16b8f4ddae
We have several ways to materialize sparse tensors (new and convert) but no explicit operation to release the underlying sparse storage scheme at runtime (other than making an explicit delSparseTensor() library call). To simplify memory management, a sparse_tensor.release operation has been introduced that lowers to the runtime library call while keeping tensors, opague pointers, and memrefs transparent in the initial IR. *Note* There is obviously some tension between the concept of immutable tensors and memory management methods. This tension is addressed by simply stating that after the "release" call, no further memref related operations are allowed on the tensor value. We expect the design to evolve over time, however, and arrive at a more satisfactory view of tensors and buffers eventually. Bug: http://llvm.org/pr52046 Reviewed By: bixia Differential Revision: https://reviews.llvm.org/D111099
399 lines
20 KiB
MLIR
399 lines
20 KiB
MLIR
// RUN: mlir-opt %s --sparse-tensor-conversion --canonicalize --cse | FileCheck %s
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#DenseVector = #sparse_tensor.encoding<{
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dimLevelType = ["dense"]
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}>
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#SparseVector = #sparse_tensor.encoding<{
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dimLevelType = ["compressed"]
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}>
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#SparseVector64 = #sparse_tensor.encoding<{
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dimLevelType = ["compressed"],
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pointerBitWidth = 64,
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indexBitWidth = 64
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}>
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#SparseVector32 = #sparse_tensor.encoding<{
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dimLevelType = ["compressed"],
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pointerBitWidth = 32,
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indexBitWidth = 32
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}>
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#SparseMatrix = #sparse_tensor.encoding<{
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dimLevelType = ["dense", "compressed"]
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}>
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#SparseTensor = #sparse_tensor.encoding<{
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dimLevelType = ["dense", "compressed", "compressed"],
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dimOrdering = affine_map<(i,j,k) -> (k,i,j)>
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}>
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// CHECK-LABEL: func @sparse_dim1d(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
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// CHECK: %[[C:.*]] = constant 0 : index
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// CHECK: %[[D:.*]] = call @sparseDimSize(%[[A]], %[[C]])
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// CHECK: return %[[D]] : index
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func @sparse_dim1d(%arg0: tensor<?xf64, #SparseVector>) -> index {
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%c = constant 0 : index
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%0 = tensor.dim %arg0, %c : tensor<?xf64, #SparseVector>
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return %0 : index
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}
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// CHECK-LABEL: func @sparse_dim3d(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
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// CHECK: %[[C:.*]] = constant 2 : index
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// CHECK: %[[D:.*]] = call @sparseDimSize(%[[A]], %[[C]])
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// CHECK: return %[[D]] : index
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func @sparse_dim3d(%arg0: tensor<?x?x?xf64, #SparseTensor>) -> index {
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// Querying for dimension 1 in the tensor type needs to be
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// permuted into querying for dimension 2 in the stored sparse
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// tensor scheme, since the latter honors the dimOrdering.
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%c = constant 1 : index
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%0 = tensor.dim %arg0, %c : tensor<?x?x?xf64, #SparseTensor>
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return %0 : index
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}
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// CHECK-LABEL: func @sparse_dim3d_const(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
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// CHECK: %[[C:.*]] = constant 20 : index
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// CHECK: return %[[C]] : index
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func @sparse_dim3d_const(%arg0: tensor<10x20x30xf64, #SparseTensor>) -> index {
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// Querying for dimension 1 in the tensor type can be directly
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// folded into the right value (even though it corresponds
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// to dimension 2 in the stored sparse tensor scheme).
