[Mlir-commits] [mlir] [mlir][sparse] migration to sparse_tensor.print (PR #83926)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Mon Mar 4 15:25:14 PST 2024
llvmbot wrote:
<!--LLVM PR SUMMARY COMMENT-->
@llvm/pr-subscribers-mlir-sparse
@llvm/pr-subscribers-mlir
Author: Aart Bik (aartbik)
<details>
<summary>Changes</summary>
Continuing the efforts started in #<!-- -->83357
---
Full diff: https://github.com/llvm/llvm-project/pull/83926.diff
2 Files Affected:
- (modified) mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir (+21-16)
- (modified) mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir (+144-116)
``````````diff
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir
index 3c10e2662f868a..4228bcdb1c0d70 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_abs.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}
//
@@ -73,7 +73,7 @@ module {
}
// Driver method to call and verify sign kernel.
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
%df = arith.constant 99.99 : f64
%di = arith.constant 9999 : i32
@@ -116,21 +116,26 @@ module {
//
// Verify the results.
//
- // CHECK: 12
- // CHECK-NEXT: ( 1.5, 1.5, 10.2, 11.3, 1, 1, nan, nan, inf, inf, 0, 0 )
- // CHECK-NEXT: 9
- // CHECK-NEXT: ( -2147483648, 2147483647, 1000, 1, 0, 1, 1000, 2147483646, 2147483647 )
+ // 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 : ( 1.5, 1.5, 10.2, 11.3, 1, 1, nan, nan, inf, inf, 0, 0,
+ // CHECK-NEXT: ----
//
- %x = sparse_tensor.values %0 : tensor<?xf64, #SparseVector> to memref<?xf64>
- %y = sparse_tensor.values %1 : tensor<?xi32, #SparseVector> to memref<?xi32>
- %a = vector.transfer_read %x[%c0], %df: memref<?xf64>, vector<12xf64>
- %b = vector.transfer_read %y[%c0], %di: memref<?xi32>, vector<9xi32>
- %na = sparse_tensor.number_of_entries %0 : tensor<?xf64, #SparseVector>
- %nb = sparse_tensor.number_of_entries %1 : tensor<?xi32, #SparseVector>
- vector.print %na : index
- vector.print %a : vector<12xf64>
- vector.print %nb : index
- vector.print %b : vector<9xi32>
+ // CHECK-NEXT: ---- 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, 5, 11, 13, 17, 18, 21, 31,
+ // CHECK-NEXT: values : ( -2147483648, 2147483647, 1000, 1, 0, 1, 1000, 2147483646, 2147483647,
+ // CHECK-NEXT: ----
+ //
+ sparse_tensor.print %0 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %1 : tensor<?xi32, #SparseVector>
// Release the resources.
bufferization.dealloc_tensor %sv1 : tensor<?xf64, #SparseVector>
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir
index 59ecbfdef85043..36701b4385a2a8 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.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}
//
@@ -365,84 +365,8 @@ module {
return %0 : tensor<4x4xf64, #DCSR>
}
- //
- // Utility functions to dump the value of a tensor.
- //
-
- 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<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>
- %3 = vector.transfer_read %dv[%c0], %d0: tensor<?xf64>, vector<32xf64>
- vector.print %3 : vector<32xf64>
- bufferization.dealloc_tensor %dv : tensor<?xf64>
- return
- }
-
- 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
- }
-
- func.func @dump_mat(%arg0: tensor<?x?xf64, #DCSR>) {
- %d0 = arith.constant 0.0 : f64
- %c0 = arith.constant 0 : index
- %dm = sparse_tensor.convert %arg0 : tensor<?x?xf64, #DCSR> to tensor<?x?xf64>
- %1 = vector.transfer_read %dm[%c0, %c0], %d0: tensor<?x?xf64>, vector<4x8xf64>
- vector.print %1 : vector<4x8xf64>
- bufferization.dealloc_tensor %dm : tensor<?x?xf64>
- return
- }
-
- func.func @dump_mat_4x4(%A: tensor<4x4xf64, #DCSR>) {
- %c0 = arith.constant 0 : index
- %du = arith.constant 0.0 : f64
-
- %c = sparse_tensor.convert %A : tensor<4x4xf64, #DCSR> to tensor<4x4xf64>
- %v = vector.transfer_read %c[%c0, %c0], %du: tensor<4x4xf64>, vector<4x4xf64>
- vector.print %v : vector<4x4xf64>
-
- %1 = sparse_tensor.values %A : tensor<4x4xf64, #DCSR> to memref<?xf64>
- %2 = vector.transfer_read %1[%c0], %du: memref<?xf64>, vector<16xf64>
- vector.print %2 : vector<16xf64>
-
- bufferization.dealloc_tensor %c : tensor<4x4xf64>
- return
- }
-
- func.func @dump_mat_4x4_i8(%A: tensor<4x4xi8, #DCSR>) {
- %c0 = arith.constant 0 : index
- %du = arith.constant 0 : i8
-
- %c = sparse_tensor.convert %A : tensor<4x4xi8, #DCSR> to tensor<4x4xi8>
- %v = vector.transfer_read %c[%c0, %c0], %du: tensor<4x4xi8>, vector<4x4xi8>
- vector.print %v : vector<4x4xi8>
-
- %1 = sparse_tensor.values %A : tensor<4x4xi8, #DCSR> to memref<?xi8>
- %2 = vector.transfer_read %1[%c0], %du: memref<?xi8>, vector<16xi8>
- vector.print %2 : vector<16xi8>
-
- bufferization.dealloc_tensor %c : tensor<4x4xi8>
- return
- }
-
// Driver method to call and verify kernels.
