608 lines
30 KiB
MLIR
608 lines
30 KiB
MLIR
// RUN: mlir-opt %s --sparse-tensor-codegen --canonicalize --cse | FileCheck %s
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#SV = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>
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#SparseVector = #sparse_tensor.encoding<{
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dimLevelType = [ "compressed" ],
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indexBitWidth = 64,
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pointerBitWidth = 32
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}>
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#Dense2D = #sparse_tensor.encoding<{
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dimLevelType = [ "dense", "dense" ],
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indexBitWidth = 64,
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pointerBitWidth = 32
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}>
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#Row = #sparse_tensor.encoding<{
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dimLevelType = [ "compressed", "dense" ],
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indexBitWidth = 64,
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pointerBitWidth = 32
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}>
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#CSR = #sparse_tensor.encoding<{
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dimLevelType = [ "dense", "compressed" ],
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indexBitWidth = 64,
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pointerBitWidth = 32
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}>
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#UCSR = #sparse_tensor.encoding<{
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dimLevelType = [ "dense", "compressed-no" ]
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}>
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#CSC = #sparse_tensor.encoding<{
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dimLevelType = [ "dense", "compressed" ],
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dimOrdering = affine_map<(i, j) -> (j, i)>
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}>
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#DCSR = #sparse_tensor.encoding<{
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dimLevelType = [ "compressed", "compressed" ],
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indexBitWidth = 64,
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pointerBitWidth = 32
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}>
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#Dense3D = #sparse_tensor.encoding<{
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dimLevelType = [ "dense", "dense", "dense" ],
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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_nop(
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// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>)
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// CHECK: return %[[A0]], %[[A1]], %[[A2]], %[[A3]], %[[A4]] :
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// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf64>
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func.func @sparse_nop(%arg0: tensor<?xf64, #SparseVector>) -> tensor<?xf64, #SparseVector> {
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return %arg0 : tensor<?xf64, #SparseVector>
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}
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// CHECK-LABEL: func @sparse_nop_multi_ret(
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// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
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// CHECK-SAME: %[[A5:.*5]]: memref<1xindex>,
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// CHECK-SAME: %[[A6:.*6]]: memref<3xindex>,
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// CHECK-SAME: %[[A7:.*7]]: memref<?xi32>,
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// CHECK-SAME: %[[A8:.*8]]: memref<?xi64>,
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// CHECK-SAME: %[[A9:.*9]]: memref<?xf64>)
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// CHECK: return %[[A0]], %[[A1]], %[[A2]], %[[A3]], %[[A4]], %[[A5]], %[[A6]], %[[A7]], %[[A8]], %[[A9]] :
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// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf64>,
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// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf64>
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func.func @sparse_nop_multi_ret(%arg0: tensor<?xf64, #SparseVector>,
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%arg1: tensor<?xf64, #SparseVector>) ->
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(tensor<?xf64, #SparseVector>, tensor<?xf64, #SparseVector>) {
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return %arg0, %arg1 : tensor<?xf64, #SparseVector>, tensor<?xf64, #SparseVector>
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}
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// CHECK-LABEL: func @sparse_nop_call(
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// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
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// CHECK-SAME: %[[A5:.*5]]: memref<1xindex>,
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// CHECK-SAME: %[[A6:.*6]]: memref<3xindex>,
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// CHECK-SAME: %[[A7:.*7]]: memref<?xi32>,
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// CHECK-SAME: %[[A8:.*8]]: memref<?xi64>,
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// CHECK-SAME: %[[A9:.*9]]: memref<?xf64>)
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// CHECK: %[[T:.*]]:10 = call @sparse_nop_multi_ret(%[[A0]], %[[A1]], %[[A2]], %[[A3]], %[[A4]], %[[A5]], %[[A6]], %[[A7]], %[[A8]], %[[A9]])
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// CHECK: return %[[T]]#0, %[[T]]#1, %[[T]]#2, %[[T]]#3, %[[T]]#4, %[[T]]#5, %[[T]]#6, %[[T]]#7, %[[T]]#8, %[[T]]#9 :
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// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf64>,
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// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf64>
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func.func @sparse_nop_call(%arg0: tensor<?xf64, #SparseVector>,
