[Mlir-commits] [mlir] 4cb5a96 - [mlir][sparse] Migrate more tests to sparse_tensor.print (#84249)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Thu Mar 7 11:02:25 PST 2024
Author: Yinying Li
Date: 2024-03-07T14:02:20-05:00
New Revision: 4cb5a96af646e18f9fc8c1b337299d5465f0a4d6
URL: https://github.com/llvm/llvm-project/commit/4cb5a96af646e18f9fc8c1b337299d5465f0a4d6
DIFF: https://github.com/llvm/llvm-project/commit/4cb5a96af646e18f9fc8c1b337299d5465f0a4d6.diff
LOG: [mlir][sparse] Migrate more tests to sparse_tensor.print (#84249)
Continuous efforts following #83946.
Added:
Modified:
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scale.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scf_nested.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_select.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_semiring_select.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sign.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_storage.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_strided_conv_2d_nhwc_hwcf.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tanh.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_mul.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_ops.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose_coo.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_unary.mlir
mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_vector_ops.mlir
Removed:
################################################################################
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scale.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scale.mlir
index 6ec13fd623b5cd..4e9090ae201d02 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scale.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scale.mlir
@@ -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}
//
@@ -65,7 +65,7 @@ module {
// and then calls the sparse scaling kernel with the sparse tensor
// as input argument.
//
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%f0 = arith.constant 0.0 : f32
@@ -88,11 +88,16 @@ module {
// Print the resulting compacted values for verification.
//
- // CHECK: ( 2, 2, 2, 4, 6, 8, 2, 10, 2, 2, 12, 2, 14, 2, 2, 16 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 16
+ // CHECK-NEXT: dim = ( 8, 8 )
+ // CHECK-NEXT: lvl = ( 8, 8 )
+ // CHECK-NEXT: pos[1] : ( 0, 3, 4, 5, 6, 8, 11, 14, 16
+ // CHECK-NEXT: crd[1] : ( 0, 2, 7, 1, 2, 3, 1, 4, 1, 2, 5, 2, 6, 7, 2, 7
+ // CHECK-NEXT: values : ( 2, 2, 2, 4, 6, 8, 2, 10, 2, 2, 12, 2, 14, 2, 2, 16
+ // CHECK-NEXT: ----
//
- %m = sparse_tensor.values %2 : tensor<8x8xf32, #CSR> to memref<?xf32>
- %v = vector.transfer_read %m[%c0], %f0: memref<?xf32>, vector<16xf32>
- vector.print %v : vector<16xf32>
+ sparse_tensor.print %2 : tensor<8x8xf32, #CSR>
// Release the resources.
bufferization.dealloc_tensor %1 : tensor<8x8xf32, #CSR>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scf_nested.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scf_nested.mlir
index 439144fedeeb89..dd8396dc23b036 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scf_nested.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scf_nested.mlir
@@ -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}
//
@@ -68,17 +68,7 @@ module @func_sparse.2 {
return %1 : tensor<2x3x4xf64, #SparseMatrix>
}
- func.func @dump(%arg0: tensor<2x3x4xf64, #SparseMatrix>) {
- %d0 = arith.constant 0.0 : f64
- %c0 = arith.constant 0 : index
- %dm = sparse_tensor.convert %arg0 : tensor<2x3x4xf64, #SparseMatrix> to tensor<2x3x4xf64>
- %0 = vector.transfer_read %dm[%c0, %c0, %c0], %d0: tensor<2x3x4xf64>, vector<2x3x4xf64>
- vector.print %0 : vector<2x3x4xf64>
- bufferization.dealloc_tensor %dm : tensor<2x3x4xf64>
- return
- }
-
- func.func public @entry() {
+ func.func public @main() {
%src = arith.constant dense<[
[ [ 1.0, 2.0, 3.0, 4.0 ],
[ 5.0, 6.0, 7.0, 8.0 ],
@@ -96,10 +86,34 @@ module @func_sparse.2 {
%sm_t = call @condition(%t, %sm) : (i1, tensor<2x3x4xf64, #SparseMatrix>) -> tensor<2x3x4xf64, #SparseMatrix>
%sm_f = call @condition(%f, %sm) : (i1, tensor<2x3x4xf64, #SparseMatrix>) -> tensor<2x3x4xf64, #SparseMatrix>
- // CHECK: ( ( ( 0, 1, 2, 3 ), ( 4, 5, 6, 7 ), ( 8, 9, 10, 11 ) ), ( ( 12, 13, 14, 15 ), ( 16, 17, 18, 19 ), ( 20, 21, 22, 23 ) ) )
- // CHECK-NEXT: ( ( ( 2, 3, 4, 5 ), ( 6, 7, 8, 9 ), ( 10, 11, 12, 13 ) ), ( ( 14, 15, 16, 17 ), ( 18, 19, 20, 21 ), ( 22, 23, 24, 25 ) ) )
- call @dump(%sm_t) : (tensor<2x3x4xf64, #SparseMatrix>) -> ()
- call @dump(%sm_f) : (tensor<2x3x4xf64, #SparseMatrix>) -> ()
+ //
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 24
+ // CHECK-NEXT: dim = ( 2, 3, 4 )
+ // CHECK-NEXT: lvl = ( 2, 3, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 2
+ // CHECK-NEXT: crd[0] : ( 0, 1
+ // CHECK-NEXT: pos[1] : ( 0, 3, 6
+ // CHECK-NEXT: crd[1] : ( 0, 1, 2, 0, 1, 2
+ // CHECK-NEXT: pos[2] : ( 0, 4, 8, 12, 16, 20, 24
+ // CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3
+ // CHECK-NEXT: values : ( 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 24
+ // CHECK-NEXT: dim = ( 2, 3, 4 )
+ // CHECK-NEXT: lvl = ( 2, 3, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 2
+ // CHECK-NEXT: crd[0] : ( 0, 1
+ // CHECK-NEXT: pos[1] : ( 0, 3, 6
+ // CHECK-NEXT: crd[1] : ( 0, 1, 2, 0, 1, 2
+ // CHECK-NEXT: pos[2] : ( 0, 4, 8, 12, 16, 20, 24
+ // CHECK-NEXT: crd[2] : ( 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3
+ // CHECK-NEXT: values : ( 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
+ // CHECK-NEXT: ----
+ //
+ sparse_tensor.print %sm_t : tensor<2x3x4xf64, #SparseMatrix>
+ sparse_tensor.print %sm_f : tensor<2x3x4xf64, #SparseMatrix>
bufferization.dealloc_tensor %sm : tensor<2x3x4xf64, #SparseMatrix>
bufferization.dealloc_tensor %sm_t : tensor<2x3x4xf64, #SparseMatrix>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_select.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_select.mlir
index 533afb6644aeda..68bc17175e3b4b 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_select.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_select.mlir
@@ -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}
//
@@ -97,39 +97,8 @@ module {
return %0 : tensor<?x?xf64, #CSR>
}
- // Dumps a sparse vector of type f64.
- func.func @dump_vec(%arg0: tensor<?xf64, #SparseVector>) {
- // Dump the values array to verify only sparse contents are stored.
- %c0 = arith.constant 0 : index
- %d0 = arith.constant 0.0 : f64
- %0 = sparse_tensor.values %arg0 : tensor<?xf64, #SparseVector> to memref<?xf64>
- %1 = vector.transfer_read %0[%c0], %d0: memref<?xf64>, vector<8xf64>
- vector.print %1 : vector<8xf64>
- // Dump the dense vector to verify structure is correct.
- %dv = sparse_tensor.convert %arg0 : tensor<?xf64, #SparseVector> to tensor<?xf64>
- %2 = vector.transfer_read %dv[%c0], %d0: tensor<?xf64>, vector<16xf64>
- vector.print %2 : vector<16xf64>
- bufferization.dealloc_tensor %dv : tensor<?xf64>
- return
- }
-
- // Dump a sparse matrix.
- func.func @dump_mat(%arg0: tensor<?x?xf64, #CSR>) {
- // Dump the values array to verify only sparse contents are stored.
- %c0 = arith.constant 0 : index
- %d0 = arith.constant 0.0 : f64
- %0 = sparse_tensor.values %arg0 : tensor<?x?xf64, #CSR> to memref<?xf64>
- %1 = vector.transfer_read %0[%c0], %d0: memref<?xf64>, vector<16xf64>
- vector.print %1 : vector<16xf64>
- %dm = sparse_tensor.convert %arg0 : tensor<?x?xf64, #CSR> to tensor<?x?xf64>
- %2 = vector.transfer_read %dm[%c0, %c0], %d0: tensor<?x?xf64>, vector<5x5xf64>
- vector.print %2 : vector<5x5xf64>
- bufferization.dealloc_tensor %dm : tensor<?x?xf64>
- return
- }
-
// Driver method to call and verify vector kernels.
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
// Setup sparse matrices.
@@ -151,19 +120,43 @@ module {
//
// Verify the results.