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%c = constant 1 : index
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%0 = tensor.dim %arg0, %c : tensor<10x20x30xf64, #SparseTensor>
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return %0 : index
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}
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// CHECK-LABEL: func @sparse_new1d(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
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// CHECK-DAG: %[[U:.*]] = constant dense<1> : tensor<1xi8>
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// CHECK-DAG: %[[V:.*]] = constant dense<128> : tensor<1xi64>
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// CHECK-DAG: %[[W:.*]] = constant dense<0> : tensor<1xi64>
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// CHECK-DAG: %[[X:.*]] = tensor.cast %[[U]] : tensor<1xi8> to tensor<?xi8>
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// CHECK-DAG: %[[Y:.*]] = tensor.cast %[[V]] : tensor<1xi64> to tensor<?xi64>
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// CHECK-DAG: %[[Z:.*]] = tensor.cast %[[W]] : tensor<1xi64> to tensor<?xi64>
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// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[A]])
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// CHECK: return %[[T]] : !llvm.ptr<i8>
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func @sparse_new1d(%arg0: !llvm.ptr<i8>) -> tensor<128xf64, #SparseVector> {
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%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<128xf64, #SparseVector>
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return %0 : tensor<128xf64, #SparseVector>
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}
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// CHECK-LABEL: func @sparse_new2d(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
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// CHECK-DAG: %[[U:.*]] = constant dense<[0, 1]> : tensor<2xi8>
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// CHECK-DAG: %[[V:.*]] = constant dense<0> : tensor<2xi64>
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// CHECK-DAG: %[[W:.*]] = constant dense<[0, 1]> : tensor<2xi64>
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// CHECK-DAG: %[[X:.*]] = tensor.cast %[[U]] : tensor<2xi8> to tensor<?xi8>
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// CHECK-DAG: %[[Y:.*]] = tensor.cast %[[V]] : tensor<2xi64> to tensor<?xi64>
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// CHECK-DAG: %[[Z:.*]] = tensor.cast %[[W]] : tensor<2xi64> to tensor<?xi64>
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// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[A]])
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// CHECK: return %[[T]] : !llvm.ptr<i8>
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func @sparse_new2d(%arg0: !llvm.ptr<i8>) -> tensor<?x?xf32, #SparseMatrix> {
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%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?xf32, #SparseMatrix>
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return %0 : tensor<?x?xf32, #SparseMatrix>
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}
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// CHECK-LABEL: func @sparse_new3d(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
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// CHECK-DAG: %[[U:.*]] = constant dense<[0, 1, 1]> : tensor<3xi8>
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// CHECK-DAG: %[[V:.*]] = constant dense<0> : tensor<3xi64>
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// CHECK-DAG: %[[W:.*]] = constant dense<[1, 2, 0]> : tensor<3xi64>
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// CHECK-DAG: %[[X:.*]] = tensor.cast %[[U]] : tensor<3xi8> to tensor<?xi8>
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// CHECK-DAG: %[[Y:.*]] = tensor.cast %[[V]] : tensor<3xi64> to tensor<?xi64>
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// CHECK-DAG: %[[Z:.*]] = tensor.cast %[[W]] : tensor<3xi64> to tensor<?xi64>
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// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[A]])
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// CHECK: return %[[T]] : !llvm.ptr<i8>
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func @sparse_new3d(%arg0: !llvm.ptr<i8>) -> tensor<?x?x?xf32, #SparseTensor> {
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%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?x?xf32, #SparseTensor>
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return %0 : tensor<?x?x?xf32, #SparseTensor>
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}
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// CHECK-LABEL: func @sparse_release(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
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// CHECK: call @delSparseTensor(%[[A]]) : (!llvm.ptr<i8>) -> ()
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// CHECK: return
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func @sparse_release(%arg0: tensor<128xf64, #SparseVector>) {
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sparse_tensor.release %arg0 : tensor<128xf64, #SparseVector>
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return
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}
