diff options
Diffstat (limited to 'mlir/test/Dialect/SparseTensor/sparse_2d.mlir')
| -rw-r--r-- | mlir/test/Dialect/SparseTensor/sparse_2d.mlir | 314 |
1 files changed, 157 insertions, 157 deletions
diff --git a/mlir/test/Dialect/SparseTensor/sparse_2d.mlir b/mlir/test/Dialect/SparseTensor/sparse_2d.mlir index 22681da..57ae183 100644 --- a/mlir/test/Dialect/SparseTensor/sparse_2d.mlir +++ b/mlir/test/Dialect/SparseTensor/sparse_2d.mlir @@ -17,14 +17,14 @@ } // CHECK-LABEL: func @add_dd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_10]] : memref<32x16xf32>) @@ -53,7 +53,7 @@ func.func @add_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func.func @cmp_dd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index @@ -61,7 +61,7 @@ func.func @add_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg // CHECK-DAG: %[[VAL_5:.*]] = arith.constant false // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1> // CHECK: linalg.fill ins(%[[VAL_5]] : i1) outs(%[[VAL_10]] : memref<32x16xi1>) @@ -90,14 +90,14 @@ func.func @cmp_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func @mul_dd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_10]] : memref<32x16xf32>) @@ -126,7 +126,7 @@ func.func @mul_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func @add_ds( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index @@ -134,9 +134,9 @@ func.func @mul_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_6:.*]] = arith.constant true // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<32x16xf32>) @@ -189,7 +189,7 @@ func.func @add_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func.func @cmp_ds( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index @@ -199,9 +199,9 @@ func.func @add_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index // CHECK-DAG: %[[VAL_8:.*]] = arith.constant true // CHECK-DAG: %[[VAL_9:.*]] = arith.constant 0.000000e+00 : f32 -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1> // CHECK: linalg.fill ins(%[[VAL_5]] : i1) outs(%[[VAL_14]] : memref<32x16xi1>) @@ -256,15 +256,15 @@ func.func @cmp_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func @mul_ds( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_11]] : memref<32x16xf32>) @@ -295,7 +295,7 @@ func.func @mul_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func @add_sd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index @@ -303,9 +303,9 @@ func.func @mul_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg // CHECK-DAG: %[[VAL_5:.*]] = arith.constant true // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<32x16xf32>) @@ -363,7 +363,7 @@ func.func @add_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func.func @cmp_sd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 16 : index @@ -373,9 +373,9 @@ func.func @add_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index // CHECK-DAG: %[[VAL_8:.*]] = arith.constant true // CHECK-DAG: %[[VAL_9:.*]] = arith.constant 0.000000e+00 : f32 -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1> // CHECK: linalg.fill ins(%[[VAL_5]] : i1) outs(%[[VAL_14]] : memref<32x16xi1>) @@ -435,15 +435,15 @@ func.func @cmp_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func @mul_sd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 16 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_11]] : memref<32x16xf32>) @@ -475,7 +475,7 @@ func.func @mul_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func @add_ss( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index @@ -483,11 +483,11 @@ func.func @mul_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg // CHECK-DAG: %[[VAL_5:.*]] = arith.constant true // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_15]] : memref<32x16xf32>) @@ -569,7 +569,7 @@ func.func @add_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func.func @cmp_ss( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index @@ -579,11 +579,11 @@ func.func @add_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32>, %arg // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index // CHECK-DAG: %[[VAL_8:.