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llvm-project/mlir/test/Dialect/SparseTensor/convert_dense2sparse.mlir
bixia1 b056d0bb69 [mlir][sparse] Refactor the convert operator conversion to support codegen for the operator. 
Outline the code that generates the loop structure to iterate over a dense
tensor or a sparse constant to genDenseTensorOrSparseConstantIterLoop.

Move a few routines to CodegenUtils for sharing.

Reviewed By: wrengr

Differential Revision: https://reviews.llvm.org/D136210
2022-10-21 08:52:47 -07:00

183 lines
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// RUN: mlir-opt %s --sparse-tensor-conversion --canonicalize --cse | FileCheck %s
#SparseVector = #sparse_tensor.encoding<{
dimLevelType = ["compressed"]
}>
#CSR = #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_convert_1d(
// CHECK-SAME: %[[A:.*]]: tensor<?xi32>) -> !llvm.ptr<i8> {
// CHECK-DAG: %[[EmptyCOO:.*]] = arith.constant 4 : i32
// CHECK-DAG: %[[FromCOO:.*]] = arith.constant 2 : i32
// CHECK-DAG: %[[I0:.*]] = arith.constant 0 : i32
// 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]], %{{.*}}, %{{.*}}, %{{.*}}, %[[EmptyCOO]], %[[NP]])
// CHECK: %[[M:.*]] = memref.alloca() : memref<1xindex>
// CHECK: %[[T:.*]] = memref.cast %[[M]] : memref<1xindex> to memref<?xindex>
// CHECK: %[[BUF:.*]] = memref.alloca() : memref<i32>
// CHECK: scf.for %[[I:.*]] = %[[C0]] to %[[U]] step %[[C1]] {
// CHECK: %[[E:.*]] = tensor.extract %[[A]][%[[I]]] : tensor<?xi32>
// CHECK: %[[N:.*]] = arith.cmpi ne, %[[E]], %[[I0]] : i32
// CHECK: scf.if %[[N]] {
// CHECK: memref.store %[[I]], %[[M]][%[[C0]]] : memref<1xindex>
// CHECK: memref.store %[[E]], %[[BUF]][] : memref<i32>
// CHECK: call @addEltI32(%[[C]], %[[BUF]], %[[T]], %[[Z]])
// CHECK: }
// CHECK: }
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %[[FromCOO]], %[[C]])
// CHECK: call @delSparseTensorCOOI32(%[[C]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func.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_complex(
// CHECK-SAME: %[[A:.*]]: tensor<100xcomplex<f64>>) -> !llvm.ptr<i8> {
// CHECK-DAG: %[[CC:.*]] = complex.constant [0.000000e+00, 0.000000e+00] : complex<f64>
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[C100:.*]] = arith.constant 100 : index
// CHECK: scf.for %[[I:.*]] = %[[C0]] to %[[C100]] step %[[C1]] {
// CHECK: %[[E:.*]] = tensor.extract %[[A]][%[[I]]] : tensor<100xcomplex<f64>>
// CHECK: %[[N:.*]] = complex.neq %[[E]], %[[CC]] : complex<f64>
// CHECK: scf.if %[[N]] {
// CHECK: memref.store %[[I]], %{{.*}}[%[[C0]]] : memref<1xindex>
// CHECK: call @addEltC64
// CHECK: }
// CHECK: }
// CHECK: %[[T:.*]] = call @newSparseTensor
// CHECK: call @delSparseTensorCOOC64
// CHECK: return %[[T]] : !llvm.ptr<i8>
func.func @sparse_convert_complex(%arg0: tensor<100xcomplex<f64>>) -> tensor<100xcomplex<f64>, #SparseVector> {
%0 = sparse_tensor.convert %arg0 : tensor<100xcomplex<f64>> to tensor<100xcomplex<f64>, #SparseVector>
return %0 : tensor<100xcomplex<f64>, #SparseVector>
}
// CHECK-LABEL: func @sparse_convert_2d(
// CHECK-SAME: %[[A:.*]]: tensor<2x4xf64>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[EmptyCOO:.*]] = arith.constant 4 : i32