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// CHECK-LABEL: func @sparse_nop_convert(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
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// CHECK: return %[[A]] : !llvm.ptr<i8>
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func @sparse_nop_convert(%arg0: tensor<64xf32, #SparseVector>) -> tensor<64xf32, #SparseVector> {
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%0 = sparse_tensor.convert %arg0 : tensor<64xf32, #SparseVector> to tensor<64xf32, #SparseVector>
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return %0 : tensor<64xf32, #SparseVector>
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}
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// CHECK-LABEL: func @sparse_convert_1d(
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// CHECK-SAME: %[[A:.*]]: tensor<?xi32>) -> !llvm.ptr<i8>
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// CHECK-DAG: %[[C0:.*]] = constant 0 : index
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// CHECK-DAG: %[[C1:.*]] = constant 1 : index
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// CHECK-DAG: %[[D0:.*]] = constant dense<0> : tensor<1xi64>
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// CHECK-DAG: %[[D1:.*]] = constant dense<1> : tensor<1xi8>
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// CHECK-DAG: %[[X:.*]] = tensor.cast %[[D1]] : tensor<1xi8> to tensor<?xi8>
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// CHECK-DAG: %[[Y:.*]] = tensor.cast %[[D0]] : tensor<1xi64> to tensor<?xi64>
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// CHECK: %[[C:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Y]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.}})
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// CHECK: %[[M:.*]] = memref.alloca() : memref<1xindex>
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// CHECK: %[[T:.*]] = memref.cast %[[M]] : memref<1xindex> to memref<?xindex>
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// CHECK: %[[U:.*]] = tensor.dim %[[A]], %[[C0]] : tensor<?xi32>
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// CHECK: scf.for %[[I:.*]] = %[[C0]] to %[[U]] step %[[C1]] {
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// CHECK: %[[E:.*]] = tensor.extract %[[A]][%[[I]]] : tensor<?xi32>
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// CHECK: memref.store %[[I]], %[[M]][%[[C0]]] : memref<1xindex>
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// CHECK: call @addEltI32(%[[C]], %[[E]], %[[T]], %[[Y]])
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// CHECK: }
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// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Y]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[C]])
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// CHECK: return %[[T]] : !llvm.ptr<i8>
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func @sparse_convert_1d(%arg0: tensor<?xi32>) -> tensor<?xi32, #SparseVector> {
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%0 = sparse_tensor.convert %arg0 : tensor<?xi32> to tensor<?xi32, #SparseVector>
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return %0 : tensor<?xi32, #SparseVector>
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}
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// CHECK-LABEL: func @sparse_convert_1d_ss(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
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// CHECK: %[[C:.*]] = call @newSparseTensor(%{{.}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[A]])
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// CHECK: %[[T:.*]] = call @newSparseTensor(%{{.}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[C]])
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// CHECK: return %[[T]] : !llvm.ptr<i8>
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func @sparse_convert_1d_ss(%arg0: tensor<?xf32, #SparseVector64>) -> tensor<?xf32, #SparseVector32> {
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%0 = sparse_tensor.convert %arg0 : tensor<?xf32, #SparseVector64> to tensor<?xf32, #SparseVector32>
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return %0 : tensor<?xf32, #SparseVector32>
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}
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// CHECK-LABEL: func @sparse_convert_2d(
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// CHECK-SAME: %[[A:.*]]: tensor<2x4xf64>) -> !llvm.ptr<i8>
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// CHECK-DAG: %[[C0:.*]] = constant 0 : index
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// CHECK-DAG: %[[C1:.*]] = constant 1 : index
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// CHECK-DAG: %[[U:.*]] = constant dense<[0, 1]> : tensor<2xi8>
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// CHECK-DAG: %[[V:.*]] = constant dense<[2, 4]> : tensor<2xi64>
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// CHECK-DAG: %[[W:.*]] = constant dense<[0, 1]> : tensor<2xi64>
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// CHECK-DAG: %[[X:.*]] = tensor.cast %[[U]] : tensor<2xi8> to tensor<?xi8>
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// CHECK-DAG: %[[Y:.*]] = tensor.cast %[[V]] : tensor<2xi64> to tensor<?xi64>
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// CHECK-DAG: %[[Z:.*]] = tensor.cast %[[W]] : tensor<2xi64> to tensor<?xi64>
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// CHECK: %[[C:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.}})