*]] = arith.constant true // CHECK-DAG: %[[VAL_9:.*]] = arith.constant 0.000000e+00 : f32 -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK: %[[VAL_16:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1> // CHECK: linalg.fill ins(%[[VAL_5]] : i1) outs(%[[VAL_16]] : memref<32x16xi1>) @@ -669,16 +669,16 @@ func.func @cmp_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func @mul_ss( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32> // CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32x16xf32>) @@ -712,20 +712,20 @@ func.func @mul_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32>, %arg } // CHECK-LABEL: func @add_ss_ss( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*2]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_16:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_16]] : memref<32x16xf32>) // CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex> @@ -875,22 +875,22 @@ func.func @add_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T } // CHECK-LABEL: func.func @cmp_ss_ss( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant false // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0.000000e+00 : f32 -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_17:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1> // CHECK: linalg.fill ins(%[[VAL_3]] : i1) outs(%[[VAL_17]] : memref<32x16xi1>) // CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex> @@ -1051,19 +1051,19 @@ func.func @cmp_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T map = (d0, d1) -> (d0 : dense, d1 : loose_compressed) }> // CHECK-LABEL: func.func @sub_ss_batched( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x3xf64, #{{.*}}>>, -// CHECK-SAME: %[[VAL_1:.*]]: tensor<2x3xf64, #{{.*}}>>) -> tensor<2x3xf64, #{{.*}}>> { +// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x3xf64, #sparse{{[0-9]*}}>, +// CHECK-SAME: %[[VAL_1:.*]]: tensor<2x3xf64, #sparse{{[0-9]*}}>) -> tensor<2x3xf64, #sparse{{[0-9]*}}> { // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2 : index // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty() : tensor<2x3xf64, #{{.*}}>> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<2x3xf64, #{{.*}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<2x3xf64, #{{.*}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<2x3xf64, #{{.*}}>> to memref<?xf64> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<2x3xf64, #{{.*}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<2x3xf64, #{{.*}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<2x3xf64, #{{.*}}>> to memref<?xf64> -// CHECK: %[[VAL_12:.*]] = scf.for %[[VAL_13:.*]] = %[[VAL_3]] to %[[VAL_2]] step %[[VAL_4]] iter_args(%[[VAL_14:.*]] = %[[VAL_5]]) -> (tensor<2x3xf64, #{{.*}}>>) { +// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty() : tensor<2x3xf64, #sparse{{[0-9]*}}> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xf64> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xf64> +// CHECK: %[[VAL_12:.*]] = scf.for %[[VAL_13:.*]] = %[[VAL_3]] to %[[VAL_2]] step %[[VAL_4]] iter_args(%[[VAL_14:.*]] = %[[VAL_5]]) -> (tensor<2x3xf64, #sparse{{[0-9]*}}>) { // CHECK: %[[VAL_15:.*]] = arith.muli %[[VAL_13]], %[[VAL_2]] : index // CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_15]]] : memref<?xindex> // CHECK: %[[VAL_17:.*]] = arith.addi %[[VAL_15]], %[[VAL_4]] : index @@ -1076,9 +1076,9 @@ func.func @cmp_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T // CHECK: %[[VAL_27:.*]] = arith.cmpi ult, %[[VAL_24]], %[[VAL_18]] : index // CHECK: %[[VAL_28:.*]] = arith.cmpi ult, %[[VAL_25]], %[[VAL_22]] : index // CHECK: %[[VAL_29:.*]] = arith.andi %[[VAL_27]], %[[VAL_28]] : i1 -// CHECK: scf.condition(%[[VAL_29]]) %[[VAL_24]], %[[VAL_25]], %[[VAL_26]] : index, index, tensor<2x3xf64, #{{.*}}>> +// CHECK: scf.condition(%[[VAL_29]]) %[[VAL_24]], %[[VAL_25]], %[[VAL_26]] : index, index, tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } do { -// CHECK: ^bb0(%[[VAL_30:.