//
- // CHECK: ( 1, 2, -4, 0, 5, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 1, 0, 2, 0, -4, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( ( 0, 0, 0, 1, 0 ), ( 0, 0, 0, 0, 2 ), ( 0, 3, 0, 4, 0 ), ( 0, 0, 0, 5, 6 ), ( 0, 0, 7, 0, 0 ) )
- // CHECK-NEXT: ( 1, 2, 5, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 1, 0, 2, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 1, 2, 4, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( ( 0, 0, 0, 1, 0 ), ( 0, 0, 0, 0, 2 ), ( 0, 0, 0, 4, 0 ), ( 0, 0, 0, 0, 6 ), ( 0, 0, 0, 0, 0 ) )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 5
+ // CHECK-NEXT: dim = ( 10 )
+ // CHECK-NEXT: lvl = ( 10 )
+ // CHECK-NEXT: pos[0] : ( 0, 5
+ // CHECK-NEXT: crd[0] : ( 1, 3, 5, 7, 9
+ // CHECK-NEXT: values : ( 1, 2, -4, 0, 5
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 7
+ // CHECK-NEXT: dim = ( 5, 5 )
+ // CHECK-NEXT: lvl = ( 5, 5 )
+ // CHECK-NEXT: pos[1] : ( 0, 1, 2, 4, 6, 7
+ // CHECK-NEXT: crd[1] : ( 3, 4, 1, 3, 3, 4, 2
+ // CHECK-NEXT: values : ( 1, 2, 3, 4, 5, 6, 7
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 3
+ // CHECK-NEXT: dim = ( 10 )
+ // CHECK-NEXT: lvl = ( 10 )
+ // CHECK-NEXT: pos[0] : ( 0, 3
+ // CHECK-NEXT: crd[0] : ( 1, 3, 9
+ // CHECK-NEXT: values : ( 1, 2, 5
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 4
+ // CHECK-NEXT: dim = ( 5, 5 )
+ // CHECK-NEXT: lvl = ( 5, 5 )
+ // CHECK-NEXT: pos[1] : ( 0, 1, 2, 3, 4, 4
+ // CHECK-NEXT: crd[1] : ( 3, 4, 3, 4
+ // CHECK-NEXT: values : ( 1, 2, 4, 6
+ // CHECK-NEXT: ----
//
- call @dump_vec(%sv1) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump_mat(%sm1) : (tensor<?x?xf64, #CSR>) -> ()
- call @dump_vec(%1) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump_mat(%2) : (tensor<?x?xf64, #CSR>) -> ()
+ sparse_tensor.print %sv1 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %sm1 : tensor<?x?xf64, #CSR>
+ sparse_tensor.print %1 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %2 : tensor<?x?xf64, #CSR>
// Release the resources.
bufferization.dealloc_tensor %sv1 : tensor<?xf64, #SparseVector>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_semiring_select.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_semiring_select.mlir
index 6244be0ba7ab64..f4435c81117b2d 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_semiring_select.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_semiring_select.mlir
@@ -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}
//
@@ -60,7 +60,7 @@ module {
}
// Driver method to call and verify vector kernels.
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%f0 = arith.constant 0.0 : f64
@@ -86,20 +86,24 @@ module {
tensor<5x5xf64, #DCSR>) -> tensor<5x5xf64, #DCSR>
- // CHECK: ( ( 0.1, 1.1, 0, 0, 0 ),
- // CHECK-SAME: ( 0, 1.1, 2.2, 0, 0 ),
- // CHECK-SAME: ( 0, 0, 2.1, 3.3, 0 ),
- // CHECK-SAME: ( 0, 0, 0, 3.1, 4.4 ),
- // CHECK-SAME: ( 0, 0, 0, 0, 4.1 ) )
- %r = sparse_tensor.convert %1 : tensor<5x5xf64, #DCSR> to tensor<5x5xf64>
- %v2 = vector.transfer_read %r[%c0, %c0], %f0 : tensor<5x5xf64>, vector<5x5xf64>
- vector.print %v2 : vector<5x5xf64>
+ //
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 9
+ // CHECK-NEXT: dim = ( 5, 5 )
+ // CHECK-NEXT: lvl = ( 5, 5 )
+ // CHECK-NEXT: pos[0] : ( 0, 5
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4
+ // CHECK-NEXT: pos[1] : ( 0, 2, 4, 6, 8, 9
+ // CHECK-NEXT: crd[1] : ( 0, 1, 1, 2, 2, 3, 3, 4, 4
+ // CHECK-NEXT: values : ( 0.1, 1.1, 1.1, 2.2, 2.1, 3.3, 3.1, 4.4, 4.1
+ // CHECK-NEXT: ----
+ //
+ sparse_tensor.print %1 : tensor<5x5xf64, #DCSR>
// Release the resources.
bufferization.dealloc_tensor %sl: tensor<5x5xf64, #DCSR>
bufferization.dealloc_tensor %sr: tensor<5x5xf64, #DCSR>
bufferization.dealloc_tensor %1: tensor<5x5xf64, #DCSR>
- bufferization.dealloc_tensor %r : tensor<5x5xf64>
return
}
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sign.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sign.mlir
index 08e75dfa2c02ca..c09374918b7d6a 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sign.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sign.mlir
@@ -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}
//
@@ -79,7 +79,7 @@ module {
}
// Driver method to call and verify sign kernel.
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%du = arith.constant 0.0 : f64
@@ -110,11 +110,16 @@ module {
//
// Verify the results.
//
- // CHECK: ( -1, 1, -1, 1, 1, -1, nan, -nan, 1, -1, -0, 0, 0 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 12
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 12
+ // CHECK-NEXT: crd[0] : ( 0, 3, 5, 11, 13, 17, 18, 20, 21, 28, 29, 31
+ // CHECK-NEXT: values : ( -1, 1, -1, 1, 1, -1, nan, -nan, 1, -1, -0, 0
+ // CHECK-NEXT: ----
//
- %1 = sparse_tensor.values %0 : tensor<?xf64, #SparseVector> to memref<?xf64>
- %2 = vector.transfer_read %1[%c0], %du: memref<?xf64>, vector<13xf64>
- vector.print %2 : vector<13xf64>
+ sparse_tensor.print %0 : tensor<?xf64, #SparseVector>
// Release the resources.
bufferization.dealloc_tensor %sv1 : tensor<?xf64, #SparseVector>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir
index e0111f692601f0..7b3f9a2ce0e012 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir
@@ -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}
//
@@ -35,19 +35,19 @@
!Filename = !llvm.ptr
#SortedCOO = #sparse_tensor.encoding<{
- map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton(soa))
}>
#SortedCOOPermuted = #sparse_tensor.encoding<{
- map = (d0, d1) -> (d1 : compressed(nonunique), d0 : singleton),
+ map = (d0, d1) -> (d1 : compressed(nonunique), d0 : singleton(soa)),
}>
#SortedCOO3D = #sparse_tensor.encoding<{
- map = (d0, d1, d2) -> (d0 : compressed(nonunique), d1 : singleton(nonunique), d2 : singleton)
+ map = (d0, d1, d2) -> (d0 : compressed(nonunique), d1 : singleton(nonunique, soa), d2 : singleton(soa))
}>
#SortedCOO3DPermuted = #sparse_tensor.encoding<{
- map = (d0, d1, d2) -> (d2 : compressed(nonunique), d0 : singleton(nonunique), d1 : singleton)
+ map = (d0, d1, d2) -> (d2 : compressed(nonunique), d0 : singleton(nonunique, soa), d1 : singleton(soa))
}>
@@ -82,29 +82,7 @@ module {
return %0 : tensor<?x?xf64, #SortedCOO>
}
- func.func @dumpi(%arg0: memref<?xindex>) {
- %c0 = arith.constant 0 : index
- %v = vector.transfer_read %arg0[%c0], %c0: memref<?xindex>, vector<20xindex>
- vector.print %v : vector<20xindex>
- return
- }
-
- func.func @dumpsi(%arg0: memref<?xindex, strided<[?], offset: ?>>) {
- %c0 = arith.constant 0 : index
- %v = vector.transfer_read %arg0[%c0], %c0: memref<?xindex, strided<[?], offset: ?>>, vector<20xindex>
- vector.print %v : vector<20xindex>
- return
- }
-
- func.func @dumpf(%arg0: memref<?xf64>) {
- %c0 = arith.constant 0 : index
- %nan = arith.constant 0x0 : f64
- %v = vector.transfer_read %arg0[%c0], %nan: memref<?xf64>, vector<20xf64>
- vector.print %v : vector<20xf64>
- return
- }
-
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
@@ -125,130 +103,88 @@ module {
%4 = sparse_tensor.convert %m : tensor<5x4xf64> to tensor<?x?xf64, #SortedCOO>
//
- // CHECK: ( 0, 17, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 0, 0, 1, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 126, 127, 254, 1, 253, 2, 0, 1, 3, 98, 126, 127, 128, 249, 253, 255, 0, 0, 0 )
- // CHECK-NEXT: ( -1, 2, -3, 4, -5, 6, -7, 8, -9, 10, -11, 12, -13, 14, -15, 16, -17, 0, 0, 0 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 17
+ // CHECK-NEXT: dim = ( 4, 256 )
+ // CHECK-NEXT: lvl = ( 4, 256 )
+ // CHECK-NEXT: pos[0] : ( 0, 17