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// CHECK: %[[M:.*]] = memref.alloca() : memref<2xindex>
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// CHECK: %[[T:.*]] = memref.cast %[[M]] : memref<2xindex> to memref<?xindex>
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// CHECK: scf.for %[[I:.*]] = %[[C0]] to %{{.*}} step %[[C1]] {
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// CHECK: scf.for %[[J:.*]] = %[[C0]] to %{{.*}} step %[[C1]] {
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// CHECK: %[[E:.*]] = tensor.extract %[[A]][%[[I]], %[[J]]] : tensor<2x4xf64>
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// CHECK: memref.store %[[I]], %[[M]][%[[C0]]] : memref<2xindex>
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// CHECK: memref.store %[[J]], %[[M]][%[[C1]]] : memref<2xindex>
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// CHECK: call @addEltF64(%[[C]], %[[E]], %[[T]], %[[Z]])
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// CHECK: }
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// CHECK: }
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// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[C]])
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// CHECK: return %[[T]] : !llvm.ptr<i8>
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func @sparse_convert_2d(%arg0: tensor<2x4xf64>) -> tensor<2x4xf64, #SparseMatrix> {
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%0 = sparse_tensor.convert %arg0 : tensor<2x4xf64> to tensor<2x4xf64, #SparseMatrix>
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return %0 : tensor<2x4xf64, #SparseMatrix>
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}
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#CSR = #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ] }>
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// CHECK-LABEL: func @entry() -> !llvm.ptr<i8> {
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// CHECK: %[[C1:.*]] = constant 1 : i32
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// CHECK: %[[Offset:.*]] = constant dense<[0, 1]> : tensor<2xi64>
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// CHECK: %[[Dims:.*]] = constant dense<[8, 7]> : tensor<2xi64>
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// CHECK: %[[Base:.*]] = constant dense<[0, 1]> : tensor<2xi8>
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// CHECK: %[[I2:.*]] = constant 2 : index
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// CHECK: %[[SparseV:.*]] = constant dense<[1.000000e+00, 5.000000e+00]> : tensor<2xf32>
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// CHECK: %[[SparseI:.*]] = constant dense<{{\[\[}}0, 0], [1, 6]]> : tensor<2x2xi64>
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// CHECK: %[[I1:.*]] = constant 1 : index
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// CHECK: %[[I0:.*]] = constant 0 : index
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// CHECK: %[[C2:.*]] = constant 2 : i32
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// CHECK: %[[BaseD:.*]] = tensor.cast %[[Base]] : tensor<2xi8> to tensor<?xi8>
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// CHECK: %[[DimsD:.*]] = tensor.cast %[[Dims]] : tensor<2xi64> to tensor<?xi64>
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// CHECK: %[[OffsetD:.*]] = tensor.cast %[[Offset]] : tensor<2xi64> to tensor<?xi64>
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// CHECK: %[[TCOO:.*]] = call @newSparseTensor(%[[BaseD]], %[[DimsD]], %[[OffsetD]], %{{.*}}, %{{.*}}, %{{.*}}, %[[C2]], %{{.}})
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// CHECK: %[[Index:.*]] = memref.alloca() : memref<2xindex>
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// CHECK: %[[IndexD:.*]] = memref.cast %[[Index]] : memref<2xindex> to memref<?xindex>
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// CHECK: scf.for %[[IV:.*]] = %[[I0]] to %[[I2]] step %[[I1]] {
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// CHECK: %[[VAL0:.*]] = tensor.extract %[[SparseI]]{{\[}}%[[IV]], %[[I0]]] : tensor<2x2xi64>
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// CHECK: %[[VAL1:.*]] = index_cast %[[VAL0]] : i64 to index
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// CHECK: memref.store %[[VAL1]], %[[Index]]{{\[}}%[[I0]]] : memref<2xindex>
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// CHECK: %[[VAL2:.*]] = tensor.extract %[[SparseI]]{{\[}}%[[IV]], %[[I1]]] : tensor<2x2xi64>
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// CHECK: %[[VAL3:.*]] = index_cast %[[VAL2]] : i64 to index
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// CHECK: memref.store %[[VAL3]], %[[Index]]{{\[}}%[[I1]]] : memref<2xindex>
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// CHECK: %[[VAL4:.*]] = tensor.extract %[[SparseV]]{{\[}}%[[IV]]] : tensor<2xf32>
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// CHECK: call @addEltF32(%[[TCOO]], %[[VAL4]], %[[IndexD]], %[[OffsetD]])
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// CHECK: }
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// CHECK: %[[T:.*]] = call @newSparseTensor(%[[BaseD]], %[[DimsD]], %[[OffsetD]], %{{.*}}, %{{.*}}, %[[C1]], %{{.*}})
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// CHECK: return %[[T]] : !llvm.ptr<i8>
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func @entry() -> tensor<8x7xf32, #CSR>{
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// Initialize a tensor.