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%arg1: tensor<?xf64, #SparseVector>) ->
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(tensor<?xf64, #SparseVector>, tensor<?xf64, #SparseVector>) {
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%1, %2 = call @sparse_nop_multi_ret(%arg0, %arg1) :
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(tensor<?xf64, #SparseVector>, tensor<?xf64, #SparseVector>) ->
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(tensor<?xf64, #SparseVector>, tensor<?xf64, #SparseVector>)
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return %1, %2: tensor<?xf64, #SparseVector>, tensor<?xf64, #SparseVector>
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}
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// CHECK-LABEL: func @sparse_nop_cast(
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// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf32>)
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// CHECK: return %[[A0]], %[[A1]], %[[A2]], %[[A3]], %[[A4]] :
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// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf32>
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func.func @sparse_nop_cast(%arg0: tensor<64xf32, #SparseVector>) -> tensor<?xf32, #SparseVector> {
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%0 = tensor.cast %arg0 : tensor<64xf32, #SparseVector> to tensor<?xf32, #SparseVector>
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return %0 : tensor<?xf32, #SparseVector>
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}
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// CHECK-LABEL: func @sparse_nop_cast_3d(
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// CHECK-SAME: %[[A0:.*0]]: memref<3xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<1xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xf32>)
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// CHECK: return %[[A0]], %[[A1]], %[[A2]] :
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// CHECK-SAME: memref<3xindex>, memref<1xindex>, memref<?xf32>
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func.func @sparse_nop_cast_3d(%arg0: tensor<10x20x30xf32, #Dense3D>) -> tensor<?x?x?xf32, #Dense3D> {
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%0 = tensor.cast %arg0 : tensor<10x20x30xf32, #Dense3D> to tensor<?x?x?xf32, #Dense3D>
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return %0 : tensor<?x?x?xf32, #Dense3D>
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}
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// CHECK-LABEL: func @sparse_dense_2d(
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// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<1xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xf64>)
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// CHECK: return
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func.func @sparse_dense_2d(%arg0: tensor<?x?xf64, #Dense2D>) {
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return
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}
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// CHECK-LABEL: func @sparse_row(
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// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>)
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// CHECK: return
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func.func @sparse_row(%arg0: tensor<?x?xf64, #Row>) {
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return
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}
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// CHECK-LABEL: func @sparse_csr(
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// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>)
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// CHECK: return
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func.func @sparse_csr(%arg0: tensor<?x?xf64, #CSR>) {
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return
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}
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// CHECK-LABEL: func @sparse_dcsr(
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// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<5xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xi32>,
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// CHECK-SAME: %[[A5:.*5]]: memref<?xi64>,
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// CHECK-SAME: %[[A6:.*6]]: memref<?xf64>)
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// CHECK: return
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func.func @sparse_dcsr(%arg0: tensor<?x?xf64, #DCSR>) {
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return
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}
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//
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// Querying for dimension 1 in the tensor type can immediately
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// fold using the original static dimension sizes.
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//
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// CHECK-LABEL: func @sparse_dense_3d(
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// CHECK-SAME: %[[A0:.*0]]: memref<3xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<1xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xf64>)
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// CHECK: %[[C:.*]] = arith.constant 20 : index
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// CHECK: return %[[C]] : index
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func.func @sparse_dense_3d(%arg0: tensor<10x20x30xf64, #Dense3D>) -> index {
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%c = arith.constant 1 : index
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%0 = tensor.dim %arg0, %c : tensor<10x20x30xf64, #Dense3D>
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return %0 : index
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}
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//
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// Querying for dimension 1 in the tensor type needs to be permuted
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// into querying for dimension 2 in the stored sparse tensor scheme,
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// since the latter honors the dimOrdering.
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//