+ // CHECK-NEXT: crd[0] : ( 0, 0, 0, 0, 1, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3
+ // CHECK-NEXT: crd[1] : ( 0, 126, 127, 254, 1, 253, 2, 0, 1, 3, 98, 126, 127, 128, 249, 253, 255
+ // CHECK-NEXT: values : ( -1, 2, -3, 4, -5, 6, -7, 8, -9, 10, -11, 12, -13, 14, -15, 16, -17
+ // CHECK-NEXT: ----
//
- %p0 = sparse_tensor.positions %0 { level = 0 : index }
- : tensor<?x?xf64, #SortedCOO> to memref<?xindex>
- %i00 = sparse_tensor.coordinates %0 { level = 0 : index }
- : tensor<?x?xf64, #SortedCOO> to memref<?xindex, strided<[?], offset: ?>>
- %i01 = sparse_tensor.coordinates %0 { level = 1 : index }
- : tensor<?x?xf64, #SortedCOO> to memref<?xindex, strided<[?], offset: ?>>
- %v0 = sparse_tensor.values %0
- : tensor<?x?xf64, #SortedCOO> to memref<?xf64>
- call @dumpi(%p0) : (memref<?xindex>) -> ()
- call @dumpsi(%i00) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpsi(%i01) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpf(%v0) : (memref<?xf64>) -> ()
+ sparse_tensor.print %0 : tensor<?x?xf64, #SortedCOO>
//
- // CHECK-NEXT: ( 0, 17, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 1, 1, 2, 3, 98, 126, 126, 127, 127, 128, 249, 253, 253, 254, 255, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 3, 1, 3, 2, 3, 3, 0, 3, 0, 3, 3, 3, 1, 3, 0, 3, 0, 0, 0 )
- // CHECK-NEXT: ( -1, 8, -5, -9, -7, 10, -11, 2, 12, -3, -13, 14, -15, 6, 16, 4, -17, 0, 0, 0 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 17
+ // CHECK-NEXT: dim = ( 4, 256 )
+ // CHECK-NEXT: lvl = ( 256, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 17
+ // CHECK-NEXT: crd[0] : ( 0, 0, 1, 1, 2, 3, 98, 126, 126, 127, 127, 128, 249, 253, 253, 254, 255
+ // CHECK-NEXT: crd[1] : ( 0, 3, 1, 3, 2, 3, 3, 0, 3, 0, 3, 3, 3, 1, 3, 0, 3
+ // CHECK-NEXT: values : ( -1, 8, -5, -9, -7, 10, -11, 2, 12, -3, -13, 14, -15, 6, 16, 4, -17
+ // CHECK-NEXT: ----
//
- %p1 = sparse_tensor.positions %1 { level = 0 : index }
- : tensor<?x?xf64, #SortedCOOPermuted> to memref<?xindex>
- %i10 = sparse_tensor.coordinates %1 { level = 0 : index }
- : tensor<?x?xf64, #SortedCOOPermuted> to memref<?xindex, strided<[?], offset: ?>>
- %i11 = sparse_tensor.coordinates %1 { level = 1 : index }
- : tensor<?x?xf64, #SortedCOOPermuted> to memref<?xindex, strided<[?], offset: ?>>
- %v1 = sparse_tensor.values %1
- : tensor<?x?xf64, #SortedCOOPermuted> to memref<?xf64>
- call @dumpi(%p1) : (memref<?xindex>) -> ()
- call @dumpsi(%i10) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpsi(%i11) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpf(%v1) : (memref<?xf64>) -> ()
+ sparse_tensor.print %1 : tensor<?x?xf64, #SortedCOOPermuted>
//
- // CHECK-NEXT: ( 0, 17, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 1, 1, 2, 2, 2, 2, 0, 0, 0, 1, 1, 1, 1, 2, 2, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 1, 1, 2, 2, 2, 2, 0, 0, 0, 1, 1, 1, 1, 2, 2, 0, 0, 0 )
- // CHECK-NEXT: ( 3, 63, 11, 100, 66, 61, 13, 43, 77, 10, 46, 61, 53, 3, 75, 22, 18, 0, 0, 0 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 17
+ // CHECK-NEXT: dim = ( 2, 3, 4 )
+ // CHECK-NEXT: lvl = ( 2, 3, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 17
+ // CHECK-NEXT: crd[0] : ( 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1
+ // CHECK-NEXT: crd[1] : ( 0, 0, 1, 1, 2, 2, 2, 2, 0, 0, 0, 1, 1, 1, 1, 2, 2
+ // CHECK-NEXT: crd[2] : ( 2, 3, 1, 2, 0, 1, 2, 3, 0, 2, 3, 0, 1, 2, 3, 1, 2
+ // CHECK-NEXT: values : ( 3, 63, 11, 100, 66, 61, 13, 43, 77, 10, 46, 61, 53, 3, 75, 22, 18
+ // CHECK-NEXT: ----
//
- %p2 = sparse_tensor.positions %2 { level = 0 : index }
- : tensor<?x?x?xf64, #SortedCOO3D> to memref<?xindex>
- %i20 = sparse_tensor.coordinates %2 { level = 0 : index }
- : tensor<?x?x?xf64, #SortedCOO3D> to memref<?xindex, strided<[?], offset: ?>>
- %i21 = sparse_tensor.coordinates %2 { level = 1 : index }
- : tensor<?x?x?xf64, #SortedCOO3D> to memref<?xindex, strided<[?], offset: ?>>
- %i22 = sparse_tensor.coordinates %2 { level = 2 : index }
- : tensor<?x?x?xf64, #SortedCOO3D> to memref<?xindex, strided<[?], offset: ?>>
- %v2 = sparse_tensor.values %2
- : tensor<?x?x?xf64, #SortedCOO3D> to memref<?xf64>
- call @dumpi(%p2) : (memref<?xindex>) -> ()
- call @dumpsi(%i20) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpsi(%i21) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpsi(%i21) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpf(%v2) : (memref<?xf64>) -> ()
+ sparse_tensor.print %2 : tensor<?x?x?xf64, #SortedCOO3D>
//
- // CHECK-NEXT: ( 0, 17, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0 )
- // CHECK-NEXT: ( 66, 77, 61, 11, 61, 53, 22, 3, 100, 13, 10, 3, 18, 63, 43, 46, 75, 0, 0, 0 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 17
+ // CHECK-NEXT: dim = ( 2, 3, 4 )
+ // CHECK-NEXT: lvl = ( 4, 2, 3 )
+ // CHECK-NEXT: pos[0] : ( 0, 17
+ // CHECK-NEXT: crd[0] : ( 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3
+ // CHECK-NEXT: crd[1] : ( 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1
+ // CHECK-NEXT: crd[2] : ( 2, 0, 1, 1, 2, 1, 2, 0, 1, 2, 0, 1, 2, 0, 2, 0, 1
+ // CHECK-NEXT: values : ( 66, 77, 61, 11, 61, 53, 22, 3, 100, 13, 10, 3, 18, 63, 43, 46, 75
+ // CHECK-NEXT: ----
//
- %p3 = sparse_tensor.positions %3 { level = 0 : index }
- : tensor<?x?x?xf64, #SortedCOO3DPermuted> to memref<?xindex>
- %i30 = sparse_tensor.coordinates %3 { level = 0 : index }
- : tensor<?x?x?xf64, #SortedCOO3DPermuted> to memref<?xindex, strided<[?], offset: ?>>
- %i31 = sparse_tensor.coordinates %3 { level = 1 : index }
- : tensor<?x?x?xf64, #SortedCOO3DPermuted> to memref<?xindex, strided<[?], offset: ?>>
- %i32 = sparse_tensor.coordinates %3 { level = 2 : index }
- : tensor<?x?x?xf64, #SortedCOO3DPermuted> to memref<?xindex, strided<[?], offset: ?>>
- %v3 = sparse_tensor.values %3
- : tensor<?x?x?xf64, #SortedCOO3DPermuted> to memref<?xf64>
- call @dumpi(%p3) : (memref<?xindex>) -> ()
- call @dumpsi(%i30) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpsi(%i31) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpsi(%i31) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpf(%v3) : (memref<?xf64>) -> ()
+ sparse_tensor.print %3 : tensor<?x?x?xf64, #SortedCOO3DPermuted>
//
- // CHECK-NEXT: ( 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 1, 2, 2, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 3, 0, 3, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 6, 5, 4, 3, 2, 11, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 6
+ // CHECK-NEXT: dim = ( 5, 4 )
+ // CHECK-NEXT: lvl = ( 5, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 6
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 2, 3, 4
+ // CHECK-NEXT: crd[1] : ( 0, 3, 0, 3, 1, 1
+ // CHECK-NEXT: values : ( 6, 5, 4, 3, 2, 11
+ // CHECK-NEXT: ----
//
- %p4 = sparse_tensor.positions %4 { level = 0 : index }
- : tensor<?x?xf64, #SortedCOO> to memref<?xindex>
- %i40 = sparse_tensor.coordinates %4 { level = 0 : index }
- : tensor<?x?xf64, #SortedCOO> to memref<?xindex, strided<[?], offset: ?>>
- %i41 = sparse_tensor.coordinates %4 { level = 1 : index }
- : tensor<?x?xf64, #SortedCOO> to memref<?xindex, strided<[?], offset: ?>>
- %v4 = sparse_tensor.values %4
- : tensor<?x?xf64, #SortedCOO> to memref<?xf64>
- call @dumpi(%p4) : (memref<?xindex>) -> ()
- call @dumpsi(%i40) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpsi(%i41) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpf(%v4) : (memref<?xf64>) -> ()
+ sparse_tensor.print %4 : tensor<?x?xf64, #SortedCOO>
// And last but not least, an actual operation applied to COO.
// Note that this performs the operation "in place".