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%0 = constant sparse<[[0, 0], [1, 6]], [1.0, 5.0]> : tensor<8x7xf32>
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// Convert the tensor to a sparse tensor.
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%1 = sparse_tensor.convert %0 : tensor<8x7xf32> to tensor<8x7xf32, #CSR>
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return %1 : tensor<8x7xf32, #CSR>
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}
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// CHECK-LABEL: func @sparse_convert_3d(
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// CHECK-SAME: %[[A:.*]]: tensor<?x?x?xf64>) -> !llvm.ptr<i8>
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// CHECK-DAG: %[[C0:.*]] = constant 0 : index
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// CHECK-DAG: %[[C1:.*]] = constant 1 : index
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// CHECK-DAG: %[[C2:.*]] = constant 2 : index
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// CHECK-DAG: %[[U:.*]] = constant dense<[0, 1, 1]> : tensor<3xi8>
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// CHECK-DAG: %[[V:.*]] = constant dense<0> : tensor<3xi64>
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// CHECK-DAG: %[[W:.*]] = constant dense<[1, 2, 0]> : tensor<3xi64>
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// CHECK-DAG: %[[X:.*]] = tensor.cast %[[U]] : tensor<3xi8> to tensor<?xi8>
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// CHECK-DAG: %[[Y:.*]] = tensor.cast %[[V]] : tensor<3xi64> to tensor<?xi64>
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// CHECK-DAG: %[[Z:.*]] = tensor.cast %[[W]] : tensor<3xi64> to tensor<?xi64>
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// CHECK: %[[C:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.}})
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// CHECK: %[[M:.*]] = memref.alloca() : memref<3xindex>
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// CHECK: %[[T:.*]] = memref.cast %[[M]] : memref<3xindex> to memref<?xindex>
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// CHECK: %[[U1:.*]] = tensor.dim %[[A]], %[[C0]] : tensor<?x?x?xf64>
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// CHECK: %[[U2:.*]] = tensor.dim %[[A]], %[[C1]] : tensor<?x?x?xf64>
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// CHECK: %[[U3:.*]] = tensor.dim %[[A]], %[[C2]] : tensor<?x?x?xf64>
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// CHECK: scf.for %[[I:.*]] = %[[C0]] to %[[U1]] step %[[C1]] {
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// CHECK: scf.for %[[J:.*]] = %[[C0]] to %[[U2]] step %[[C1]] {
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// CHECK: scf.for %[[K:.*]] = %[[C0]] to %[[U3]] step %[[C1]] {
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// CHECK: %[[E:.*]] = tensor.extract %[[A]][%[[I]], %[[J]], %[[K]]] : tensor<?x?x?xf64>
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// CHECK: memref.store %[[I]], %[[M]][%[[C0]]] : memref<3xindex>
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// CHECK: memref.store %[[J]], %[[M]][%[[C1]]] : memref<3xindex>
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// CHECK: memref.store %[[K]], %[[M]][%[[C2]]] : memref<3xindex>
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// CHECK: call @addEltF64(%[[C]], %[[E]], %[[T]], %[[Z]])
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// CHECK: }
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// CHECK: }
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// CHECK: }
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// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[C]])
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// CHECK: return %[[T]] : !llvm.ptr<i8>
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func @sparse_convert_3d(%arg0: tensor<?x?x?xf64>) -> tensor<?x?x?xf64, #SparseTensor> {