- func.func @entry() {
+ func.func @main() {
%c0 = arith.constant 0 : index
// Setup sparse vectors.
@@ -525,45 +449,149 @@ 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: ( 1, 11, 2, 13, 14, 3, 15, 4, 16, 5, 6, 7, 8, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 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: ( 0, 6, 3, 28, 0, 6, 56, 72, 9, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 28, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 56, 72, 0, 9 )
- // CHECK-NEXT: ( 1, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 4, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 3, 11, 17, 20, 21, 28, 29, 31, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 11, 0, 0, 0, 0, 0, 17, 0, 0, 20, 21, 0, 0, 0, 0, 0, 0, 28, 29, 0, 31 )
- // CHECK-NEXT: ( ( 7, 0, 0, 0, 0, 0, 0, -5 ), ( -4, 0, 0, 0, 0, 0, -3, 0 ), ( 0, -2, 0, 0, 0, 0, 0, 7 ), ( 0, 0, 0, 0, 0, 0, 0, 0 ) )
- // CHECK-NEXT: ( ( 2, 0, 4, 1 ), ( 0, 2.5, 0, 0 ), ( 1, 5, 2, 4 ), ( 5, 4, 0, 0 ) )
- // CHECK-NEXT: ( 2, 4, 1, 2.5, 1, 5, 2, 4, 5, 4, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( ( 2, 0, 4, 1 ), ( 0, 2.5, 0, 0 ), ( 1, 5, 2, 4 ), ( 5, 4, 0, 0 ) )
- // CHECK-NEXT: ( 2, 4, 1, 2.5, 1, 5, 2, 4, 5, 4, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( ( 2, 0, 4, 1 ), ( 0, 2.5, 0, 0 ), ( -1, -5, 2, 4 ), ( 1, 4, 0, 0 ) )
- // CHECK-NEXT: ( 2, 4, 1, 2.5, -1, -5, 2, 4, 1, 4, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( ( 0, 0, 1, -1 ), ( 0, 1, 0, 0 ), ( -1, -2, -2, 2 ), ( 1, 2, 0, 0 ) )
- // CHECK-NEXT: ( 0, 1, -1, 1, -1, -2, -2, 2, 1, 2, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( ( 1, 0, 0, 0 ), ( 0, 0, 0, 0 ), ( 0, 0, 0, 0 ), ( 0, 0, 0, 0 ) )
- // CHECK-NEXT: ( 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 )
- // CHECK-NEXT: ( ( 0, 0, 0, -1 ), ( 0, 0, 0, 0 ), ( -1, -5, -2, 4 ), ( 0, 4, 0, 0 ) )
- // CHECK-NEXT: ( -1, -1, -5, -2, 4, 4, 0, 0, 0, 0, 0, 0, 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-NEXT: ---- 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-NEXT: ---- 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 : ( 1, 11, 2, 13, 14, 3, 15, 4, 16, 5, 6, 7, 8, 9,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- 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, 3, 28, 0, 6, 56, 72, 9,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 4
+ // CHECK-NEXT: dim = ( 32 )
+ // CHECK-NEXT: lvl = ( 32 )
+ // CHECK-NEXT: pos[0] : ( 0, 4,
+ // CHECK-NEXT: crd[0] : ( 0, 11, 17, 20,
+ // CHECK-NEXT: values : ( 1, 3, 4, 5,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- 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, 3, 11, 17, 20, 21, 28, 29, 31,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 6
+ // CHECK-NEXT: dim = ( 4, 8 )
+ // CHECK-NEXT: lvl = ( 4, 8 )
+ // CHECK-NEXT: pos[0] : ( 0, 3,
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2,
+ // CHECK-NEXT: pos[1] : ( 0, 2, 4, 6,
+ // CHECK-NEXT: crd[1] : ( 0, 7, 0, 6, 1, 7,
+ // CHECK-NEXT: values : ( 7, -5, -4, -3, -2, 7,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 10
+ // CHECK-NEXT: dim = ( 4, 4 )
+ // CHECK-NEXT: lvl = ( 4, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 4,
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3,
+ // CHECK-NEXT: pos[1] : ( 0, 3, 4, 8, 10,
+ // CHECK-NEXT: crd[1] : ( 0, 2, 3, 1, 0, 1, 2, 3, 0, 1,
+ // CHECK-NEXT: values : ( 2, 4, 1, 2.5, 1, 5, 2, 4, 5, 4,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 10
