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Feb 29, 2024
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[mlir][sparse] migrate integration tests to sparse_tensor.print #83357

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45 changes: 23 additions & 22 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/block.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@
// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
// DEFINE: %{run_opts} = -e entry -entry-point-result=void
// DEFINE: %{run_opts} = -e main -entry-point-result=void
// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
//
Expand Down Expand Up @@ -82,38 +82,39 @@ module {
return %0 : tensor<?x?xf64, #BSR>
}

func.func @entry() {
func.func @main() {
%c0 = arith.constant 0 : index
%f0 = arith.constant 0.0 : f64

%fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
%A = sparse_tensor.new %fileName : !Filename to tensor<?x?xf64, #BSR>

// CHECK: ( 0, 2, 3 )
// CHECK-NEXT: ( 0, 2, 1 )
// CHECK-NEXT: ( 1, 2, 0, 3, 4, 0, 0, 5, 6, 7, 8, 0 )
%pos = sparse_tensor.positions %A {level = 1 : index } : tensor<?x?xf64, #BSR> to memref<?xindex>
%vecp = vector.transfer_read %pos[%c0], %c0 : memref<?xindex>, vector<3xindex>
vector.print %vecp : vector<3xindex>
%crd = sparse_tensor.coordinates %A {level = 1 : index } : tensor<?x?xf64, #BSR> to memref<?xindex>
%vecc = vector.transfer_read %crd[%c0], %c0 : memref<?xindex>, vector<3xindex>
vector.print %vecc : vector<3xindex>
%val = sparse_tensor.values %A : tensor<?x?xf64, #BSR> to memref<?xf64>
%vecv = vector.transfer_read %val[%c0], %f0 : memref<?xf64>, vector<12xf64>
vector.print %vecv : vector<12xf64>
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 12
// CHECK-NEXT: pos[1] : ( 0, 2, 3,
// CHECK-NEXT: crd[1] : ( 0, 2, 1,
// CHECK-NEXT: values : ( 1, 2, 0, 3, 4, 0, 0, 5, 6, 7, 8, 0,
// CHECK-NEXT: ----
sparse_tensor.print %A : tensor<?x?xf64, #BSR>

// CHECK-NEXT: ( 1, 2, 0, 3, 4, 0, 0, 5, 6, 7, 8, 0 )
// CHECK-NEXT: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 12
// CHECK-NEXT: pos[1] : ( 0, 2, 3,
// CHECK-NEXT: crd[1] : ( 0, 2, 1
// CHECK-NEXT: values : ( 1, 2, 0, 3, 4, 0, 0, 5, 6, 7, 8, 0,
// CHECK-NEXT: ----
%t1 = sparse_tensor.reinterpret_map %A : tensor<?x?xf64, #BSR>
to tensor<?x?x2x2xf64, #DSDD>
%vdsdd = sparse_tensor.values %t1 : tensor<?x?x2x2xf64, #DSDD> to memref<?xf64>
%vecdsdd = vector.transfer_read %vdsdd[%c0], %f0 : memref<?xf64>, vector<12xf64>
vector.print %vecdsdd : vector<12xf64>
sparse_tensor.print %t1 : tensor<?x?x2x2xf64, #DSDD>

// CHECK-NEXT: ( 3, 6, 0, 9, 12, 0, 0, 15, 18, 21, 24, 0 )
// CHECK-NEXT: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 12
// CHECK-NEXT: pos[1] : ( 0, 2, 3,
// CHECK-NEXT: crd[1] : ( 0, 2, 1,
// CHECK-NEXT: values : ( 3, 6, 0, 9, 12, 0, 0, 15, 18, 21, 24, 0,
// CHECK-NEXT: ----
%As = call @scale(%A) : (tensor<?x?xf64, #BSR>) -> (tensor<?x?xf64, #BSR>)
%vals = sparse_tensor.values %As : tensor<?x?xf64, #BSR> to memref<?xf64>
%vecs = vector.transfer_read %vals[%c0], %f0 : memref<?xf64>, vector<12xf64>
vector.print %vecs : vector<12xf64>
sparse_tensor.print %As : tensor<?x?xf64, #BSR>

// Release the resources.
bufferization.dealloc_tensor %A: tensor<?x?xf64, #BSR>
Expand Down
85 changes: 37 additions & 48 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -102,9 +102,15 @@
//
module {

// CHECK: ( 0, 1, 2 )
// CHECK-NEXT: ( 0, 2 )
// CHECK-NEXT: ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 )