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// CHECK-LABEL: func @sparse_dense_3d_dyn(
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// CHECK-SAME: %[[A0:.*0]]: memref<3xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<1xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xf64>)
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// CHECK: %[[C:.*]] = arith.constant 2 : index
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// CHECK: %[[L:.*]] = memref.load %[[A0]][%[[C]]] : memref<3xindex>
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// CHECK: return %[[L]] : index
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func.func @sparse_dense_3d_dyn(%arg0: tensor<?x?x?xf64, #Dense3D>) -> index {
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%c = arith.constant 1 : index
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%0 = tensor.dim %arg0, %c : tensor<?x?x?xf64, #Dense3D>
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return %0 : index
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}
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// CHECK-LABEL: func @sparse_pointers_dcsr(
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// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<5xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xi32>,
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// CHECK-SAME: %[[A5:.*5]]: memref<?xi64>,
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// CHECK-SAME: %[[A6:.*6]]: memref<?xf64>)
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// CHECK: return %[[A4]] : memref<?xi32>
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func.func @sparse_pointers_dcsr(%arg0: tensor<?x?xf64, #DCSR>) -> memref<?xi32> {
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%0 = sparse_tensor.pointers %arg0 { dimension = 1 : index } : tensor<?x?xf64, #DCSR> to memref<?xi32>
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return %0 : memref<?xi32>
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}
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// CHECK-LABEL: func @sparse_indices_dcsr(
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// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<5xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xi32>,
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// CHECK-SAME: %[[A5:.*5]]: memref<?xi64>,
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// CHECK-SAME: %[[A6:.*6]]: memref<?xf64>)
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// CHECK: return %[[A5]] : memref<?xi64>
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func.func @sparse_indices_dcsr(%arg0: tensor<?x?xf64, #DCSR>) -> memref<?xi64> {
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%0 = sparse_tensor.indices %arg0 { dimension = 1 : index } : tensor<?x?xf64, #DCSR> to memref<?xi64>
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return %0 : memref<?xi64>
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}
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// CHECK-LABEL: func @sparse_values_dcsr(
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// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<5xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xi32>,
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// CHECK-SAME: %[[A5:.*5]]: memref<?xi64>,
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// CHECK-SAME: %[[A6:.*6]]: memref<?xf64>)
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// CHECK: return %[[A6]] : memref<?xf64>
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func.func @sparse_values_dcsr(%arg0: tensor<?x?xf64, #DCSR>) -> memref<?xf64> {
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%0 = sparse_tensor.values %arg0 : tensor<?x?xf64, #DCSR> to memref<?xf64>
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return %0 : memref<?xf64>
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}
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// CHECK-LABEL: func @sparse_noe(
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// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>)
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// CHECK: %[[C2:.*]] = arith.constant 2 : index
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// CHECK: %[[NOE:.*]] = memref.load %[[A1]][%[[C2]]] : memref<3xindex>
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// CHECK: return %[[NOE]] : index
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func.func @sparse_noe(%arg0: tensor<128xf64, #SparseVector>) -> index {
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%0 = sparse_tensor.number_of_entries %arg0 : tensor<128xf64, #SparseVector>
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return %0 : index
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}
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// CHECK-LABEL: func @sparse_dealloc_csr(
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// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>)
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// CHECK: memref.dealloc %[[A0]] : memref<2xindex>
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// CHECK: memref.dealloc %[[A1]] : memref<3xindex>
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// CHECK: memref.dealloc %[[A2]] : memref<?xi32>
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// CHECK: memref.dealloc %[[A3]] : memref<?xi64>
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// CHECK: memref.dealloc %[[A4]] : memref<?xf64>
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// CHECK: return
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func.func @sparse_dealloc_csr(%arg0: tensor<?x?xf64, #CSR>) {
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bufferization.dealloc_tensor %arg0 : tensor<?x?xf64, #CSR>
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return
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}
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// CHECK-LABEL: func @sparse_alloc_csc(
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// CHECK-SAME: %[[A:.*]]: index) ->
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// CHECK-SAME: memref<2xindex>, memref<3xindex>, memref<?xindex>, memref<?xindex>, memref<?xf64>
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// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
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// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
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// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