%5 = call @sparse_scale(%4) : (tensor<?x?xf64, #SortedCOO>) -> tensor<?x?xf64, #SortedCOO>
//
- // CHECK-NEXT: ( 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 1, 2, 2, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 3, 0, 3, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 12, 10, 8, 6, 4, 22, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 6
+ // CHECK-NEXT: dim = ( 5, 4 )
+ // CHECK-NEXT: lvl = ( 5, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 6
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 2, 3, 4
+ // CHECK-NEXT: crd[1] : ( 0, 3, 0, 3, 1, 1
+ // CHECK-NEXT: values : ( 12, 10, 8, 6, 4, 22
+ // CHECK-NEXT: ----
//
- %p5 = sparse_tensor.positions %5 { level = 0 : index }
- : tensor<?x?xf64, #SortedCOO> to memref<?xindex>
- %i50 = sparse_tensor.coordinates %5 { level = 0 : index }
- : tensor<?x?xf64, #SortedCOO> to memref<?xindex, strided<[?], offset: ?>>
- %i51 = sparse_tensor.coordinates %5 { level = 1 : index }
- : tensor<?x?xf64, #SortedCOO> to memref<?xindex, strided<[?], offset: ?>>
- %v5 = sparse_tensor.values %5
- : tensor<?x?xf64, #SortedCOO> to memref<?xf64>
- call @dumpi(%p5) : (memref<?xindex>) -> ()
- call @dumpsi(%i50) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpsi(%i51) : (memref<?xindex, strided<[?], offset: ?>>) -> ()
- call @dumpf(%v5) : (memref<?xf64>) -> ()
+ sparse_tensor.print %5 : tensor<?x?xf64, #SortedCOO>
// Release the resources.
bufferization.dealloc_tensor %0 : tensor<?x?xf64, #SortedCOO>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
index 573b1a2aac2598..ca8bcd7744c8f4 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
@@ -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}
//
@@ -76,7 +76,7 @@ module {
//
// Main driver that reads matrix from file and calls the sparse kernel.
//
- func.func @entry() {
+ func.func @main() {
%i0 = arith.constant 0.0 : f64
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_storage.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_storage.mlir
index 8ca95f2139e49a..2ee189de7906ca 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_storage.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_storage.mlir
@@ -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}
//
@@ -72,7 +72,7 @@ module {
// are typically not concerned with such details, but the test ensures
// everything is working "under the hood".
//
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%d0 = arith.constant 0.0 : f64
@@ -107,166 +107,103 @@ module {
//
// Inspect storage scheme of Dense.
//
- // CHECK: ( 1, 0, 2, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0,
- // CHECK-SAME: 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0,
- // CHECK-SAME: 0, 0, 0, 0, 6, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 9,
- // CHECK-SAME: 0, 0, 10, 0, 0, 0, 11, 12, 0, 13, 14, 0, 0, 0, 15, 16,
- // CHECK-SAME: 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 0 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 80
+ // CHECK-NEXT: dim = ( 10, 8 )
+ // CHECK-NEXT: lvl = ( 10, 8 )
+ // CHECK-NEXT: values : ( 1, 0, 2, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 9, 0, 0, 10, 0, 0, 0, 11, 12, 0, 13, 14, 0, 0, 0, 15, 16, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 0
+ // CHECK-NEXT: ----
//
- %5 = sparse_tensor.values %0 : tensor<10x8xf64, #Dense> to memref<?xf64>
- %6 = vector.transfer_read %5[%c0], %d0: memref<?xf64>, vector<80xf64>
- vector.print %6 : vector<80xf64>
+ sparse_tensor.print %0 : tensor<10x8xf64, #Dense>
//
// Inspect storage scheme of CSR.
//
- // positions(1)
- // indices(1)
- // values
//
- // CHECK: ( 0, 3, 3, 4, 5, 6, 9, 12, 16, 16, 17 )
- // CHECK: ( 0, 2, 7, 2, 3, 4, 1, 2, 7, 2, 6, 7, 1, 2, 6, 7, 6 )
- // CHECK: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 17
+ // CHECK-NEXT: dim = ( 10, 8 )
+ // CHECK-NEXT: lvl = ( 10, 8 )
+ // CHECK-NEXT: pos[1] : ( 0, 3, 3, 4, 5, 6, 9, 12, 16, 16, 17
+ // CHECK-NEXT: crd[1] : ( 0, 2, 7, 2, 3, 4, 1, 2, 7, 2, 6, 7, 1, 2, 6, 7, 6
+ // CHECK-NEXT: values : ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17
+ // CHECK-NEXT: ----
//
- %7 = sparse_tensor.positions %1 { level = 1 : index } : tensor<10x8xf64, #CSR> to memref<?xindex>
- %8 = vector.transfer_read %7[%c0], %c0: memref<?xindex>, vector<11xindex>
- vector.print %8 : vector<11xindex>
- %9 = sparse_tensor.coordinates %1 { level = 1 : index } : tensor<10x8xf64, #CSR> to memref<?xindex>
- %10 = vector.transfer_read %9[%c0], %c0: memref<?xindex>, vector<17xindex>
- vector.print %10 : vector<17xindex>
- %11 = sparse_tensor.values %1 : tensor<10x8xf64, #CSR> to memref<?xf64>
- %12 = vector.transfer_read %11[%c0], %d0: memref<?xf64>, vector<17xf64>
- vector.print %12 : vector<17xf64>
+ sparse_tensor.print %1 : tensor<10x8xf64, #CSR>
//
// Inspect storage scheme of DCSR.
//
- // positions(0)
- // indices(0)
- // positions(1)
- // indices(1)
- // values
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 17
+ // CHECK-NEXT: dim = ( 10, 8 )
+ // CHECK-NEXT: lvl = ( 10, 8 )
+ // CHECK-NEXT: pos[0] : ( 0, 8
+ // CHECK-NEXT: crd[0] : ( 0, 2, 3, 4, 5, 6, 7, 9
+ // CHECK-NEXT: pos[1] : ( 0, 3, 4, 5, 6, 9, 12, 16, 17
+ // CHECK-NEXT: crd[1] : ( 0, 2, 7, 2, 3, 4, 1, 2, 7, 2, 6, 7, 1, 2, 6, 7, 6
+ // CHECK-NEXT: values : ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17
+ // CHECK-NEXT: ----
//
- // CHECK: ( 0, 8 )
- // CHECK: ( 0, 2, 3, 4, 5, 6, 7, 9 )
- // CHECK: ( 0, 3, 4, 5, 6, 9, 12, 16, 17 )
- // CHECK: ( 0, 2, 7, 2, 3, 4, 1, 2, 7, 2, 6, 7, 1, 2, 6, 7, 6 )
- // CHECK: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 )
- //
- %13 = sparse_tensor.positions %2 { level = 0 : index } : tensor<10x8xf64, #DCSR> to memref<?xindex>
- %14 = vector.transfer_read %13[%c0], %c0: memref<?xindex>, vector<2xindex>
- vector.print %14 : vector<2xindex>
- %15 = sparse_tensor.coordinates %2 { level = 0 : index } : tensor<10x8xf64, #DCSR> to memref<?xindex>
- %16 = vector.transfer_read %15[%c0], %c0: memref<?xindex>, vector<8xindex>
- vector.print %16 : vector<8xindex>
- %17 = sparse_tensor.positions %2 { level = 1 : index } : tensor<10x8xf64, #DCSR> to memref<?xindex>
- %18 = vector.transfer_read %17[%c0], %c0: memref<?xindex>, vector<9xindex>
- vector.print %18 : vector<9xindex>
- %19 = sparse_tensor.coordinates %2 { level = 1 : index } : tensor<10x8xf64, #DCSR> to memref<?xindex>
- %20 = vector.transfer_read %19[%c0], %c0: memref<?xindex>, vector<17xindex>
- vector.print %20 : vector<17xindex>
- %21 = sparse_tensor.values %2 : tensor<10x8xf64, #DCSR> to memref<?xf64>
- %22 = vector.transfer_read %21[%c0], %d0: memref<?xf64>, vector<17xf64>
- vector.print %22 : vector<17xf64>
+ sparse_tensor.print %2 : tensor<10x8xf64, #DCSR>
//
// Inspect storage scheme of CSC.
//
- // positions(1)
- // indices(1)
- // values
- //
- // CHECK: ( 0, 1, 3, 8, 9, 10, 10, 13, 17 )
- // CHECK: ( 0, 5, 7, 0, 2, 5, 6, 7, 3, 4, 6, 7, 9, 0, 5, 6, 7 )
- // CHECK: ( 1, 7, 13, 2, 4, 8, 10, 14, 5, 6, 11, 15, 17, 3, 9, 12, 16 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 17
+ // CHECK-NEXT: dim = ( 10, 8 )
+ // CHECK-NEXT: lvl = ( 8, 10 )
+ // CHECK-NEXT: pos[1] : ( 0, 1, 3, 8, 9, 10, 10, 13, 17
+ // CHECK-NEXT: crd[1] : ( 0, 5, 7, 0, 2, 5, 6, 7, 3, 4, 6, 7, 9, 0, 5, 6, 7
+ // CHECK-NEXT: values : ( 1, 7, 13, 2, 4, 8, 10, 14, 5, 6, 11, 15, 17, 3, 9, 12, 16
+ // CHECK-NEXT: ----
//
- %23 = sparse_tensor.positions %3 { level = 1 : index } : tensor<10x8xf64, #CSC> to memref<?xindex>
- %24 = vector.transfer_read %23[%c0], %c0: memref<?xindex>, vector<9xindex>
- vector.print %24 : vector<9xindex>
- %25 = sparse_tensor.coordinates %3 { level = 1 : index } : tensor<10x8xf64, #CSC> to memref<?xindex>
- %26 = vector.transfer_read %25[%c0], %c0: memref<?xindex>, vector<17xindex>
- vector.print %26 : vector<17xindex>
- %27 = sparse_tensor.values %3 : tensor<10x8xf64, #CSC> to memref<?xf64>
- %28 = vector.transfer_read %27[%c0], %d0: memref<?xf64>, vector<17xf64>
- vector.print %28 : vector<17xf64>
+ sparse_tensor.print %3 : tensor<10x8xf64, #CSC>
//
// Inspect storage scheme of DCSC.