//
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 24
// CHECK-NEXT: pos[1] : ( 0, 1, 2,
// CHECK-NEXT: crd[1] : ( 0, 2,
// CHECK-NEXT: values : ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7,
// CHECK-NEXT: ----
//
func.func @foo1() {
// Build.
%c0 = arith.constant 0 : index
Expand All @@ -115,23 +121,20 @@ module {
> : tensor<6x16xf64>
%s1 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_row_rowmajor>
// Test.
%pos1 = sparse_tensor.positions %s1 {level = 1 : index } : tensor<?x?xf64, #BSR_row_rowmajor> to memref<?xindex>
%vecp1 = vector.transfer_read %pos1[%c0], %c0 : memref<?xindex>, vector<3xindex>
vector.print %vecp1 : vector<3xindex>
%crd1 = sparse_tensor.coordinates %s1 {level = 1 : index } : tensor<?x?xf64, #BSR_row_rowmajor> to memref<?xindex>
%vecc1 = vector.transfer_read %crd1[%c0], %c0 : memref<?xindex>, vector<2xindex>
vector.print %vecc1 : vector<2xindex>
%val1 = sparse_tensor.values %s1 : tensor<?x?xf64, #BSR_row_rowmajor> to memref<?xf64>
%vecv1 = vector.transfer_read %val1[%c0], %f0 : memref<?xf64>, vector<24xf64>
vector.print %vecv1 : vector<24xf64>
sparse_tensor.print %s1 : tensor<?x?xf64, #BSR_row_rowmajor>
// Release.
bufferization.dealloc_tensor %s1: tensor<?x?xf64, #BSR_row_rowmajor>
return
}

// CHECK-NEXT: ( 0, 1, 2 )
// CHECK-NEXT: ( 0, 2 )
// CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 )
//
// CHECK-NEXT: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 24
// CHECK-NEXT: pos[1] : ( 0, 1, 2,
// CHECK-NEXT: crd[1] : ( 0, 2,
// CHECK-NEXT: values : ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7,
// CHECK-NEXT: ----
//
func.func @foo2() {
// Build.
%c0 = arith.constant 0 : index
Expand All @@ -142,23 +145,20 @@ module {
> : tensor<6x16xf64>
%s2 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_row_colmajor>
// Test.
%pos2 = sparse_tensor.positions %s2 {level = 1 : index } : tensor<?x?xf64, #BSR_row_colmajor> to memref<?xindex>
%vecp2 = vector.transfer_read %pos2[%c0], %c0 : memref<?xindex>, vector<3xindex>
vector.print %vecp2 : vector<3xindex>
%crd2 = sparse_tensor.coordinates %s2 {level = 1 : index } : tensor<?x?xf64, #BSR_row_colmajor> to memref<?xindex>
%vecc2 = vector.transfer_read %crd2[%c0], %c0 : memref<?xindex>, vector<2xindex>
vector.print %vecc2 : vector<2xindex>
%val2 = sparse_tensor.values %s2 : tensor<?x?xf64, #BSR_row_colmajor> to memref<?xf64>
%vecv2 = vector.transfer_read %val2[%c0], %f0 : memref<?xf64>, vector<24xf64>
vector.print %vecv2 : vector<24xf64>
sparse_tensor.print %s2 : tensor<?x?xf64, #BSR_row_colmajor>
// Release.
bufferization.dealloc_tensor %s2: tensor<?x?xf64, #BSR_row_colmajor>
return
}