*]]: index, %[[VAL_31:.*]]: index, %[[VAL_32:.*]]: tensor<2x3xf64, #{{.*}}>>): +// CHECK: ^bb0(%[[VAL_30:.*]]: index, %[[VAL_31:.*]]: index, %[[VAL_32:.*]]: tensor<2x3xf64, #sparse{{[0-9]*}}>): // CHECK: %[[VAL_33:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_30]]] : memref<?xindex> // CHECK: %[[VAL_34:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_31]]] : memref<?xindex> // CHECK: %[[VAL_35:.*]] = arith.cmpi ult, %[[VAL_34]], %[[VAL_33]] : index @@ -1086,31 +1086,31 @@ func.func @cmp_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T // CHECK: %[[VAL_37:.*]] = arith.cmpi eq, %[[VAL_33]], %[[VAL_36]] : index // CHECK: %[[VAL_38:.*]] = arith.cmpi eq, %[[VAL_34]], %[[VAL_36]] : index // CHECK: %[[VAL_39:.*]] = arith.andi %[[VAL_37]], %[[VAL_38]] : i1 -// CHECK: %[[VAL_40:.*]] = scf.if %[[VAL_39]] -> (tensor<2x3xf64, #{{.*}}>>) { +// CHECK: %[[VAL_40:.*]] = scf.if %[[VAL_39]] -> (tensor<2x3xf64, #sparse{{[0-9]*}}>) { // CHECK: %[[VAL_41:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_30]]] : memref<?xf64> // CHECK: %[[VAL_42:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_31]]] : memref<?xf64> // CHECK: %[[VAL_43:.*]] = arith.subf %[[VAL_41]], %[[VAL_42]] : f64 -// CHECK: %[[VAL_44:.*]] = sparse_tensor.insert %[[VAL_43]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #{{.*}}>> -// CHECK: scf.yield %[[VAL_44]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: %[[VAL_44:.*]] = sparse_tensor.insert %[[VAL_43]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #sparse{{[0-9]*}}> +// CHECK: scf.yield %[[VAL_44]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } else { // CHECK: %[[VAL_45:.*]] = arith.cmpi eq, %[[VAL_33]], %[[VAL_36]] : index -// CHECK: %[[VAL_46:.*]] = scf.if %[[VAL_45]] -> (tensor<2x3xf64, #{{.*}}>>) { +// CHECK: %[[VAL_46:.*]] = scf.if %[[VAL_45]] -> (tensor<2x3xf64, #sparse{{[0-9]*}}>) { // CHECK: %[[VAL_47:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_30]]] : memref<?xf64> -// CHECK: %[[VAL_48:.*]] = sparse_tensor.insert %[[VAL_47]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #{{.*}}>> -// CHECK: scf.yield %[[VAL_48]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: %[[VAL_48:.*]] = sparse_tensor.insert %[[VAL_47]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #sparse{{[0-9]*}}> +// CHECK: scf.yield %[[VAL_48]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } else { // CHECK: %[[VAL_49:.*]] = arith.cmpi eq, %[[VAL_34]], %[[VAL_36]] : index -// CHECK: %[[VAL_50:.*]] = scf.if %[[VAL_49]] -> (tensor<2x3xf64, #{{.*}}>>) { +// CHECK: %[[VAL_50:.*]] = scf.if %[[VAL_49]] -> (tensor<2x3xf64, #sparse{{[0-9]*}}>) { // CHECK: %[[VAL_51:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_31]]] : memref<?xf64> // CHECK: %[[VAL_52:.*]] = arith.negf %[[VAL_51]] : f64 -// CHECK: %[[VAL_53:.*]] = sparse_tensor.insert %[[VAL_52]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #{{.*}}>> -// CHECK: scf.yield %[[VAL_53]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: %[[VAL_53:.*]] = sparse_tensor.insert %[[VAL_52]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #sparse{{[0-9]*}}> +// CHECK: scf.yield %[[VAL_53]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } else { -// CHECK: scf.yield %[[VAL_32]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: scf.yield %[[VAL_32]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } -// CHECK: scf.yield %[[VAL_54:.*]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: scf.yield %[[VAL_54:.*]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } -// CHECK: scf.yield %[[VAL_55:.*]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: scf.yield %[[VAL_55:.*]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } // CHECK: %[[VAL_56:.*]] = arith.cmpi eq, %[[VAL_33]], %[[VAL_36]] : index // CHECK: %[[VAL_57:.*]] = arith.addi %[[VAL_30]], %[[VAL_4]] : index @@ -1118,25 +1118,25 @@ func.func @cmp_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T // CHECK: %[[VAL_59:.