// CHECK-DAG: %[[FromCOO:.*]] = arith.constant 2 : i32
// 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]], %{{.*}}, %{{.*}}, %{{.*}}, %[[EmptyCOO]], %[[NP]])
// CHECK: %[[M:.*]] = memref.alloca() : memref<2xindex>
// CHECK: %[[T:.*]] = memref.cast %[[M]] : memref<2xindex> to memref<?xindex>
// CHECK: %[[BUF:.*]] = memref.alloca() : memref<f64>
// 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: memref.store %[[E]], %[[BUF]][] : memref<f64>
// CHECK: call @addEltF64(%[[C]], %[[BUF]], %[[T]], %[[Z]])
// CHECK: }
// CHECK: }
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %[[FromCOO]], %[[C]])
// CHECK: call @delSparseTensorCOOF64(%[[C]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func.func @sparse_convert_2d(%arg0: tensor<2x4xf64>) -> tensor<2x4xf64, #CSR> {
%0 = sparse_tensor.convert %arg0 : tensor<2x4xf64> to tensor<2x4xf64, #CSR>
return %0 : tensor<2x4xf64, #CSR>
}
// CHECK-LABEL: func @sparse_constant() -> !llvm.ptr<i8> {
// CHECK-DAG: %[[EmptyCOO:.*]] = arith.constant 4 : i32
// CHECK-DAG: %[[FromCOO:.*]] = arith.constant 2 : i32
// 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]], %{{.*}}, %{{.*}}, %{{.*}}, %[[EmptyCOO]], %[[NP]])
// CHECK: %[[M:.*]] = memref.alloca() : memref<2xindex>
// CHECK: %[[N:.*]] = memref.cast %[[M]] : memref<2xindex> to memref<?xindex>
// CHECK: %[[BUF:.*]] = memref.alloca() : memref<f32>
// CHECK: scf.for %[[I:.*]] = %[[C0]] to %[[C2]] step %[[C1]] {
// CHECK-DAG: memref.store %{{.*}}, %[[M]][%[[C0]]] : memref<2xindex>
// CHECK-DAG: memref.store %{{.*}}, %[[M]][%[[C1]]] : memref<2xindex>
// CHECK-DAG: %[[V:.*]] = tensor.extract %{{.*}}[%[[I]]] : tensor<2xf32>
// CHECK: memref.store %[[V]], %[[BUF]][] : memref<f32>
// CHECK: call @addEltF32(%{{.*}}, %[[BUF]], %[[N]], %{{.*}})
// CHECK: }
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %[[FromCOO]], %[[C]])
// CHECK: call @delSparseTensorCOOF32(%[[C]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func.func @sparse_constant() -> tensor<8x7xf32, #CSR>{
// 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, #CSR>
return %1 : tensor<8x7xf32, #CSR>
}
// CHECK-LABEL: func @sparse_convert_3d(
// CHECK-SAME: %[[A:.*]]: tensor<?x?x?xf64>) -> !llvm.ptr<i8>
// CHECK-DAG: %[[EmptyCOO:.*]] = arith.constant 4 : i32
// CHECK-DAG: %[[FromCOO:.*]] = arith.constant 2 : i32
// 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]], %{{.*}}, %{{.*}}, %{{.*}}, %[[EmptyCOO]], %[[NP]])
// CHECK: %[[M:.*]] = memref.alloca() : memref<3xindex>
// CHECK: %[[N:.*]] = memref.cast %[[M]] : memref<3xindex> to memref<?xindex>
// CHECK: %[[BUF:.*]] = memref.alloca() : memref<f64>
// 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: memref.store %[[E]], %[[BUF]][] : memref<f64>
// CHECK: call @addEltF64(%[[C]], %[[BUF]], %[[N]], %[[Z]])
// CHECK: }
// CHECK: }
// CHECK: }
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[X]], %[[Y]], %[[Z]], %{{.*}}, %{{.*}}, %{{.*}}, %[[FromCOO]], %[[C]])
// CHECK: call @delSparseTensorCOOF64(%[[C]])
// CHECK: return %[[T]] : !llvm.ptr<i8>
func.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>
}
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