//
- // positions(0)
- // indices(0)
- // positions(1)
- // indices(1)
- // values
- //
- // CHECK: ( 0, 7 )
- // CHECK: ( 0, 1, 2, 3, 4, 6, 7 )
- // CHECK: ( 0, 1, 3, 8, 9, 10, 13, 17 )
- // CHECK: ( 0, 5, 7, 0, 2, 5, 6, 7, 3, 4, 6, 7, 9, 0, 5, 6, 7 )
- // CHECK: ( 1, 7, 13, 2, 4, 8, 10, 14, 5, 6, 11, 15, 17, 3, 9, 12, 16 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 17
+ // CHECK-NEXT: dim = ( 10, 8 )
+ // CHECK-NEXT: lvl = ( 8, 10 )
+ // CHECK-NEXT: pos[0] : ( 0, 7
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4, 6, 7
+ // CHECK-NEXT: pos[1] : ( 0, 1, 3, 8, 9, 10, 13, 17
+ // CHECK-NEXT: crd[1] : ( 0, 5, 7, 0, 2, 5, 6, 7, 3, 4, 6, 7, 9, 0, 5, 6, 7
+ // CHECK-NEXT: values : ( 1, 7, 13, 2, 4, 8, 10, 14, 5, 6, 11, 15, 17, 3, 9, 12, 16
+ // CHECK-NEXT: ----
//
- %29 = sparse_tensor.positions %4 { level = 0 : index } : tensor<10x8xf64, #DCSC> to memref<?xindex>
- %30 = vector.transfer_read %29[%c0], %c0: memref<?xindex>, vector<2xindex>
- vector.print %30 : vector<2xindex>
- %31 = sparse_tensor.coordinates %4 { level = 0 : index } : tensor<10x8xf64, #DCSC> to memref<?xindex>
- %32 = vector.transfer_read %31[%c0], %c0: memref<?xindex>, vector<7xindex>
- vector.print %32 : vector<7xindex>
- %33 = sparse_tensor.positions %4 { level = 1 : index } : tensor<10x8xf64, #DCSC> to memref<?xindex>
- %34 = vector.transfer_read %33[%c0], %c0: memref<?xindex>, vector<8xindex>
- vector.print %34 : vector<8xindex>
- %35 = sparse_tensor.coordinates %4 { level = 1 : index } : tensor<10x8xf64, #DCSC> to memref<?xindex>
- %36 = vector.transfer_read %35[%c0], %c0: memref<?xindex>, vector<17xindex>
- vector.print %36 : vector<17xindex>
- %37 = sparse_tensor.values %4 : tensor<10x8xf64, #DCSC> to memref<?xf64>
- %38 = vector.transfer_read %37[%c0], %d0: memref<?xf64>, vector<17xf64>
- vector.print %38 : vector<17xf64>
+ sparse_tensor.print %4 : tensor<10x8xf64, #DCSC>
//
// Inspect storage scheme of BlockRow.
//
- // positions(0)
- // indices(0)
- // values
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 64
+ // CHECK-NEXT: dim = ( 10, 8 )
+ // CHECK-NEXT: lvl = ( 10, 8 )
+ // CHECK-NEXT: pos[0] : ( 0, 8
+ // CHECK-NEXT: crd[0] : ( 0, 2, 3, 4, 5, 6, 7, 9
+ // CHECK-NEXT: values : ( 1, 0, 2, 0, 0, 0, 0, 3, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 9, 0, 0, 10, 0, 0, 0, 11, 12, 0, 13, 14, 0, 0, 0, 15, 16, 0, 0, 0, 0, 0, 0, 17, 0
+ // CHECK-NEXT: ----
//
- // CHECK: ( 0, 8 )
- // CHECK: ( 0, 2, 3, 4, 5, 6, 7, 9 )
- // CHECK: ( 1, 0, 2, 0, 0, 0, 0, 3, 0, 0, 4, 0, 0, 0, 0, 0,
- // CHECK-SAME: 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0,
- // CHECK-SAME: 0, 7, 8, 0, 0, 0, 0, 9, 0, 0, 10, 0, 0, 0, 11, 12,
- // CHECK-SAME: 0, 13, 14, 0, 0, 0, 15, 16, 0, 0, 0, 0, 0, 0, 17, 0 )
- //
- %39 = sparse_tensor.positions %x { level = 0 : index } : tensor<10x8xf64, #BlockRow> to memref<?xindex>
- %40 = vector.transfer_read %39[%c0], %c0: memref<?xindex>, vector<2xindex>
- vector.print %40 : vector<2xindex>
- %41 = sparse_tensor.coordinates %x { level = 0 : index } : tensor<10x8xf64, #BlockRow> to memref<?xindex>
- %42 = vector.transfer_read %41[%c0], %c0: memref<?xindex>, vector<8xindex>
- vector.print %42 : vector<8xindex>
- %43 = sparse_tensor.values %x : tensor<10x8xf64, #BlockRow> to memref<?xf64>
- %44 = vector.transfer_read %43[%c0], %d0: memref<?xf64>, vector<64xf64>
- vector.print %44 : vector<64xf64>
+ sparse_tensor.print %x : tensor<10x8xf64, #BlockRow>
//
// Inspect storage scheme of BlockCol.
//
- // positions(0)
- // indices(0)
- // values
- //
- // CHECK: ( 0, 7 )
- // CHECK: ( 0, 1, 2, 3, 4, 6, 7 )
- // CHECK: ( 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 13, 0, 0, 2, 0, 4, 0,
- // CHECK-SAME: 0, 8, 10, 14, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0,
- // CHECK-SAME: 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 15, 0, 17, 3, 0, 0, 0, 0, 9, 12, 16, 0, 0 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 70
+ // CHECK-NEXT: dim = ( 10, 8 )
+ // CHECK-NEXT: lvl = ( 8, 10 )
+ // CHECK-NEXT: pos[0] : ( 0, 7
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4, 6, 7
+ // CHECK-NEXT: values : ( 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 13, 0, 0, 2, 0, 4, 0, 0, 8, 10, 14, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 15, 0, 17, 3, 0, 0, 0, 0, 9, 12, 16, 0, 0
+ // CHECK-NEXT: ----
//
- %45 = sparse_tensor.positions %y { level = 0 : index } : tensor<10x8xf64, #BlockCol> to memref<?xindex>
- %46 = vector.transfer_read %45[%c0], %c0: memref<?xindex>, vector<2xindex>
- vector.print %46 : vector<2xindex>
- %47 = sparse_tensor.coordinates %y { level = 0 : index } : tensor<10x8xf64, #BlockCol> to memref<?xindex>
- %48 = vector.transfer_read %47[%c0], %c0: memref<?xindex>, vector<7xindex>
- vector.print %48 : vector<7xindex>
- %49 = sparse_tensor.values %y : tensor<10x8xf64, #BlockCol> to memref<?xf64>
- %50 = vector.transfer_read %49[%c0], %d0: memref<?xf64>, vector<70xf64>
- vector.print %50 : vector<70xf64>
+ sparse_tensor.print %y : tensor<10x8xf64, #BlockCol>
// Release the resources.
bufferization.dealloc_tensor %0 : tensor<10x8xf64, #Dense>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_strided_conv_2d_nhwc_hwcf.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_strided_conv_2d_nhwc_hwcf.mlir
index 5184083f665d56..2b2b8536fe39ed 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_strided_conv_2d_nhwc_hwcf.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_strided_conv_2d_nhwc_hwcf.mlir
@@ -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}
//
@@ -78,7 +78,7 @@ func.func @conv_2d_nhwc_hwcf_dual_CDCC(%arg0: tensor<?x?x?x?xf32, #CDCC>, %arg1:
}
-func.func @entry() {
+func.func @main() {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%c3 = arith.constant 3 : index
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir
index e6cbff231024ed..d1c58bfb6d59ef 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir
@@ -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}
//
@@ -75,7 +75,7 @@ module {
//
// Main driver that reads matrix from file and calls the sparse kernel.
//
- func.func @entry() {
+ func.func @main() {
%d0 = arith.constant 0.0 : f64
%c0 = arith.constant 0 : index
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir
index ee00a19a412306..16a8b50ab08e5c 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir
@@ -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}
//
@@ -67,7 +67,7 @@ module {
//
// Main driver that reads matrix from file and calls the sparse kernel.
//
- func.func @entry() {
+ func.func @main() {
// Setup input sparse matrix from compressed constant.
%d = arith.constant dense <[
[ 1.1, 1.2, 0.0, 1.4 ],
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir
index 5fdf636ef1230a..f95c163a57c164 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir
@@ -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}
//
@@ -75,7 +75,7 @@ module {
//
// Main driver that reads matrix from file and calls the sparse kernel.
//
- func.func @entry() {
+ func.func @main() {
//%d0 = arith.constant 0.0 : complex<f64>
%d0 = complex.constant [0.0 : f64, 0.0 : f64] : complex<f64>
%c0 = arith.constant 0 : index
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir
index 6a34695229495d..30be587c8f6119 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir
@@ -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}
//
@@ -66,7 +66,7 @@ module {
//
// Main driver that reads matrix from file and calls the sparse kernel.
//
- func.func @entry() {
+ func.func @main() {
// Setup input sparse matrix from compressed constant.
