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clang-p2996/mlir/test/Dialect/SparseTensor/conversion.mlir
Aart Bik bd5494d127 [mlir][sparse] make index type explicit in public API of support library 
The current implementation used explicit index->int64_t casts for some, but
not all instances of passing values of type "index" in and from the sparse
support library. This revision makes the situation more consistent by
using new "index_t" type at all such places  (which allows for less trivial
casting in the generated MLIR code).  Note that the current revision still
assumes that "index" is 64-bit wide. If we want to support targets with
alternative "index" bit widths, we need to build the support library different.
But the current revision is a step forward by making this requirement explicit
and more visible.

Reviewed By: wrengr

Differential Revision: https://reviews.llvm.org/D112122
2021-10-20 12:46:31 -07:00

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// RUN: mlir-opt %s --sparse-tensor-conversion --canonicalize --cse | FileCheck %s
#DenseVector = #sparse_tensor.encoding<{
dimLevelType = ["dense"]
}>
#SparseVector = #sparse_tensor.encoding<{
dimLevelType = ["compressed"]
}>
#SparseVector64 = #sparse_tensor.encoding<{
dimLevelType = ["compressed"],
pointerBitWidth = 64,
indexBitWidth = 64
}>
#SparseVector32 = #sparse_tensor.encoding<{
dimLevelType = ["compressed"],
pointerBitWidth = 32,
indexBitWidth = 32
}>
#SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = ["dense", "compressed"]
}>
#SparseTensor = #sparse_tensor.encoding<{
dimLevelType = ["dense", "compressed", "compressed"],
dimOrdering = affine_map<(i,j,k) -> (k,i,j)>
}>
// CHECK-LABEL: func @sparse_dim1d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[D:.*]] = call @sparseDimSize(%[[A]], %[[C]])
// CHECK: return %[[D]] : index
func @sparse_dim1d(%arg0: tensor<?xf64, #SparseVector>) -> index {
%c = arith.constant 0 : index
%0 = tensor.dim %arg0, %c : tensor<?xf64, #SparseVector>
return %0 : index
}
// CHECK-LABEL: func @sparse_dim3d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 2 : index
// CHECK: %[[D:.*]] = call @sparseDimSize(%[[A]], %[[C]])
// CHECK: return %[[D]] : index
func @sparse_dim3d(%arg0: tensor<?x?x?xf64, #SparseTensor>) -> index {
// Querying for dimension 1 in the tensor type needs to be
// permuted into querying for dimension 2 in the stored sparse
// tensor scheme, since the latter honors the dimOrdering.
%c = arith.constant 1 : index
%0 = tensor.dim %arg0, %c : tensor<?x?x?xf64, #SparseTensor>
return %0 : index
}
// CHECK-LABEL: func @sparse_dim3d_const(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 20 : index
// CHECK: return %[[C]] : index
func @sparse_dim3d_const(%arg0: tensor<10x20x30xf64, #SparseTensor>) -> index {
// Querying for dimension 1 in the tensor type can be directly
// folded into the right value (even though it corresponds
// to dimension 2 in the stored sparse tensor scheme).
