<12xf64>
- %b2 = sparse_tensor.values %collapse2 : tensor<12xf64, #SparseVector> to memref<?xf64>
- %v2 = vector.transfer_read %b2[%c0], %df: memref<?xf64>, vector<12xf64>
- vector.print %v2 : vector<12xf64>
- %b3 = sparse_tensor.values %collapse3 : tensor<12xf64, #SparseVector> to memref<?xf64>
- %v3 = vector.transfer_read %b3[%c0], %df: memref<?xf64>, vector<12xf64>
- vector.print %v3 : vector<12xf64>
-
- %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<60xf64>
- vector.print %v6 : vector<60xf64>
- %b7 = sparse_tensor.values %collapse7 : tensor<6x10xf64, #SparseMatrix> to memref<?xf64>
- %v7 = vector.transfer_read %b7[%c0], %df: memref<?xf64>, vector<60xf64>
- vector.print %v7 : vector<60xf64>
-
- %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<60xf64>
- vector.print %v10 : vector<60xf64>
- %b11 = sparse_tensor.values %collapse11 : tensor<?x?xf64, #SparseMatrix> to memref<?xf64>
- %v11 = vector.transfer_read %b11[%c0], %df: memref<?xf64>, vector<60xf64>
- vector.print %v11 : vector<60xf64>
-
-
- // 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 %expand11 : 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>
- bufferization.dealloc_tensor %collapse11 : 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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