%d = arith.constant dense <[
[ 1.1, 1.2, 0.0, 1.4 ],
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tanh.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tanh.mlir
index 336044d5660057..29bc744c992032 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tanh.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tanh.mlir
@@ -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}
//
@@ -56,28 +56,8 @@ module {
return %0 : tensor<?xf64, #SparseVector>
}
- // Dumps a sparse vector of type f64.
- func.func @dump_vec_f64(%arg0: tensor<?xf64, #SparseVector>) {
- // Dump the values array to verify only sparse contents are stored.
- %c0 = arith.constant 0 : index
- %d0 = arith.constant -1.0 : f64
- %n = sparse_tensor.number_of_entries %arg0: tensor<?xf64, #SparseVector>
- vector.print %n : index
- %0 = sparse_tensor.values %arg0
- : tensor<?xf64, #SparseVector> to memref<?xf64>
- %1 = vector.transfer_read %0[%c0], %d0: memref<?xf64>, vector<9xf64>
- vector.print %1 : vector<9xf64>
- // Dump the dense vector to verify structure is correct.
- %dv = sparse_tensor.convert %arg0
- : tensor<?xf64, #SparseVector> to tensor<?xf64>
- %3 = vector.transfer_read %dv[%c0], %d0: tensor<?xf64>, vector<32xf64>
- vector.print %3 : vector<32xf64>
- bufferization.dealloc_tensor %dv : tensor<?xf64>
- return
- }
-
// Driver method to call and verify vector kernels.
- func.func @entry() {
+ func.func @main() {
// Setup sparse vector.
%v1 = arith.constant sparse<
[ [0], [3], [11], [17], [20], [21], [28], [29], [31] ],
@@ -93,11 +73,16 @@ module {
//
// Verify the results (within some precision).
//
- // CHECK: 9
- // CHECK-NEXT: {{( -0.761[0-9]*, 0.761[0-9]*, 0.96[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 1 )}}
- // CHECK-NEXT: {{( -0.761[0-9]*, 0, 0, 0.761[0-9]*, 0, 0, 0, 0, 0, 0, 0, 0.96[0-9]*, 0, 0, 0, 0, 0, 0.99[0-9]*, 0, 0, 0.99[0-9]*, 0.99[0-9]*, 0, 0, 0, 0, 0, 0, 0.99[0-9]*, 0.99[0-9]*, 0, 1 )}}
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 9
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 9
+ // CHECK-NEXT: crd[0] : ( 0, 3, 11, 17, 20, 21, 28, 29, 31
+ // CHECK-NEXT: values : ({{ -0.761[0-9]*, 0.761[0-9]*, 0.96[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 1}}
+ // CHECK-NEXT: ----
//
- call @dump_vec_f64(%0) : (tensor<?xf64, #SparseVector>) -> ()
+ sparse_tensor.print %0 : tensor<?xf64, #SparseVector>
// Release the resources.
bufferization.dealloc_tensor %sv1 : tensor<?xf64, #SparseVector>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_mul.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_mul.mlir
index d53b03025f5588..67155201c58442 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_mul.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_mul.mlir
@@ -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}
//
@@ -67,7 +67,7 @@ module {
}
// Driver method to call and verify tensor multiplication kernel.
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%default_val = arith.constant -1.0 : f64
@@ -103,30 +103,28 @@ module {
%0 = call @tensor_mul(%sta, %stb)
: (tensor<?x?x?xf64, #ST>, tensor<?x?x?xf64, #ST>) -> tensor<?x?x?xf64, #ST>
- // Verify results
//
- // CHECK: 4
- // CHECK-NEXT: ( 2.4, 3.5, 2, 8 )
- // CHECK-NEXT: ( ( ( 0, 0, 0, 0, 0 ), ( 0, 0, 0, 0, 0 ), ( 2.4, 0, 3.5, 0, 0 ) ),
- // CHECK-SAME: ( ( 0, 0, 0, 0, 0 ), ( 0, 0, 0, 0, 0 ), ( 0, 0, 0, 0, 0 ) ),
- // CHECK-SAME: ( ( 2, 0, 0, 0, 0 ), ( 0, 0, 0, 0, 0 ), ( 0, 0, 8, 0, 0 ) ) )
+ // Verify results.
//
- %n = sparse_tensor.number_of_entries %0 : tensor<?x?x?xf64, #ST>
- vector.print %n : index
- %m1 = sparse_tensor.values %0 : tensor<?x?x?xf64, #ST> to memref<?xf64>
- %v1 = vector.transfer_read %m1[%c0], %default_val: memref<?xf64>, vector<4xf64>
- vector.print %v1 : vector<4xf64>
-
- // Print %0 in dense form.
- %dt = sparse_tensor.convert %0 : tensor<?x?x?xf64, #ST> to tensor<?x?x?xf64>
- %v2 = vector.transfer_read %dt[%c0, %c0, %c0], %default_val: tensor<?x?x?xf64>, vector<3x3x5xf64>
- vector.print %v2 : vector<3x3x5xf64>
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 4
+ // CHECK-NEXT: dim = ( 3, 3, 5 )
+ // CHECK-NEXT: lvl = ( 3, 3, 5 )
+ // CHECK-NEXT: pos[0] : ( 0, 2
+ // CHECK-NEXT: crd[0] : ( 0, 2
+ // CHECK-NEXT: pos[1] : ( 0, 1, 3
+ // CHECK-NEXT: crd[1] : ( 2, 0, 2
+ // CHECK-NEXT: pos[2] : ( 0, 2, 3, 4
+ // CHECK-NEXT: crd[2] : ( 0, 2, 0, 2
+ // CHECK-NEXT: values : ( 2.4, 3.5, 2, 8
+ // CHECK-NEXT: ----
+ //
+ sparse_tensor.print %0 : tensor<?x?x?xf64, #ST>
// Release the resources.
bufferization.dealloc_tensor %sta : tensor<?x?x?xf64, #ST>
bufferization.dealloc_tensor %stb : tensor<?x?x?xf64, #ST>
bufferization.dealloc_tensor %0 : tensor<?x?x?xf64, #ST>
- bufferization.dealloc_tensor %dt : tensor<?x?x?xf64>
return
}
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_ops.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_ops.mlir
index 6ef6b393019a8e..356808ebee3f7c 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_ops.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_ops.mlir
@@ -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}
//
@@ -67,7 +67,7 @@ module {
}
// Driver method to call and verify tensor kernel.
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%d1 = arith.constant -1.0 : f64
@@ -90,22 +90,34 @@ module {
// Call sparse vector kernels.
%0 = call @tensor_scale(%st) : (tensor<?x?x?xf64, #ST1>) -> tensor<?x?x?xf64, #ST2>
+ //
// Sanity check on stored values.
//
- // CHECK: 5
- // CHECK-NEXT: ( 1, 2, 3, 4, 5 )
- // CHECK-NEXT: 24
- // CHECK-NEXT: ( 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 6, 8, 0, 0, 0, 0, 10 )
- %m1 = sparse_tensor.values %st : tensor<?x?x?xf64, #ST1> to memref<?xf64>
- %m2 = sparse_tensor.values %0 : tensor<?x?x?xf64, #ST2> to memref<?xf64>
- %n1 = sparse_tensor.number_of_entries %st : tensor<?x?x?xf64, #ST1>
- %n2 = sparse_tensor.number_of_entries %0 : tensor<?x?x?xf64, #ST2>
- %v1 = vector.transfer_read %m1[%c0], %d1: memref<?xf64>, vector<5xf64>
- %v2 = vector.transfer_read %m2[%c0], %d1: memref<?xf64>, vector<24xf64>
- vector.print %n1 : index
- vector.print %v1 : vector<5xf64>
- vector.print %n2 : index
- vector.print %v2 : vector<24xf64>
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 5
+ // CHECK-NEXT: dim = ( 3, 4, 8 )
+ // CHECK-NEXT: lvl = ( 3, 4, 8 )
+ // CHECK-NEXT: pos[0] : ( 0, 2
+ // CHECK-NEXT: crd[0] : ( 0, 2
+ // CHECK-NEXT: pos[1] : ( 0, 2, 3
+ // CHECK-NEXT: crd[1] : ( 0, 3, 2
+ // CHECK-NEXT: pos[2] : ( 0, 1, 2, 5
+ // CHECK-NEXT: crd[2] : ( 0, 7, 1, 2, 7
+ // CHECK-NEXT: values : ( 1, 2, 3, 4, 5
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 24
+ // CHECK-NEXT: dim = ( 3, 4, 8 )
+ // CHECK-NEXT: lvl = ( 3, 4, 8 )
+ // CHECK-NEXT: pos[0] : ( 0, 2
+ // CHECK-NEXT: crd[0] : ( 0, 2
+ // CHECK-NEXT: pos[1] : ( 0, 2, 3
+ // CHECK-NEXT: crd[1] : ( 0, 3, 2
+ // CHECK-NEXT: values : ( 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 6, 8, 0, 0, 0, 0, 10
+ // CHECK-NEXT: ----
+ //
+ sparse_tensor.print %st : tensor<?x?x?xf64, #ST1>
+ sparse_tensor.print %0 : tensor<?x?x?xf64, #ST2>
// Release the resources.
bufferization.dealloc_tensor %st : tensor<?x?x?xf64, #ST1>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose.mlir
index 185f6161493e04..549c2082fcb3ac 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose.mlir
@@ -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}
//
@@ -92,7 +92,7 @@ module {
//
// Main driver.