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%0 = sparse_tensor.convert %arg0 : tensor<?x?x?xf64> to tensor<?x?x?xf64, #SparseTensor>
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return %0 : tensor<?x?x?xf64, #SparseTensor>
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}
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// CHECK-LABEL: func @sparse_pointers(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
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// CHECK: %[[C:.*]] = constant 0 : index
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// CHECK: %[[T:.*]] = call @sparsePointers(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xindex>
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// CHECK: return %[[T]] : memref<?xindex>
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func @sparse_pointers(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xindex> {
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%c = constant 0 : index
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%0 = sparse_tensor.pointers %arg0, %c : tensor<128xf64, #SparseVector> to memref<?xindex>
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return %0 : memref<?xindex>
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}
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// CHECK-LABEL: func @sparse_pointers64(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
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|
// CHECK: %[[C:.*]] = constant 0 : index
|
|
// CHECK: %[[T:.*]] = call @sparsePointers64(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xi64>
|
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// CHECK: return %[[T]] : memref<?xi64>
|
|
func @sparse_pointers64(%arg0: tensor<128xf64, #SparseVector64>) -> memref<?xi64> {
|
|
%c = constant 0 : index
|
|
%0 = sparse_tensor.pointers %arg0, %c : tensor<128xf64, #SparseVector64> to memref<?xi64>
|
|
return %0 : memref<?xi64>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_pointers32(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
|
|
// CHECK: %[[C:.*]] = constant 0 : index
|
|
// CHECK: %[[T:.*]] = call @sparsePointers32(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xi32>
|
|
// CHECK: return %[[T]] : memref<?xi32>
|
|
func @sparse_pointers32(%arg0: tensor<128xf64, #SparseVector32>) -> memref<?xi32> {
|
|
%c = constant 0 : index
|
|
%0 = sparse_tensor.pointers %arg0, %c : tensor<128xf64, #SparseVector32> to memref<?xi32>
|
|
return %0 : memref<?xi32>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_indices(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
|
|
// CHECK: %[[C:.*]] = constant 0 : index
|
|
// CHECK: %[[T:.*]] = call @sparseIndices(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xindex>
|
|
// CHECK: return %[[T]] : memref<?xindex>
|
|
func @sparse_indices(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xindex> {
|
|
%c = constant 0 : index
|
|
%0 = sparse_tensor.indices %arg0, %c : tensor<128xf64, #SparseVector> to memref<?xindex>
|
|
return %0 : memref<?xindex>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_indices64(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
|
|
// CHECK: %[[C:.*]] = constant 0 : index
|
|
// CHECK: %[[T:.*]] = call @sparseIndices64(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xi64>
|
|
// CHECK: return %[[T]] : memref<?xi64>
|
|
func @sparse_indices64(%arg0: tensor<128xf64, #SparseVector64>) -> memref<?xi64> {
|
|
%c = constant 0 : index
|
|
%0 = sparse_tensor.indices %arg0, %c : tensor<128xf64, #SparseVector64> to memref<?xi64>
|
|
return %0 : memref<?xi64>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_indices32(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
|
|
// CHECK: %[[C:.*]] = constant 0 : index
|
|
// CHECK: %[[T:.*]] = call @sparseIndices32(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xi32>