%c = arith.constant 1 : index
%0 = tensor.dim %arg0, %c : tensor<10x20x30xf64, #SparseTensor>
return %0 : index
}
// CHECK-LABEL: func @sparse_new1d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[P:.*]] = memref.alloca() : memref<1xi8>
// CHECK-DAG: %[[Q:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[R:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[X:.*]] = memref.cast %[[P]] : memref<1xi8> to memref<?xi8>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[Q]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[Z:.*]] = memref.cast %[[R]] : memref<1xindex> to memref<?xindex>
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[A]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func @sparse_new1d(%arg0: !llvm.ptr<i8>) -> tensor<128xf64, #SparseVector> {
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<128xf64, #SparseVector>
return %0 : tensor<128xf64, #SparseVector>
}
// CHECK-LABEL: func @sparse_new2d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[P:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[Q:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[R:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[X:.*]] = memref.cast %[[P]] : memref<2xi8> to memref<?xi8>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[Q]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[Z:.*]] = memref.cast %[[R]] : memref<2xindex> to memref<?xindex>
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[A]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func @sparse_new2d(%arg0: !llvm.ptr<i8>) -> tensor<?x?xf32, #SparseMatrix> {
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?xf32, #SparseMatrix>
return %0 : tensor<?x?xf32, #SparseMatrix>
}
// CHECK-LABEL: func @sparse_new3d(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[P:.*]] = memref.alloca() : memref<3xi8>
// CHECK-DAG: %[[Q:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[R:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[X:.*]] = memref.cast %[[P]] : memref<3xi8> to memref<?xi8>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[Q]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: %[[Z:.*]] = memref.cast %[[R]] : memref<3xindex> to memref<?xindex>
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[A]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func @sparse_new3d(%arg0: !llvm.ptr<i8>) -> tensor<?x?x?xf32, #SparseTensor> {
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?x?xf32, #SparseTensor>
return %0 : tensor<?x?x?xf32, #SparseTensor>
}
// CHECK-LABEL: func @sparse_init(
// CHECK-SAME: %[[I:.*]]: index,
// CHECK-SAME: %[[J:.*]]: index) -> !llvm.ptr<i8>
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[P:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[Q:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[R:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[X:.*]] = memref.cast %[[P]] : memref<2xi8> to memref<?xi8>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[Q]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[Z:.*]] = memref.cast %[[R]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I]], %[[Q]][%[[C0]]] : memref<2xindex>
// CHECK-DAG: memref.store %[[J]], %[[Q]][%[[C1]]] : memref<2xindex>
// CHECK: %[[NP:.*]] = llvm.mlir.null : !llvm.ptr<i8>
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[NP]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func @sparse_init(%arg0: index, %arg1: index) -> tensor<?x?xf64, #SparseMatrix> {
%0 = sparse_tensor.init [%arg0, %arg1] : tensor<?x?xf64, #SparseMatrix>
return %0 : tensor<?x?xf64, #SparseMatrix>
}
// CHECK-LABEL: func @sparse_release(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: call @delSparseTensor(%[[A]]) : (!llvm.ptr<i8>) -> ()
// CHECK: return
func @sparse_release(%arg0: tensor<128xf64, #SparseVector>) {
sparse_tensor.release %arg0 : tensor<128xf64, #SparseVector>
return
}
// CHECK-LABEL: func @sparse_nop_convert(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> !llvm.ptr<i8>
// CHECK: return %[[A]] : !llvm.ptr<i8>
func @sparse_nop_convert(%arg0: tensor<64xf32, #SparseVector>) -> tensor<64xf32, #SparseVector> {
%0 = sparse_tensor.convert %arg0 : tensor<64xf32, #SparseVector> to tensor<64xf32, #SparseVector>
return %0 : tensor<64xf32, #SparseVector>
}
// CHECK-LABEL: func @sparse_convert_1d(
// CHECK-SAME: %[[A:.*]]: tensor<?xi32>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[U:.*]] = tensor.dim %[[A]], %[[C0]] : tensor<?xi32>
// CHECK-DAG: %[[P:.*]] = memref.alloca() : memref<1xi8>
// CHECK-DAG: %[[Q:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[R:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[X:.*]] = memref.cast %[[P]] : memref<1xi8> to memref<?xi8>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[Q]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[Z:.*]] = memref.cast %[[R]] : memref<1xindex> to memref<?xindex>
