diff options
Diffstat (limited to 'mlir/test/Dialect/SparseTensor/sparse_1d.mlir')
| -rw-r--r-- | mlir/test/Dialect/SparseTensor/sparse_1d.mlir | 200 |
1 files changed, 100 insertions, 100 deletions
diff --git a/mlir/test/Dialect/SparseTensor/sparse_1d.mlir b/mlir/test/Dialect/SparseTensor/sparse_1d.mlir index d29758e..8f96f33 100644 --- a/mlir/test/Dialect/SparseTensor/sparse_1d.mlir +++ b/mlir/test/Dialect/SparseTensor/sparse_1d.mlir @@ -14,13 +14,13 @@ } // CHECK-LABEL: func @add_d( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: f32, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // 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.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_8]] : memref<32xf32>) // CHECK: scf.for %[[VAL_9:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] { @@ -43,14 +43,14 @@ func.func @add_d(%arga: tensor<32xf32, #DV>, %argb: f32, %argx: tensor<32xf32>) } // CHECK-LABEL: func @add_d_init( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: f32) -> tensor<32xf32> { // CHECK: %[[VAL_2:.*]] = arith.constant 32 : index // CHECK: %[[VAL_3:.*]] = arith.constant 0.000000e+00 : f32 // CHECK: %[[VAL_4:.*]] = arith.constant 0 : index // CHECK: %[[VAL_5:.*]] = arith.constant 1 : index // CHECK: %[[VAL_INITTENSOR:.*]] = tensor.empty() : tensor<32xf32> -// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_INITTENSOR]] : memref<32xf32> // CHECK: linalg.fill ins(%[[VAL_3]] : f32) outs(%[[VAL_7]] : memref<32xf32>) // CHECK: scf.for %[[VAL_8:.*]] = %[[VAL_4]] to %[[VAL_2]] step %[[VAL_5]] { @@ -74,13 +74,13 @@ func.func @add_d_init(%arga: tensor<32xf32, #DV>, %argb: f32) -> tensor<32xf32> } // CHECK-LABEL: func @mul_d( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: f32, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // 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.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_8]] : memref<32xf32>) // CHECK: scf.for %[[VAL_9:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] { @@ -103,16 +103,16 @@ func.func @mul_d(%arga: tensor<32xf32, #DV>, %argb: f32, %argx: tensor<32xf32>) } // CHECK-LABEL: func @add_s( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: f32, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant true // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex> // CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_6]]] : memref<?xindex> // CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] @@ -158,13 +158,13 @@ func.func @add_s(%arga: tensor<32xf32, #SV>, %argb: f32, %argx: tensor<32xf32>) } // CHECK-LABEL: func @repeated_add_s( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>) -> tensor<32xf32> { // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] // CHECK-DAG: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex> // CHECK-DAG: %[[VAL_10:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex> @@ -197,14 +197,14 @@ func.func @repeated_add_s(%arga: tensor<32xf32, #SV>, %argx: tensor<32xf32>) -> } // CHECK-LABEL: func @mul_s( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: f32, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // 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<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_9]] : memref<32xf32>) // CHECK-DAG: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex> @@ -240,13 +240,13 @@ func.func @mul_s(%arga: tensor<32xf32, #SV>, %argb: f32, %argx: tensor<32xf32>) } // CHECK-LABEL: func @add_dd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // 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.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32> // CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_9]] : memref<32xf32>) @@ -271,13 +271,13 @@ func.func @add_dd(%arga: tensor<32xf32, #DV>, %argb: tensor<32xf32>, %argx: tens } // CHECK-LABEL: func @mul_dd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // 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.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32> // CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_9]] : memref<32xf32>) @@ -303,16 +303,16 @@ func.func @mul_dd(%arga: tensor<32xf32, #DV>, %argb: tensor<32xf32>, %argx: tens // CHECK-LABEL: func @add_ds( // CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32>, -// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant true // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index // CHECK-DAG: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_0]] : memref<32xf32> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32xf32>) // CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_4]]] : memref<?xindex> @@ -362,14 +362,14 @@ func.func @add_ds(%arga: tensor<32xf32>, %argb: tensor<32xf32, #SV>, %argx: tens // CHECK-LABEL: func @mul_ds( // CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32>, -// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index // CHECK-DAG: %[[VAL_5:.*]] = bufferization.to_memref %[[VAL_0]] : memref<32xf32> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_10]] : memref<32xf32>) // CHECK-DAG: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_3]]] : memref<?xindex> @@ -396,16 +396,16 @@ func.func @mul_ds(%arga: tensor<32xf32>, %argb: tensor<32xf32, #SV>, %argx: tens } // CHECK-LABEL: func @add_sd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_5:.