|
|
// CHECK: return %[[T]] : memref<?xi32>
|
|
func @sparse_indices32(%arg0: tensor<128xf64, #SparseVector32>) -> memref<?xi32> {
|
|
%c = constant 0 : index
|
|
%0 = sparse_tensor.indices %arg0, %c : tensor<128xf64, #SparseVector32> to memref<?xi32>
|
|
return %0 : memref<?xi32>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_valuesf64(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
|
|
// CHECK: %[[T:.*]] = call @sparseValuesF64(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xf64>
|
|
// CHECK: return %[[T]] : memref<?xf64>
|
|
func @sparse_valuesf64(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xf64> {
|
|
%0 = sparse_tensor.values %arg0 : tensor<128xf64, #SparseVector> to memref<?xf64>
|
|
return %0 : memref<?xf64>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_valuesf32(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
|
|
// CHECK: %[[T:.*]] = call @sparseValuesF32(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xf32>
|
|
// CHECK: return %[[T]] : memref<?xf32>
|
|
func @sparse_valuesf32(%arg0: tensor<128xf32, #SparseVector>) -> memref<?xf32> {
|
|
%0 = sparse_tensor.values %arg0: tensor<128xf32, #SparseVector> to memref<?xf32>
|
|
return %0 : memref<?xf32>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_valuesi32(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
|
|
// CHECK: %[[T:.*]] = call @sparseValuesI32(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xi32>
|
|
// CHECK: return %[[T]] : memref<?xi32>
|
|
func @sparse_valuesi32(%arg0: tensor<128xi32, #SparseVector>) -> memref<?xi32> {
|
|
%0 = sparse_tensor.values %arg0: tensor<128xi32, #SparseVector> to memref<?xi32>
|
|
return %0 : memref<?xi32>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_valuesi16(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
|
|
// CHECK: %[[T:.*]] = call @sparseValuesI16(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xi16>
|
|
// CHECK: return %[[T]] : memref<?xi16>
|
|
func @sparse_valuesi16(%arg0: tensor<128xi16, #SparseVector>) -> memref<?xi16> {
|
|
%0 = sparse_tensor.values %arg0: tensor<128xi16, #SparseVector> to memref<?xi16>
|
|
return %0 : memref<?xi16>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_valuesi8(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
|
|
// CHECK: %[[T:.*]] = call @sparseValuesI8(%[[A]]) : (!llvm.ptr<i8>) -> memref<?xi8>
|
|
// CHECK: return %[[T]] : memref<?xi8>
|
|
func @sparse_valuesi8(%arg0: tensor<128xi8, #SparseVector>) -> memref<?xi8> {
|
|
%0 = sparse_tensor.values %arg0: tensor<128xi8, #SparseVector> to memref<?xi8>
|
|
return %0 : memref<?xi8>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_reconstruct_1(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>
|
|
// CHECK: return %[[A]] : !llvm.ptr<i8>
|
|
func @sparse_reconstruct_1(%arg0: tensor<128xf32, #DenseVector> {linalg.inplaceable = true}) -> tensor<128xf32, #DenseVector> {
|
|
%0 = sparse_tensor.values %arg0 : tensor<128xf32, #DenseVector> to memref<?xf32>
|
|
%1 = sparse_tensor.tensor %0 : memref<?xf32> to tensor<128xf32, #DenseVector>
|
|
return %1 : tensor<128xf32, #DenseVector>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_reconstruct_n(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>
|
|
// CHECK: return %[[A]] : !llvm.ptr<i8>
|
|
func @sparse_reconstruct_n(%arg0: tensor<128xf32, #SparseVector> {linalg.inplaceable = true}) -> tensor<128xf32, #SparseVector> {
|
|
%c = constant 0 : index
|
|
%0 = sparse_tensor.pointers %arg0, %c : tensor<128xf32, #SparseVector> to memref<?xindex>
|
|
%1 = sparse_tensor.indices %arg0, %c : tensor<128xf32, #SparseVector> to memref<?xindex>
|
|
%2 = sparse_tensor.values %arg0 : tensor<128xf32, #SparseVector> to memref<?xf32>
|
|
%3 = sparse_tensor.tensor %0, %1, %2 : memref<?xindex>, memref<?xindex>, memref<?xf32> to tensor<128xf32, #SparseVector>
|
|
return %3 : tensor<128xf32, #SparseVector>
|
|
}
|