// CHECK-NEXT: ( 0, 1, 1, 2, 2 )
// CHECK-NEXT: ( 0, 1 )
// CHECK-NEXT: ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 )
//
// CHECK-NEXT: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 24
// CHECK-NEXT: pos[1] : ( 0, 1, 1, 2, 2,
// CHECK-NEXT: crd[1] : ( 0, 1,
// CHECK-NEXT: values : ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7,
// CHECK-NEXT: ----
//
func.func @foo3() {
// Build.
%c0 = arith.constant 0 : index
Expand All @@ -169,23 +169,20 @@ module {
> : tensor<6x16xf64>
%s3 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_col_rowmajor>
// Test.
%pos3 = sparse_tensor.positions %s3 {level = 1 : index } : tensor<?x?xf64, #BSR_col_rowmajor> to memref<?xindex>
%vecp3 = vector.transfer_read %pos3[%c0], %c0 : memref<?xindex>, vector<5xindex>
vector.print %vecp3 : vector<5xindex>
%crd3 = sparse_tensor.coordinates %s3 {level = 1 : index } : tensor<?x?xf64, #BSR_col_rowmajor> to memref<?xindex>
%vecc3 = vector.transfer_read %crd3[%c0], %c0 : memref<?xindex>, vector<2xindex>
vector.print %vecc3 : vector<2xindex>
%val3 = sparse_tensor.values %s3 : tensor<?x?xf64, #BSR_col_rowmajor> to memref<?xf64>
%vecv3 = vector.transfer_read %val3[%c0], %f0 : memref<?xf64>, vector<24xf64>
vector.print %vecv3 : vector<24xf64>
sparse_tensor.print %s3 : tensor<?x?xf64, #BSR_col_rowmajor>
// Release.
bufferization.dealloc_tensor %s3: tensor<?x?xf64, #BSR_col_rowmajor>
return
}

// CHECK-NEXT: ( 0, 1, 1, 2, 2 )
// CHECK-NEXT: ( 0, 1 )
// CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 )
//
// CHECK-NEXT: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 24
// CHECK-NEXT: pos[1] : ( 0, 1, 1, 2, 2,
// CHECK-NEXT: crd[1] : ( 0, 1,
// CHECK-NEXT: values : ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7,
// CHECK-NEXT: ----
//
func.func @foo4() {
// Build.
%c0 = arith.constant 0 : index
Expand All @@ -196,15 +193,7 @@ module {
> : tensor<6x16xf64>
%s4 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_col_colmajor>
// Test.
%pos4 = sparse_tensor.positions %s4 {level = 1 : index } : tensor<?x?xf64, #BSR_col_colmajor> to memref<?xindex>
%vecp4 = vector.transfer_read %pos4[%c0], %c0 : memref<?xindex>, vector<5xindex>
vector.print %vecp4 : vector<5xindex>
%crd4 = sparse_tensor.coordinates %s4 {level = 1 : index } : tensor<?x?xf64, #BSR_col_colmajor> to memref<?xindex>
%vecc4 = vector.transfer_read %crd4[%c0], %c0 : memref<?xindex>, vector<2xindex>
vector.print %vecc4 : vector<2xindex>
%val4 = sparse_tensor.values %s4 : tensor<?x?xf64, #BSR_col_colmajor> to memref<?xf64>
%vecv4 = vector.transfer_read %val4[%c0], %f0 : memref<?xf64>, vector<24xf64>
vector.print %vecv4 : vector<24xf64>
sparse_tensor.print %s4 : tensor<?x?xf64, #BSR_col_colmajor>
// Release.
bufferization.dealloc_tensor %s4: tensor<?x?xf64, #BSR_col_colmajor>
return
Expand Down
18 changes: 8 additions & 10 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@
// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
// DEFINE: %{run_opts} = -e entry -entry-point-result=void
// DEFINE: %{run_opts} = -e main -entry-point-result=void
// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
//
Expand Down Expand Up @@ -83,12 +83,11 @@ module {
}

func.func private @getTensorFilename(index) -> (!Filename)
func.func private @printMemref1dF64(%ptr : memref<?xf64>) attributes { llvm.emit_c_interface }

//
// Main driver that reads matrix from file and calls the kernel.
//
func.func @entry() {
func.func @main() {
%d0 = arith.constant 0.0 : f64
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
Expand All @@ -104,14 +103,13 @@ module {

//
// Print the linearized 5x5 result for verification.
// CHECK: 25
// CHECK: [2, 0, 0, 2.8, 0, 0, 4, 0, 0, 5, 0, 0, 6, 0, 0, 8.2, 0, 0, 8, 0, 0, 10.4, 0, 0, 10
//
%n = sparse_tensor.number_of_entries %0 : tensor<?x?xf64, #DenseMatrix>
vector.print %n : index
%m = sparse_tensor.values %0
: tensor<?x?xf64, #DenseMatrix> to memref<?xf64>
call @printMemref1dF64(%m) : (memref<?xf64>) -> ()
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 25
// CHECK-NEXT: values : ( 2, 0, 0, 2.8, 0, 0, 4, 0, 0, 5, 0, 0, 6, 0, 0, 8.2, 0, 0, 8, 0, 0, 10.4, 0, 0, 10,
// CHECK-NEXT: ----
//
sparse_tensor.print %0 : tensor<?x?xf64, #DenseMatrix>