*]] = arith.constant true // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32> // CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32xf32>) @@ -455,14 +455,14 @@ func.func @add_sd(%arga: tensor<32xf32, #SV>, %argb: tensor<32xf32>, %argx: tens } // CHECK-LABEL: func @mul_sd( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>, // CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> { // 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<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32> // CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_10]] : memref<32xf32>) @@ -490,16 +490,16 @@ func.func @mul_sd(%arga: tensor<32xf32, #SV>, %argb: tensor<32xf32>, %argx: tens } // CHECK-LABEL: func @add_ss( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*2]]: tensor<32xf32>) -> tensor<32xf32> { // 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<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32xf32>) // CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex> @@ -572,16 +572,16 @@ func.func @add_ss(%arga: tensor<32xf32, #SV>, %argb: tensor<32xf32, #SV>, %argx: } // CHECK-LABEL: func @mul_ss( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*2]]: tensor<32xf32>) -> tensor<32xf32> { // 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<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32xf32>) // CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex> @@ -632,17 +632,17 @@ func.func @mul_ss(%arga: tensor<32xf32, #SV>, %argb: tensor<32xf32, #SV>, %argx: } // CHECK-LABEL: func @two_way_inv( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*2]]: f32, // CHECK-SAME: %[[VAL_3:.*3]]: tensor<16xf32>) -> tensor<16xf32> { // 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<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_3]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<16xf32>) // CHECK-DAG: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex> @@ -724,17 +724,17 @@ func.func @two_way_inv(%arga: tensor<16xf32, #SV>, %argb: tensor<16xf32, #SV>, % } // CHECK-LABEL: func @two_way_inv_alt( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*2]]: f32, // CHECK-SAME: %[[VAL_3:.*3]]: tensor<16xf32>) -> tensor<16xf32> { // 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<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_3]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<16xf32>) // CHECK-DAG: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex> @@ -824,12 +824,12 @@ func.func @two_way_inv_alt(%arga: tensor<16xf32, #SV>, } // CHECK-LABEL: func @sum_reduction( -// CHECK-SAME: %[[VAL_0:.*]]: tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_1:.*]]: tensor<f32>) -> tensor<f32> { // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index -// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_1]] : memref<f32> // CHECK-DAG: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex> // CHECK-DAG: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex> @@ -865,16 +865,16 @@ func.func @sum_reduction(%arga: tensor<?xf32, #SV>, %argx: tensor<f32>) -> tenso } // CHECK-LABEL: func @sum_reduction_ss( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_2:.*2]]: tensor<f32>) -> tensor<f32> { // 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<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<f32> // CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_11]][] : memref<f32> // CHECK-DAG: %[[VAL_14:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex> @@ -970,17 +970,17 @@ func.func @sum_reduction_ss(%arga: tensor<16xf32, #SV>, } // CHECK-LABEL: func @sum_reduction_inv( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<f32>, %[[VAL_2:.*2]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<f32>, %[[VAL_2:.*2]]: tensor<16xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_3:.*3]]: tensor<f32>) -> tensor<f32> { // 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<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<f32> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32> // CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_3]] : memref<f32> // CHECK-DAG: %[[VAL_15:.*]] = memref.load %[[VAL_13]][] : memref<f32> // CHECK-DAG: %[[VAL_16:.*]] = memref.load %[[VAL_9]][] : memref<f32> @@ -1084,19 +1084,19 @@ func.func @sum_reduction_inv(%arga: tensor<16xf32, #SV>, // CHECK-LABEL: func @four_tensors_op( // CHECK-SAME: %[[VAL_0:.*0]]: tensor<?xf64>, -// CHECK-SAME: %[[VAL_1:.*1]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_2:.*2]]: tensor<?xf64>, %[[VAL_3:.*3]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_1:.*1]]: tensor<?xf64, #sparse{{[0-9]*}}>, %[[VAL_2:.*2]]: tensor<?xf64>, %[[VAL_3:.*3]]: tensor<?xf64, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_4:.*]]: tensor<?xf64>) -> tensor<?xf64> { // 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:.*]] = bufferization.to_memref %[[VAL_0]] : memref<?xf64> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64> // CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<?xf64> -// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_3]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_3]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.values %[[VAL_3]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64> +// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_3]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_3]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.values %[[VAL_3]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64> // CHECK-DAG: %[[VAL_16:.*]] = tensor.dim %[[VAL_0]], %[[VAL_5]] : tensor<?xf64> // CHECK-DAG: %[[VAL_18:.*]] = bufferization.to_memref %[[VAL_4]] // CHECK-DAG: linalg.fill ins(%{{.*}} : f64) outs(%[[VAL_18]] : memref<?xf64>) @@ -1259,19 +1259,19 @@ func.func @four_tensors_op(%arga: tensor<?xf64>, } // CHECK-LABEL: func @red3s( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_2:.*2]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>, +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?xf64, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<?xf64, #sparse{{[0-9]*}}>, %[[VAL_2:.*2]]: tensor<?xf64, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[VAL_3:.*3]]: tensor<f64>) -> tensor<f64> { // 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<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64> -// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64> -// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex> -// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64> +// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64> +// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64> +// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex> +// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64> // CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_3]] : memref<f64> // CHECK-DAG: %[[VAL_17:.*]] = memref.load %[[VAL_15]][] : memref<f64> // CHECK-DAG: %[[VAL_18:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex> |