diff options
Diffstat (limited to 'mlir/test/Dialect/SparseTensor/sparse_reshape.mlir')
| -rw-r--r-- | mlir/test/Dialect/SparseTensor/sparse_reshape.mlir | 79 |
1 files changed, 68 insertions, 11 deletions
diff --git a/mlir/test/Dialect/SparseTensor/sparse_reshape.mlir b/mlir/test/Dialect/SparseTensor/sparse_reshape.mlir index c791536e1519..65eb56b9bac3 100644 --- a/mlir/test/Dialect/SparseTensor/sparse_reshape.mlir +++ b/mlir/test/Dialect/SparseTensor/sparse_reshape.mlir @@ -1,24 +1,81 @@ -// RUN: mlir-opt %s | mlir-opt | FileCheck %s - -// TODO: check lowering to an actual implementation +// RUN: mlir-opt %s | mlir-opt | FileCheck %s --check-prefix=CHECK-ROUND +// RUN: mlir-opt %s --sparse-tensor-conversion --cse | FileCheck %s --check-prefix=CHECK-CONV #SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }> #SparseMatrix = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }> -// CHECK-LABEL: func.func @sparse_expand( -// CHECK-SAME: %[[A:.*]]: tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>> -// CHECK: %[[E:.*]] = tensor.expand_shape %[[A]] {{\[\[}}0, 1]] : tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>> into tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>> -// CHECK: return %[[E]] : tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>> +// +// roundtrip: +// +// CHECK-ROUND-LABEL: func.func @sparse_expand( +// CHECK-ROUND-SAME: %[[A:.*]]: tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>> +// CHECK-ROUND: %[[E:.*]] = tensor.expand_shape %[[A]] {{\[\[}}0, 1]] : tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>> into tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>> +// CHECK-ROUND: return %[[E]] : tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>> +// +// conversion: +// +// CHECK-CONV-LABEL: func.func @sparse_expand( +// CHECK-CONV-DAG: %[[C0:.*]] = arith.constant 0 : index +// CHECK-CONV-DAG: %[[C1:.*]] = arith.constant 1 : index +// CHECK-CONV-DAG: %[[C10:.*]] = arith.constant 10 : index +// CHECK-CONV-DAG: call @newSparseTensor +// CHECK-CONV-DAG: call @newSparseTensor +// CHECK-CONV: scf.while : () -> () { +// CHECK-CONV: call @getNextF64 +// CHECK-CONV: scf.condition(%13) +// CHECK-CONV: } do { +// CHECK-CONV: %[[X:.*]] = memref.load %{{.*}}[%[[C0]]] : memref<?xindex> +// CHECK-CONV: %[[D:.*]] = arith.divui %[[X]], %[[C10]] : index +// CHECK-CONV: memref.store %[[D]], %{{.*}}[%[[C0]]] : memref<?xindex> +// CHECK-CONV: %[[R:.*]] = arith.remui %[[X]], %[[C10]] : index +// CHECK-CONV: memref.store %[[R]], %{{.*}}[%[[C1]]] : memref<?xindex> +// CHECK-CONV: call @addEltF64 +// CHECK-CONV: scf.yield +// CHECK-CONV: } +// CHECK-CONV: %[[N:.*]] = call @newSparseTensor +// CHECK-CONV: call @delSparseTensorCOOF64 +// CHECK-CONV: call @delSparseTensorCOOF64 +// CHECK-CONV: return %[[N]] : !llvm.ptr<i8> +// func.func @sparse_expand(%arg0: tensor<100xf64, #SparseVector>) -> tensor<10x10xf64, #SparseMatrix> { %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<100xf64, #SparseVector> into tensor<10x10xf64, #SparseMatrix> return %0 : tensor<10x10xf64, #SparseMatrix> } -// CHECK-LABEL: func.func @sparse_collapse( -// CHECK-SAME: %[[A:.*]]: tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>> -// CHECK: %[[C:.*]] = tensor.collapse_shape %[[A]] {{\[\[}}0, 1]] : tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>> into tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>> -// CHECK: return %[[C]] : tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>> +// +// roundtrip: +// +// CHECK-ROUND-LABEL: func.func @sparse_collapse( +// CHECK-ROUND-SAME: %[[A:.*]]: tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>> +// CHECK-ROUND: %[[C:.*]] = tensor.collapse_shape %[[A]] {{\[\[}}0, 1]] : tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>> into tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>> +// CHECK-ROUND: return %[[C]] : tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>> +// +// conversion: +// +// CHECK-CONV-LABEL: func.func @sparse_collapse( +// CHECK-CONV-DAG: %[[C0:.*]] = arith.constant 0 : index +// CHECK-CONV-DAG: %[[C1:.*]] = arith.constant 1 : index +// CHECK-CONV-DAG: %[[C10:.*]] = arith.constant 10 : index +// CHECK-CONV-DAG: call @newSparseTensor +// CHECK-CONV-DAG: call @newSparseTensor +// CHECK-CONV: scf.while : () -> () { +// CHECK-CONV: call @getNextF64 +// CHECK-CONV: scf.condition(%13) +// CHECK-CONV: } do { +// CHECK-CONV: %[[X:.*]] = memref.load %{{.*}}[%[[C0]]] : memref<?xindex> +// CHECK-CONV: %[[M:.*]] = arith.muli %[[X]], %[[C10]] : index +// CHECK-CONV: %[[Y:.*]] = memref.load %{{.*}}[%[[C1]]] : memref<?xindex> +// CHECK-CONV: %[[A:.*]] = arith.addi %[[M]], %[[Y]] : index +// CHECK-CONV: memref.store %[[A]], %{{.*}}[%[[C0]]] : memref<?xindex> +// CHECK-CONV: call @addEltF64 +// CHECK-CONV: scf.yield +// CHECK-CONV: } +// CHECK-CONV: %[[N:.*]] = call @newSparseTensor +// CHECK-CONV: call @delSparseTensorCOOF64 +// CHECK-CONV: call @delSparseTensorCOOF64 +// CHECK-CONV: return %[[N]] : !llvm.ptr<i8> +// func.func @sparse_collapse(%arg0: tensor<10x10xf64, #SparseMatrix>) -> tensor<100xf64, #SparseVector> { %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<10x10xf64, #SparseMatrix> into tensor<100xf64, #SparseVector> |