// Release the resources.
bufferization.dealloc_tensor %a : tensor<?x?xf64, #SparseMatrix>
Expand Down
24 changes: 8 additions & 16 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_bf16.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@
// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
// DEFINE: %{run_opts} = -e entry -entry-point-result=void
// DEFINE: %{run_opts} = -e main -entry-point-result=void
// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
//
Expand Down Expand Up @@ -67,20 +67,8 @@ module {
return %0 : tensor<?xbf16, #DenseVector>
}

// Dumps a dense vector of type bf16.
func.func @dump_vec(%arg0: tensor<?xbf16, #DenseVector>) {
// Dump the values array to verify only sparse contents are stored.
%c0 = arith.constant 0 : index
%d0 = arith.constant -1.0 : bf16
%0 = sparse_tensor.values %arg0 : tensor<?xbf16, #DenseVector> to memref<?xbf16>
%1 = vector.transfer_read %0[%c0], %d0: memref<?xbf16>, vector<32xbf16>
%f1 = arith.extf %1: vector<32xbf16> to vector<32xf32>
vector.print %f1 : vector<32xf32>
return
}

// Driver method to call and verify the kernel.
func.func @entry() {
func.func @main() {
%c0 = arith.constant 0 : index

// Setup sparse vectors.
Expand All @@ -103,8 +91,12 @@ module {
//
// Verify the result.
//
// CHECK: ( 1, 11, 0, 2, 13, 0, 0, 0, 0, 0, 14, 3, 0, 0, 0, 0, 15, 4, 16, 0, 5, 6, 0, 0, 0, 0, 0, 0, 7, 8, 0, 9 )
call @dump_vec(%0) : (tensor<?xbf16, #DenseVector>) -> ()
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 32
// CHECK-NEXT: values : ( 1, 11, 0, 2, 13, 0, 0, 0, 0, 0, 14, 3, 0, 0, 0, 0, 15, 4, 16, 0, 5, 6, 0, 0, 0, 0, 0, 0, 7, 8, 0, 9,
// CHECK-NEXT: ----
//
sparse_tensor.print %0 : tensor<?xbf16, #DenseVector>

// Release the resources.
bufferization.dealloc_tensor %sv1 : tensor<?xbf16, #SparseVector>
Expand Down
24 changes: 8 additions & 16 deletions mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@
// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
// DEFINE: %{run_opts} = -e entry -entry-point-result=void
// DEFINE: %{run_opts} = -e main -entry-point-result=void
// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
//
Expand Down Expand Up @@ -68,20 +68,8 @@ module {
return %0 : tensor<?xf16, #DenseVector>
}

// Dumps a dense vector of type f16.
func.func @dump_vec(%arg0: tensor<?xf16, #DenseVector>) {
// Dump the values array to verify only sparse contents are stored.
%c0 = arith.constant 0 : index
%d0 = arith.constant -1.0 : f16
%0 = sparse_tensor.values %arg0 : tensor<?xf16, #DenseVector> to memref<?xf16>
%1 = vector.transfer_read %0[%c0], %d0: memref<?xf16>, vector<32xf16>
%f1 = arith.extf %1: vector<32xf16> to vector<32xf32>
vector.print %f1 : vector<32xf32>
return
}

// Driver method to call and verify the kernel.
func.func @entry() {
func.func @main() {
%c0 = arith.constant 0 : index

// Setup sparse vectors.
Expand All @@ -104,8 +92,12 @@ module {
//
// Verify the result.
//
// CHECK: ( 1, 11, 0, 2, 13, 0, 0, 0, 0, 0, 14, 3, 0, 0, 0, 0, 15, 4, 16, 0, 5, 6, 0, 0, 0, 0, 0, 0, 7, 8, 0, 9 )
call @dump_vec(%0) : (tensor<?xf16, #DenseVector>) -> ()
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 32
// CHECK-NEXT: values : ( 1, 11, 0, 2, 13, 0, 0, 0, 0, 0, 14, 3, 0, 0, 0, 0, 15, 4, 16, 0, 5, 6, 0, 0, 0, 0, 0, 0, 7, 8, 0, 9,
// CHECK-NEXT: ----
//
sparse_tensor.print %0 : tensor<?xf16, #DenseVector>

// Release the resources.
bufferization.dealloc_tensor %sv1 : tensor<?xf16, #SparseVector>
Expand Down
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