// CHECK: %[[NP:.*]] = llvm.mlir.null : !llvm.ptr<i8>
// CHECK: %[[C:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[NP]])
// CHECK: %[[M:.*]] = memref.alloca() : memref<1xindex>
// CHECK: %[[T:.*]] = memref.cast %[[M]] : memref<1xindex> to memref<?xindex>
// CHECK: scf.for %[[I:.*]] = %[[C0]] to %[[U]] step %[[C1]] {
// CHECK: %[[E:.*]] = tensor.extract %[[A]][%[[I]]] : tensor<?xi32>
// CHECK: memref.store %[[I]], %[[M]][%[[C0]]] : memref<1xindex>
// CHECK: call @addEltI32(%[[C]], %[[E]], %[[T]], %[[Z]])
// CHECK: }
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[C]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func @sparse_convert_1d(%arg0: tensor<?xi32>) -> tensor<?xi32, #SparseVector> {
%0 = sparse_tensor.convert %arg0 : tensor<?xi32> to tensor<?xi32, #SparseVector>
return %0 : tensor<?xi32, #SparseVector>
}
// CHECK-LABEL: func @sparse_convert_1d_ss(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK-DAG: %[[P:.*]] = memref.alloca() : memref<1xi8>
// CHECK-DAG: %[[Q:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[R:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[X:.*]] = memref.cast %[[P]] : memref<1xi8> to memref<?xi8>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[Q]] : memref<1xindex> to memref<?xindex>
// CHECK-DAG: %[[Z:.*]] = memref.cast %[[R]] : memref<1xindex> to memref<?xindex>
// CHECK: %[[C:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[A]])
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[C]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func @sparse_convert_1d_ss(%arg0: tensor<?xf32, #SparseVector64>) -> tensor<?xf32, #SparseVector32> {
%0 = sparse_tensor.convert %arg0 : tensor<?xf32, #SparseVector64> to tensor<?xf32, #SparseVector32>
return %0 : tensor<?xf32, #SparseVector32>
}
// CHECK-LABEL: func @sparse_convert_2d(
// CHECK-SAME: %[[A:.*]]: tensor<2x4xf64>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[P:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[Q:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[R:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[X:.*]] = memref.cast %[[P]] : memref<2xi8> to memref<?xi8>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[Q]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[Z:.*]] = memref.cast %[[R]] : memref<2xindex> to memref<?xindex>
// CHECK: %[[NP:.*]] = llvm.mlir.null : !llvm.ptr<i8>
// CHECK: %[[C:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[NP]])
// CHECK: %[[M:.*]] = memref.alloca() : memref<2xindex>
// CHECK: %[[T:.*]] = memref.cast %[[M]] : memref<2xindex> to memref<?xindex>
// CHECK: scf.for %[[I:.*]] = %[[C0]] to %{{.*}} step %[[C1]] {
// CHECK: scf.for %[[J:.*]] = %[[C0]] to %{{.*}} step %[[C1]] {
// CHECK: %[[E:.*]] = tensor.extract %[[A]][%[[I]], %[[J]]] : tensor<2x4xf64>
// CHECK: memref.store %[[I]], %[[M]][%[[C0]]] : memref<2xindex>
// CHECK: memref.store %[[J]], %[[M]][%[[C1]]] : memref<2xindex>
// CHECK: call @addEltF64(%[[C]], %[[E]], %[[T]], %[[Z]])
// CHECK: }
// CHECK: }
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[C]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func @sparse_convert_2d(%arg0: tensor<2x4xf64>) -> tensor<2x4xf64, #SparseMatrix> {
%0 = sparse_tensor.convert %arg0 : tensor<2x4xf64> to tensor<2x4xf64, #SparseMatrix>
return %0 : tensor<2x4xf64, #SparseMatrix>
}
// CHECK-LABEL: func @sparse_constant() -> !llvm.ptr<i8> {
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[P:.*]] = memref.alloca() : memref<2xi8>
// CHECK-DAG: %[[Q:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[R:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[X:.*]] = memref.cast %[[P]] : memref<2xi8> to memref<?xi8>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[Q]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[Z:.*]] = memref.cast %[[R]] : memref<2xindex> to memref<?xindex>
// CHECK: %[[NP:.*]] = llvm.mlir.null : !llvm.ptr<i8>
// CHECK: %[[C:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[NP]])
// CHECK: %[[M:.*]] = memref.alloca() : memref<2xindex>
// CHECK: %[[N:.*]] = memref.cast %[[M]] : memref<2xindex> to memref<?xindex>
// CHECK: scf.for %[[I:.*]] = %[[C0]] to %[[C2]] step %[[C1]] {
// CHECK: memref.store %{{.*}}, %[[M]][%[[C0]]] : memref<2xindex>
// CHECK: memref.store %{{.*}}, %[[M]][%[[C1]]] : memref<2xindex>
// CHECK: %[[V:.*]] = tensor.extract %{{.*}}[%[[I]]] : tensor<2xf32>
// CHECK: call @addEltF32(%{{.*}}, %[[V]], %[[N]], %{{.*}})
// CHECK: }
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[C]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func @sparse_constant() -> tensor<8x7xf32, #SparseMatrix>{
// Initialize a tensor.