//
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%c4 = arith.constant 4 : index
@@ -115,26 +115,29 @@ module {
//
// Verify result.
//
- // CHECK: ( 1.1, 0, 3.1 )
- // CHECK-NEXT: ( 1.2, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 3.3 )
- // CHECK-NEXT: ( 1.4, 0, 3.4 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 6
+ // CHECK-NEXT: dim = ( 4, 3 )
+ // CHECK-NEXT: lvl = ( 4, 3 )
+ // CHECK-NEXT: pos[0] : ( 0, 4
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3
+ // CHECK-NEXT: pos[1] : ( 0, 2, 3, 4, 6
+ // CHECK-NEXT: crd[1] : ( 0, 2, 0, 2, 0, 2
+ // CHECK-NEXT: values : ( 1.1, 3.1, 1.2, 3.3, 1.4, 3.4
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 6
+ // CHECK-NEXT: dim = ( 4, 3 )
+ // CHECK-NEXT: lvl = ( 4, 3 )
+ // CHECK-NEXT: pos[0] : ( 0, 4
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3
+ // CHECK-NEXT: pos[1] : ( 0, 2, 3, 4, 6
+ // CHECK-NEXT: crd[1] : ( 0, 2, 0, 2, 0, 2
+ // CHECK-NEXT: values : ( 1.1, 3.1, 1.2, 3.3, 1.4, 3.4
+ // CHECK-NEXT: ----
//
- // CHECK-NEXT: ( 1.1, 0, 3.1 )
- // CHECK-NEXT: ( 1.2, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 3.3 )
- // CHECK-NEXT: ( 1.4, 0, 3.4 )
- //
- %x = sparse_tensor.convert %0 : tensor<4x3xf64, #DCSR> to tensor<4x3xf64>
- scf.for %i = %c0 to %c4 step %c1 {
- %v1 = vector.transfer_read %x[%i, %c0], %du: tensor<4x3xf64>, vector<3xf64>
- vector.print %v1 : vector<3xf64>
- }
- %y = sparse_tensor.convert %1 : tensor<4x3xf64, #DCSR> to tensor<4x3xf64>
- scf.for %i = %c0 to %c4 step %c1 {
- %v2 = vector.transfer_read %y[%i, %c0], %du: tensor<4x3xf64>, vector<3xf64>
- vector.print %v2 : vector<3xf64>
- }
+ sparse_tensor.print %0 : tensor<4x3xf64, #DCSR>
+ sparse_tensor.print %1 : tensor<4x3xf64, #DCSR>
// Release resources.
bufferization.dealloc_tensor %a : tensor<3x4xf64, #DCSR>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose_coo.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose_coo.mlir
index dba897334830ad..cc6f6a068746d0 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose_coo.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose_coo.mlir
@@ -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}
//
@@ -31,7 +31,7 @@
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %}
#SortedCOO = #sparse_tensor.encoding<{
- map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
+ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton(soa))
}>
module {
@@ -52,7 +52,7 @@ module {
return %1 : tensor<5x10xf32, #SortedCOO>
}
- func.func @entry() {
+ func.func @main() {
%f0 = arith.constant 0.0 : f32
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
@@ -79,17 +79,27 @@ module {
//
// Verify original and transposed sorted COO.
//
- // CHECK: ( 10, 20, 30, 40, 50, 11, 21, 31, 41, 51, 12, 22, 32, 42, 52, 13, 23, 33, 43, 53, 14, 24, 34, 44, 54, 15, 25, 35, 45, 55, 16, 26, 36, 46, 56, 17, 27, 37, 47, 57, 18, 28, 38, 48, 58, 19, 29, 39, 49, 59 )
- // CHECK-NEXT: ( 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, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 50
+ // CHECK-NEXT: dim = ( 10, 5 )
+ // CHECK-NEXT: lvl = ( 10, 5 )
+ // CHECK-NEXT: pos[0] : ( 0, 50
+ // CHECK-NEXT: crd[0] : ( 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9
+ // CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4
+ // CHECK-NEXT: values : ( 10, 20, 30, 40, 50, 11, 21, 31, 41, 51, 12, 22, 32, 42, 52, 13, 23, 33, 43, 53, 14, 24, 34, 44, 54, 15, 25, 35, 45, 55, 16, 26, 36, 46, 56, 17, 27, 37, 47, 57, 18, 28, 38, 48, 58, 19, 29, 39, 49, 59
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 50
+ // CHECK-NEXT: dim = ( 5, 10 )
+ // CHECK-NEXT: lvl = ( 5, 10 )
+ // CHECK-NEXT: pos[0] : ( 0, 50
+ // CHECK-NEXT: crd[0] : ( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4
+ // CHECK-NEXT: crd[1] : ( 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9
+ // CHECK-NEXT: values : ( 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, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59
+ // CHECK-NEXT: ----
//
- %va = sparse_tensor.values %SA
- : tensor<10x5xf32, #SortedCOO> to memref<?xf32>
- %vat = sparse_tensor.values %SAT
- : tensor<5x10xf32, #SortedCOO> to memref<?xf32>
- %v1 = vector.transfer_read %va[%c0], %f0 : memref<?xf32>, vector<50xf32>
- %v2 = vector.transfer_read %vat[%c0], %f0 : memref<?xf32>, vector<50xf32>
- vector.print %v1 : vector<50xf32>
- vector.print %v2 : vector<50xf32>
+ sparse_tensor.print %SA : tensor<10x5xf32, #SortedCOO>
+ sparse_tensor.print %SAT : tensor<5x10xf32, #SortedCOO>
// Release resources.
bufferization.dealloc_tensor %SA : tensor<10x5xf32, #SortedCOO>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_unary.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_unary.mlir
index e03f99253b7845..3da1e35818cfa5 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_unary.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_unary.mlir
@@ -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}
//
@@ -204,54 +204,8 @@ module {
return %0 : tensor<?x?xf64, #DCSR>
}
- // Dumps a sparse vector of type f64.
- func.func @dump_vec_f64(%arg0: tensor<?xf64, #SparseVector>) {
- // Dump the values array to verify only sparse contents are stored.
- %c0 = arith.constant 0 : index
- %d0 = arith.constant 0.0 : f64
- %0 = sparse_tensor.values %arg0 : tensor<?xf64, #SparseVector> to memref<?xf64>
- %1 = vector.transfer_read %0[%c0], %d0: memref<?xf64>, vector<32xf64>
- vector.print %1 : vector<32xf64>
- // Dump the dense vector to verify structure is correct.
- %dv = sparse_tensor.convert %arg0 : tensor<?xf64, #SparseVector> to tensor<?xf64>
- %3 = vector.transfer_read %dv[%c0], %d0: tensor<?xf64>, vector<32xf64>
- vector.print %3 : vector<32xf64>
- bufferization.dealloc_tensor %dv : tensor<?xf64>
- return
- }
-
- // Dumps a sparse vector of type i32.
- func.func @dump_vec_i32(%arg0: tensor<?xi32, #SparseVector>) {
- // Dump the values array to verify only sparse contents are stored.
- %c0 = arith.constant 0 : index
- %d0 = arith.constant 0 : i32
- %0 = sparse_tensor.values %arg0 : tensor<?xi32, #SparseVector> to memref<?xi32>
- %1 = vector.transfer_read %0[%c0], %d0: memref<?xi32>, vector<24xi32>
- vector.print %1 : vector<24xi32>
- // Dump the dense vector to verify structure is correct.
- %dv = sparse_tensor.convert %arg0 : tensor<?xi32, #SparseVector> to tensor<?xi32>
- %3 = vector.transfer_read %dv[%c0], %d0: tensor<?xi32>, vector<32xi32>
- vector.print %3 : vector<32xi32>
- bufferization.dealloc_tensor %dv : tensor<?xi32>
- return
- }
-
- // Dump a sparse matrix.
- func.func @dump_mat(%arg0: tensor<?x?xf64, #DCSR>) {
- %c0 = arith.constant 0 : index
- %d0 = arith.constant 0.0 : f64
- %0 = sparse_tensor.values %arg0 : tensor<?x?xf64, #DCSR> to memref<?xf64>
- %1 = vector.transfer_read %0[%c0], %d0: memref<?xf64>, vector<16xf64>
- vector.print %1 : vector<16xf64>
- %dm = sparse_tensor.convert %arg0 : tensor<?x?xf64, #DCSR> to tensor<?x?xf64>
- %3 = vector.transfer_read %dm[%c0, %c0], %d0: tensor<?x?xf64>, vector<4x8xf64>
- vector.print %3 : vector<4x8xf64>
- bufferization.dealloc_tensor %dm : tensor<?x?xf64>
- return
- }
-
// Driver method to call and verify vector kernels.
- func.func @entry() {
+ func.func @main() {
%cmu = arith.constant -99 : i32
%c0 = arith.constant 0 : index
@@ -289,26 +243,66 @@ module {
//
// Verify the results.