*]] = arith.cmpi eq, %[[VAL_34]], %[[VAL_36]] : index // CHECK: %[[VAL_60:.*]] = arith.addi %[[VAL_31]], %[[VAL_4]] : index // CHECK: %[[VAL_61:.*]] = arith.select %[[VAL_59]], %[[VAL_60]], %[[VAL_31]] : index -// CHECK: scf.yield %[[VAL_58]], %[[VAL_61]], %[[VAL_62:.*]] : index, index, tensor<2x3xf64, #{{.*}}>> +// CHECK: scf.yield %[[VAL_58]], %[[VAL_61]], %[[VAL_62:.*]] : index, index, tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } attributes // CHECK: %[[VAL_63:.*]] = scf.for %[[VAL_64:.*]] = %[[VAL_65:.*]]#0 to %[[VAL_18]] step %[[VAL_4]] iter_args(%[[VAL_66:.*]] = %[[VAL_65]]#2) // CHECK: %[[VAL_67:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_64]]] : memref<?xindex> // CHECK: %[[VAL_68:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_64]]] : memref<?xf64> -// CHECK: %[[VAL_69:.*]] = sparse_tensor.insert %[[VAL_68]] into %[[VAL_66]]{{\[}}%[[VAL_13]], %[[VAL_67]]] : tensor<2x3xf64, #{{.*}}>> -// CHECK: scf.yield %[[VAL_69]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: %[[VAL_69:.*]] = sparse_tensor.insert %[[VAL_68]] into %[[VAL_66]]{{\[}}%[[VAL_13]], %[[VAL_67]]] : tensor<2x3xf64, #sparse{{[0-9]*}}> +// CHECK: scf.yield %[[VAL_69]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } // CHECK: %[[VAL_70:.*]] = scf.for %[[VAL_71:.*]] = %[[VAL_72:.*]]#1 to %[[VAL_22]] step %[[VAL_4]] iter_args(%[[VAL_73:.*]] = %[[VAL_74:.*]]) // CHECK: %[[VAL_75:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_71]]] : memref<?xindex> // CHECK: %[[VAL_76:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_71]]] : memref<?xf64> // CHECK: %[[VAL_77:.*]] = arith.negf %[[VAL_76]] : f64 -// CHECK: %[[VAL_78:.*]] = sparse_tensor.insert %[[VAL_77]] into %[[VAL_73]]{{\[}}%[[VAL_13]], %[[VAL_75]]] : tensor<2x3xf64, #{{.*}}>> -// CHECK: scf.yield %[[VAL_78]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: %[[VAL_78:.*]] = sparse_tensor.insert %[[VAL_77]] into %[[VAL_73]]{{\[}}%[[VAL_13]], %[[VAL_75]]] : tensor<2x3xf64, #sparse{{[0-9]*}}> +// CHECK: scf.yield %[[VAL_78]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } -// CHECK: scf.yield %[[VAL_79:.*]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: scf.yield %[[VAL_79:.*]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } -// CHECK: %[[VAL_80:.*]] = sparse_tensor.load %[[VAL_81:.*]] hasInserts : tensor<2x3xf64, #{{.*}}>> -// CHECK: return %[[VAL_80]] : tensor<2x3xf64, #{{.*}}>> +// CHECK: %[[VAL_80:.*]] = sparse_tensor.load %[[VAL_81:.*]] hasInserts : tensor<2x3xf64, #sparse{{[0-9]*}}> +// CHECK: return %[[VAL_80]] : tensor<2x3xf64, #sparse{{[0-9]*}}> // CHECK: } func.func @sub_ss_batched(%0: tensor<2x3xf64, #BatchedVector>, %1: tensor<2x3xf64, #BatchedVector>) -> tensor<2x3xf64, #BatchedVector> { @@ -1152,20 +1152,20 @@ func.func @sub_ss_batched(%0: tensor<2x3xf64, #BatchedVector>, %1: tensor<2x3xf6 } // CHECK-LABEL: func @mul_ss_ss( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*2]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_16:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_16]] : memref<32x16xf32>) // CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex> @@ -1247,19 +1247,19 @@ func.func @mul_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T } // CHECK-LABEL: func @add_sd_ds( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_6:.*]] = arith.constant true // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_15]] : memref<32x16xf32>) // CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_5]]] : memref<?xindex> @@ -1352,17 +1352,17 @@ func.func @add_sd_ds(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32, #T } // CHECK-LABEL: func @mul_sd_ds( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 16 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32> // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<32x16xf32>) // CHECK: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex> @@ -1407,15 +1407,15 @@ func.func @mul_sd_ds(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32, #T } // CHECK-LABEL: func @matvec( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<16x32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<16x32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<16xf32>) -> tensor<16xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 16 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<16x32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<16x32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16x32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<16x32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<16x32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16x32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32> // CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<16xf32> // CHECK: scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] { @@ -1458,13 +1458,13 @@ func.func @matvec(%argA: tensor<16x32xf32, #Tds>, %argb: tensor<32xf32>, %argx: } // CHECK-LABEL: func @sum_reduction( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<f32>) -> tensor<f32> { // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 10 : index // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index -// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<f32> // CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<f32> // CHECK: %[[VAL_10:.*]] = scf.for %[[VAL_11:.*]] = %[[VAL_4]] to %[[VAL_2]] step %[[VAL_3]] iter_args(%[[VAL_12:.*]] = %[[VAL_9]]) -> (f32) { @@ -1503,15 +1503,15 @@ func.func @sum_reduction(%arga: tensor<10x20xf32, #Tds>, %argx: tensor<f32>) -> } // CHECK-LABEL: func @scale( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf64, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?xf64>) -> tensor<?x?xf64> { // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2.000000e+00 : f64 // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_3]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xf64> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_3]] : tensor<?x?xf64, #sparse{{[0-9]*}}> // CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<?x?xf64> // CHECK: linalg.fill ins(%{{.*}} : f64) outs(%[[VAL_11]] : memref<?x?xf64>) // CHECK: scf.for %[[VAL_12:.*]] = %[[VAL_3]] to %[[VAL_8]] step %[[VAL_4]] { @@ -1552,17 +1552,17 @@ func.func @scale(%arga: tensor<?x?xf64, #Tds>, %argx: tensor<?x?xf64>) -> tensor } // CHECK-LABEL: func.func @sampled_dense_dense( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?x?xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*1]]: tensor<?x?xf32>, // CHECK-SAME: %[[VAL_2:.*2]]: tensor<?x?xf32>, // CHECK-SAME: %[[VAL_3:.*3]]: tensor<?x?xf32>) -> tensor<?x?xf32> { // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_11:.*]] = tensor.dim %[[VAL_1]], %[[VAL_4]] : tensor<?x?xf32> // CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_1]] : memref<?x?xf32> // CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<?x?xf32> @@ -1621,24 +1621,24 @@ func.func @sampled_dense_dense(%args: tensor<?x?xf32, #Tss>, } // CHECK-LABEL: func @sum_kernel_with_inv( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_2:.*2]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?x?xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<?x?xf32, #sparse{{[0-9]*}}>, %[[VAL_2:.*2]]: tensor<?x?xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_3:.*3]]: tensor<?xf32>, // CHECK-SAME: %[[VAL_4:.*4]]: tensor<f32>, // CHECK-SAME: %[[VAL_5:.*5]]: tensor<?xf32>) -> tensor<?xf32> { // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index // CHECK-DAG: %[[VAL_8:.*]] = arith.constant true -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_18:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_19:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_18:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_19:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_20:.*]] = bufferization.to_memref %[[VAL_3]] : memref<?xf32> // CHECK-DAG: %[[VAL_21:.*]] = bufferization.to_memref %[[VAL_4]] : memref<f32> // CHECK-DAG: %[[VAL_22:.*]] = sparse_tensor.lvl %[[VAL_2]], %[[VAL_6]] : tensor<?x?xf32, |