%0 = arith.constant sparse<[[0, 0], [1, 6]], [1.0, 5.0]> : tensor<8x7xf32>
// Convert the tensor to a sparse tensor.
%1 = sparse_tensor.convert %0 : tensor<8x7xf32> to tensor<8x7xf32, #SparseMatrix>
return %1 : tensor<8x7xf32, #SparseMatrix>
}
// CHECK-LABEL: func @sparse_convert_3d(
// CHECK-SAME: %[[A:.*]]: tensor<?x?x?xf64>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[U1:.*]] = tensor.dim %[[A]], %[[C0]] : tensor<?x?x?xf64>
// CHECK-DAG: %[[U2:.*]] = tensor.dim %[[A]], %[[C1]] : tensor<?x?x?xf64>
// CHECK-DAG: %[[U3:.*]] = tensor.dim %[[A]], %[[C2]] : tensor<?x?x?xf64>
// CHECK-DAG: %[[P:.*]] = memref.alloca() : memref<3xi8>
// CHECK-DAG: %[[Q:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[R:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[X:.*]] = memref.cast %[[P]] : memref<3xi8> to memref<?xi8>
// CHECK-DAG: %[[Y:.*]] = memref.cast %[[Q]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: %[[Z:.*]] = memref.cast %[[R]] : memref<3xindex> to memref<?xindex>
// CHECK: %[[NP:.*]] = llvm.mlir.null : !llvm.ptr<i8>
// CHECK: %[[C:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[NP]])
// CHECK: %[[M:.*]] = memref.alloca() : memref<3xindex>
// CHECK: %[[N:.*]] = memref.cast %[[M]] : memref<3xindex> to memref<?xindex>
// CHECK: scf.for %[[I:.*]] = %[[C0]] to %[[U1]] step %[[C1]] {
// CHECK: scf.for %[[J:.*]] = %[[C0]] to %[[U2]] step %[[C1]] {
// CHECK: scf.for %[[K:.*]] = %[[C0]] to %[[U3]] step %[[C1]] {
// CHECK: %[[E:.*]] = tensor.extract %[[A]][%[[I]], %[[J]], %[[K]]] : tensor<?x?x?xf64>
// CHECK: memref.store %[[I]], %[[M]][%[[C0]]] : memref<3xindex>
// CHECK: memref.store %[[J]], %[[M]][%[[C1]]] : memref<3xindex>
// CHECK: memref.store %[[K]], %[[M]][%[[C2]]] : memref<3xindex>
// CHECK: call @addEltF64(%[[C]], %[[E]], %[[N]], %[[Z]])
// CHECK: }
// CHECK: }
// CHECK: }
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[C]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func @sparse_convert_3d(%arg0: tensor<?x?x?xf64>) -> tensor<?x?x?xf64, #SparseTensor> {
%0 = sparse_tensor.convert %arg0 : tensor<?x?x?xf64> to tensor<?x?x?xf64, #SparseTensor>
return %0 : tensor<?x?x?xf64, #SparseTensor>
}
// CHECK-LABEL: func @sparse_pointers(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[T:.*]] = call @sparsePointers(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xindex>
// CHECK: return %[[T]] : memref<?xindex>
func @sparse_pointers(%arg0: tensor<128xf64, #SparseVector>) -> memref<?xindex> {
%c = arith.constant 0 : index
%0 = sparse_tensor.pointers %arg0, %c : tensor<128xf64, #SparseVector> to memref<?xindex>
return %0 : memref<?xindex>
}
// CHECK-LABEL: func @sparse_pointers64(
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>)
// CHECK: %[[C:.*]] = arith.constant 0 : index
// CHECK: %[[T:.*]] = call @sparsePointers64(%[[A]], %[[C]]) : (!llvm.ptr<i8>, index) -> memref<?xi64>
// CHECK: return %[[T]] : memref<?xi64>
func @sparse_pointers64(%arg0: tensor<128xf64, #SparseVector64>) -> memref<?xi64> {
%c = arith.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:.*]] = arith.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 = arith.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:.*]] = arith.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 = arith.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:.*]] = arith.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 = arith.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:.*]] = arith.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 = arith.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 = arith.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>
}
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