//
- // CHECK: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 7, 8, 0, 9 )
- // CHECK-NEXT: ( 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0 )
- // CHECK-NEXT: ( 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0 )
- // CHECK-NEXT: ( -1, 1, 1, -2, 1, 1, 1, 1, 1, 1, 1, -3, 1, 1, 1, 1, 1, -4, 1, 1, -5, -6, 1, 1, 1, 1, 1, 1, -7, -8, 1, -9 )
- // CHECK-NEXT: ( -1, 1, 1, -2, 1, 1, 1, 1, 1, 1, 1, -3, 1, 1, 1, 1, 1, -4, 1, 1, -5, -6, 1, 1, 1, 1, 1, 1, -7, -8, 1, -9 )
- // CHECK-NEXT: ( 0, 6, 33, 68, 100, 126, 196, 232, 279, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0, 33, 0, 0, 0, 0, 0, 68, 0, 0, 100, 126, 0, 0, 0, 0, 0, 0, 196, 232, 0, 279 )
- // CHECK-NEXT: ( 3, 3, 3, 4, 5, 6, 7, 7, 7, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( ( 3, 3, 0, 0, 0, 0, 0, 0 ), ( 0, 0, 0, 0, 0, 0, 0, 3 ), ( 0, 0, 4, 0, 5, 0, 0, 6 ), ( 7, 0, 7, 7, 0, 0, 0, 0 ) )
- // CHECK-NEXT: ( 99, 99, 99, 99, 5, 6, 99, 99, 99, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( ( 99, 99, 0, 0, 0, 0, 0, 0 ), ( 0, 0, 0, 0, 0, 0, 0, 99 ), ( 0, 0, 99, 0, 5, 0, 0, 6 ), ( 99, 0, 99, 99, 0, 0, 0, 0 ) )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 9
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 9
+ // CHECK-NEXT: crd[0] : ( 0, 3, 11, 17, 20, 21, 28, 29, 31
+ // CHECK-NEXT: values : ( 1, 2, 3, 4, 5, 6, 7, 8, 9
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 23
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 23
+ // CHECK-NEXT: crd[0] : ( 1, 2, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 18, 19, 22, 23, 24, 25, 26, 27, 30
+ // CHECK-NEXT: values : ( 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 32
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 32
+ // CHECK-NEXT: crd[0] : ( 0, 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
+ // CHECK-NEXT: values : ( -1, 1, 1, -2, 1, 1, 1, 1, 1, 1, 1, -3, 1, 1, 1, 1, 1, -4, 1, 1, -5, -6, 1, 1, 1, 1, 1, 1, -7, -8, 1, -9
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 9
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 9
+ // CHECK-NEXT: crd[0] : ( 0, 3, 11, 17, 20, 21, 28, 29, 31
+ // CHECK-NEXT: values : ( 0, 6, 33, 68, 100, 126, 196, 232, 279
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 9
+ // CHECK-NEXT: dim = ( 4, 8 )
+ // CHECK-NEXT: lvl = ( 4, 8 )
+ // CHECK-NEXT: pos[0] : ( 0, 4
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3
+ // CHECK-NEXT: pos[1] : ( 0, 2, 3, 6, 9
+ // CHECK-NEXT: crd[1] : ( 0, 1, 7, 2, 4, 7, 0, 2, 3
+ // CHECK-NEXT: values : ( 3, 3, 3, 4, 5, 6, 7, 7, 7
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 9
+ // CHECK-NEXT: dim = ( 4, 8 )
+ // CHECK-NEXT: lvl = ( 4, 8 )
+ // CHECK-NEXT: pos[0] : ( 0, 4
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3
+ // CHECK-NEXT: pos[1] : ( 0, 2, 3, 6, 9
+ // CHECK-NEXT: crd[1] : ( 0, 1, 7, 2, 4, 7, 0, 2, 3
+ // CHECK-NEXT: values : ( 99, 99, 99, 99, 5, 6, 99, 99, 99
+ // CHECK-NEXT: ----
// CHECK-NEXT: ( 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0 )
//
- call @dump_vec_f64(%sv1) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump_vec_i32(%0) : (tensor<?xi32, #SparseVector>) -> ()
- call @dump_vec_f64(%1) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump_vec_f64(%2) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump_mat(%3) : (tensor<?x?xf64, #DCSR>) -> ()
- call @dump_mat(%4) : (tensor<?x?xf64, #DCSR>) -> ()
+ sparse_tensor.print %sv1 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %0 : tensor<?xi32, #SparseVector>
+ sparse_tensor.print %1 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %2 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %3 : tensor<?x?xf64, #DCSR>
+ sparse_tensor.print %4 : tensor<?x?xf64, #DCSR>
%v = vector.transfer_read %5[%c0], %cmu: tensor<?xi32>, vector<32xi32>
vector.print %v : vector<32xi32>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_vector_ops.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_vector_ops.mlir
index d9ca2dca85342a..55332333164130 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_vector_ops.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_vector_ops.mlir
@@ -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}
//
@@ -162,24 +162,8 @@ module {
return %0 : tensor<f64>
}
- // Dumps a sparse vector.
- func.func @dump(%arg0: tensor<?xf64, #SparseVector>) {
- // Dump the values array to verify only sparse contents are stored.
- %c0 = arith.constant 0 : index
- %d0 = arith.constant 0.0 : f64
- %0 = sparse_tensor.values %arg0 : tensor<?xf64, #SparseVector> to memref<?xf64>
- %1 = vector.transfer_read %0[%c0], %d0: memref<?xf64>, vector<16xf64>
- vector.print %1 : vector<16xf64>
- // Dump the dense vector to verify structure is correct.
- %dv = sparse_tensor.convert %arg0 : tensor<?xf64, #SparseVector> to tensor<?xf64>
- %2 = vector.transfer_read %dv[%c0], %d0: tensor<?xf64>, vector<32xf64>
- vector.print %2 : vector<32xf64>
- bufferization.dealloc_tensor %dv : tensor<?xf64>
- return
- }
-
// Driver method to call and verify vector kernels.
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%d1 = arith.constant 1.1 : f64
@@ -221,31 +205,69 @@ module {
//
// Verify the results.
//
- // CHECK: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 0, 0, 5, 6, 0, 0, 0, 0, 0, 0, 7, 8, 0, 9 )
- // CHECK-NEXT: ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 11, 0, 12, 13, 0, 0, 0, 0, 0, 14, 0, 0, 0, 0, 0, 15, 0, 16, 0, 0, 17, 0, 0, 0, 0, 0, 0, 18, 19, 0, 20 )
- // CHECK-NEXT: ( 2, 4, 6, 8, 10, 12, 14, 16, 18, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 2, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 8, 0, 0, 10, 12, 0, 0, 0, 0, 0, 0, 14, 16, 0, 18 )
- // CHECK-NEXT: ( 2, 4, 6, 8, 10, 12, 14, 16, 18, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 2, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 8, 0, 0, 10, 12, 0, 0, 0, 0, 0, 0, 14, 16, 0, 18 )
- // CHECK-NEXT: ( 2, 11, 16, 13, 14, 6, 15, 8, 16, 10, 29, 32, 35, 38, 0, 0 )
- // CHECK-NEXT: ( 2, 11, 0, 16, 13, 0, 0, 0, 0, 0, 14, 6, 0, 0, 0, 0, 15, 8, 16, 0, 10, 29, 0, 0, 0, 0, 0, 0, 32, 35, 0, 38 )
- // CHECK-NEXT: ( 48, 204, 252, 304, 360, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 0, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 204, 0, 0, 0, 0, 0, 0, 252, 304, 0, 360 )
- // CHECK-NEXT: ( 0, 0, 0, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 204, 0, 0, 0, 0, 0, 0, 252, 304, 0, 360 )
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 9
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 9
+ // CHECK-NEXT: crd[0] : ( 0, 3, 11, 17, 20, 21, 28, 29, 31
+ // CHECK-NEXT: values : ( 1, 2, 3, 4, 5, 6, 7, 8, 9
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 10
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 10
+ // CHECK-NEXT: crd[0] : ( 1, 3, 4, 10, 16, 18, 21, 28, 29, 31
+ // CHECK-NEXT: values : ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 9
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 9
+ // CHECK-NEXT: crd[0] : ( 0, 3, 11, 17, 20, 21, 28, 29, 31
+ // CHECK-NEXT: values : ( 2, 4, 6, 8, 10, 12, 14, 16, 18
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 9
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 9
+ // CHECK-NEXT: crd[0] : ( 0, 3, 11, 17, 20, 21, 28, 29, 31
+ // CHECK-NEXT: values : ( 2, 4, 6, 8, 10, 12, 14, 16, 18
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 14
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 14
+ // CHECK-NEXT: crd[0] : ( 0, 1, 3, 4, 10, 11, 16, 17, 18, 20, 21, 28, 29, 31
+ // CHECK-NEXT: values : ( 2, 11, 16, 13, 14, 6, 15, 8, 16, 10, 29, 32, 35, 38
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 5
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 5
+ // CHECK-NEXT: crd[0] : ( 3, 21, 28, 29, 31
+ // CHECK-NEXT: values : ( 48, 204, 252, 304, 360
+ // CHECK-NEXT: ----
+ // CHECK: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 32
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: values : ( 0, 0, 0, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 204, 0, 0, 0, 0, 0, 0, 252, 304, 0, 360
+ // CHECK-NEXT: ----
// CHECK-NEXT: 1169.1
//
-
- call @dump(%sv1) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump(%sv2) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump(%0) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump(%1) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump(%2) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump(%3) : (tensor<?xf64, #SparseVector>) -> ()
- %m4 = sparse_tensor.values %4 : tensor<?xf64, #DenseVector> to memref<?xf64>
- %v4 = vector.load %m4[%c0]: memref<?xf64>, vector<32xf64>
- vector.print %v4 : vector<32xf64>
+ sparse_tensor.print %sv1 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %sv2 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %0 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %1 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %2 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %3 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %4 : tensor<?xf64, #DenseVector>
%v5 = tensor.extract %5[] : tensor<f64>
vector.print %v5 : f64
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