+ // CHECK-NEXT: dim = ( 4, 4 )
+ // CHECK-NEXT: lvl = ( 4, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 4,
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3,
+ // CHECK-NEXT: pos[1] : ( 0, 3, 4, 8, 10,
+ // CHECK-NEXT: crd[1] : ( 0, 2, 3, 1, 0, 1, 2, 3, 0, 1,
+ // CHECK-NEXT: values : ( 2, 4, 1, 2.5, 1, 5, 2, 4, 5, 4,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 10
+ // CHECK-NEXT: dim = ( 4, 4 )
+ // CHECK-NEXT: lvl = ( 4, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 4,
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3,
+ // CHECK-NEXT: pos[1] : ( 0, 3, 4, 8, 10,
+ // CHECK-NEXT: crd[1] : ( 0, 2, 3, 1, 0, 1, 2, 3, 0, 1,
+ // CHECK-NEXT: values : ( 2, 4, 1, 2.5, -1, -5, 2, 4, 1, 4,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 10
+ // CHECK-NEXT: dim = ( 4, 4 )
+ // CHECK-NEXT: lvl = ( 4, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 4,
+ // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3,
+ // CHECK-NEXT: pos[1] : ( 0, 3, 4, 8, 10,
+ // CHECK-NEXT: crd[1] : ( 0, 2, 3, 1, 0, 1, 2, 3, 0, 1,
+ // CHECK-NEXT: values : ( 0, 1, -1, 1, -1, -2, -2, 2, 1, 2,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 4
+ // CHECK-NEXT: dim = ( 4, 4 )
+ // CHECK-NEXT: lvl = ( 4, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 3,
+ // CHECK-NEXT: crd[0] : ( 0, 1, 3,
+ // CHECK-NEXT: pos[1] : ( 0, 2, 3, 4,
+ // CHECK-NEXT: crd[1] : ( 0, 2, 1, 0,
+ // CHECK-NEXT: values : ( 1, 0, 0, 0,
+ // CHECK-NEXT: ----
+ //
+ // CHECK-NEXT: ---- Sparse Tensor ----
+ // CHECK-NEXT: nse = 6
+ // CHECK-NEXT: dim = ( 4, 4 )
+ // CHECK-NEXT: lvl = ( 4, 4 )
+ // CHECK-NEXT: pos[0] : ( 0, 3,
+ // CHECK-NEXT: crd[0] : ( 0, 2, 3,
+ // CHECK-NEXT: pos[1] : ( 0, 1, 5, 6,
+ // CHECK-NEXT: crd[1] : ( 3, 0, 1, 2, 3, 1,
+ // CHECK-NEXT: values : ( -1, -1, -5, -2, 4, 4,
//
- call @dump_vec(%sv1) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump_vec(%sv2) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump_vec_i32(%0) : (tensor<?xi32, #SparseVector>) -> ()
- call @dump_vec(%1) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump_vec(%2) : (tensor<?xf64, #SparseVector>) -> ()
- call @dump_vec_i32(%3) : (tensor<?xi32, #SparseVector>) -> ()
- call @dump_mat(%5) : (tensor<?x?xf64, #DCSR>) -> ()
- call @dump_mat_4x4(%6) : (tensor<4x4xf64, #DCSR>) -> ()
- call @dump_mat_4x4(%7) : (tensor<4x4xf64, #DCSR>) -> ()
- call @dump_mat_4x4(%8) : (tensor<4x4xf64, #DCSR>) -> ()
- call @dump_mat_4x4(%9) : (tensor<4x4xf64, #DCSR>) -> ()
- call @dump_mat_4x4_i8(%10) : (tensor<4x4xi8, #DCSR>) -> ()
- call @dump_mat_4x4(%11) : (tensor<4x4xf64, #DCSR>) -> ()
+ sparse_tensor.print %sv1 : tensor<?xf64, #SparseVector>
+ sparse_tensor.print %sv2 : 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<?xi32, #SparseVector>
+ sparse_tensor.print %5 : tensor<?x?xf64, #DCSR>
+ sparse_tensor.print %6 : tensor<4x4xf64, #DCSR>
+ sparse_tensor.print %7 : tensor<4x4xf64, #DCSR>
+ sparse_tensor.print %8 : tensor<4x4xf64, #DCSR>
+ sparse_tensor.print %9 : tensor<4x4xf64, #DCSR>
+ sparse_tensor.print %10 : tensor<4x4xi8, #DCSR>
+ sparse_tensor.print %11 : tensor<4x4xf64, #DCSR>
// Release the resources.
bufferization.dealloc_tensor %sv1 : tensor<?xf64, #SparseVector>
``````````
</details>
https://github.com/llvm/llvm-project/pull/83926
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