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// CHECK: %[[T0:.*]] = memref.alloc() : memref<2xindex>
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// CHECK: %[[T1:.*]] = memref.alloc() : memref<3xindex>
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// CHECK: %[[T2:.*]] = memref.alloc() : memref<16xindex>
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// CHECK: %[[T3:.*]] = memref.cast %[[T2]] : memref<16xindex> to memref<?xindex>
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// CHECK: %[[T4:.*]] = memref.alloc() : memref<16xindex>
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// CHECK: %[[T5:.*]] = memref.cast %[[T4]] : memref<16xindex> to memref<?xindex>
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// CHECK: %[[T6:.*]] = memref.alloc() : memref<16xf64>
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// CHECK: %[[T7:.*]] = memref.cast %[[T6]] : memref<16xf64> to memref<?xf64>
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// CHECK: linalg.fill ins(%[[C0]] : index) outs(%[[T1]] : memref<3xindex>)
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// CHECK: memref.store %[[A]], %[[T0]][%[[C0]]] : memref<2xindex>
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// CHECK: memref.store %[[C10]], %[[T0]][%[[C1]]] : memref<2xindex>
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// CHECK: %[[P0:.*]] = sparse_tensor.push_back %[[T1]], %[[T3]]
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// CHECK: %[[P1:.*]] = sparse_tensor.push_back %[[T1]], %[[P0]]
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// CHECK: return %[[T0]], %[[T1]], %[[P1]], %[[T5]], %[[T7]] :
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// CHECK-SAME: memref<2xindex>, memref<3xindex>, memref<?xindex>, memref<?xindex>, memref<?xf64>
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func.func @sparse_alloc_csc(%arg0: index) -> tensor<10x?xf64, #CSC> {
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%0 = bufferization.alloc_tensor(%arg0) : tensor<10x?xf64, #CSC>
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%1 = sparse_tensor.load %0 : tensor<10x?xf64, #CSC>
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return %1 : tensor<10x?xf64, #CSC>
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}
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// CHECK-LABEL: func @sparse_alloc_3d() ->
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// CHECK-SAME: memref<3xindex>, memref<1xindex>, memref<?xf64>
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// CHECK-DAG: %[[F0:.*]] = arith.constant 0.000000e+00 : f64
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// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
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// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
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// CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index
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// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
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// CHECK-DAG: %[[C20:.*]] = arith.constant 20 : index
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// CHECK-DAG: %[[C30:.*]] = arith.constant 30 : index
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// CHECK-DAG: %[[C6000:.*]] = arith.constant 6000 : index
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// CHECK: %[[A0:.*]] = memref.alloc() : memref<3xindex>
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// CHECK: %[[A1:.*]] = memref.alloc() : memref<1xindex>
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// CHECK: %[[AV:.*]] = memref.alloc() : memref<16xf64>
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// CHECK: %[[A2:.*]] = memref.cast %[[AV]] : memref<16xf64> to memref<?xf64>
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// CHECK: linalg.fill ins(%[[C0]] : index) outs(%[[A1]] : memref<1xindex>)
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// CHECK: memref.store %[[C30]], %[[A0]][%[[C0]]] : memref<3xindex>
|
|
// CHECK: memref.store %[[C10]], %[[A0]][%[[C1]]] : memref<3xindex>
|
|
// CHECK: memref.store %[[C20]], %[[A0]][%[[C2]]] : memref<3xindex>
|
|
// CHECK: %[[P:.*]] = sparse_tensor.push_back %[[A1]], %[[A2]], %[[F0]], %[[C6000]]
|
|
// CHECK: return %[[A0]], %[[A1]], %[[P]] :
|
|
// CHECK-SAME: memref<3xindex>, memref<1xindex>, memref<?xf64>
|
|
func.func @sparse_alloc_3d() -> tensor<10x20x30xf64, #Dense3D> {
|
|
%0 = bufferization.alloc_tensor() : tensor<10x20x30xf64, #Dense3D>
|
|
%1 = sparse_tensor.load %0 : tensor<10x20x30xf64, #Dense3D>
|
|
return %1 : tensor<10x20x30xf64, #Dense3D>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func @sparse_expansion1()
|
|
// CHECK: %[[A:.*]] = memref.alloc() : memref<8xf64>
|
|
// CHECK: %[[B:.*]] = memref.alloc() : memref<8xi1>
|
|
// CHECK: %[[C:.*]] = memref.alloc() : memref<8xindex>
|
|
// CHECK: %[[D:.*]] = memref.cast %[[C]] : memref<8xindex> to memref<?xindex>
|
|
// CHECK-DAG: linalg.fill ins(%{{.*}} : f64) outs(%[[A]] : memref<8xf64>)
|
|
// CHECK-DAG: linalg.fill ins(%{{.*}} : i1) outs(%[[B]] : memref<8xi1>)
|
|
// CHECK: return %[[D]] : memref<?xindex>
|
|
func.func @sparse_expansion1() -> memref<?xindex> {
|
|
%0 = bufferization.alloc_tensor() : tensor<4x8xf64, #CSR>
|
|
%values, %filled, %added, %count = sparse_tensor.expand %0
|
|
: tensor<4x8xf64, #CSR> to memref<?xf64>, memref<?xi1>, memref<?xindex>
|
|
return %added : memref<?xindex>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func @sparse_expansion2()
|
|
// CHECK: %[[A:.*]] = memref.alloc() : memref<4xf64>
|
|
// CHECK: %[[B:.*]] = memref.alloc() : memref<4xi1>
|
|
// CHECK: %[[C:.*]] = memref.alloc() : memref<4xindex>
|
|
// CHECK: %[[D:.*]] = memref.cast %[[C]] : memref<4xindex> to memref<?xindex>
|
|
// CHECK-DAG: linalg.fill ins(%{{.*}} : f64) outs(%[[A]] : memref<4xf64>)
|
|
// CHECK-DAG: linalg.fill ins(%{{.*}} : i1) outs(%[[B]] : memref<4xi1>)
|
|
// CHECK: return %[[D]] : memref<?xindex>
|
|
func.func @sparse_expansion2() -> memref<?xindex> {
|
|
%0 = bufferization.alloc_tensor() : tensor<4x8xf64, #CSC>
|
|
%values, %filled, %added, %count = sparse_tensor.expand %0
|
|
: tensor<4x8xf64, #CSC> to memref<?xf64>, memref<?xi1>, memref<?xindex>
|
|
return %added : memref<?xindex>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func @sparse_expansion3(
|
|
// CHECK-SAME: %[[D0:.*]]: index,
|
|
// CHECK-SAME: %{{.*}}: index) -> memref<?xindex> {
|
|
// CHECK: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK: %[[S0:.*]] = memref.alloc() : memref<2xindex>
|
|
// CHECK: memref.store %[[D0]], %[[S0]]{{\[}}%[[C1]]] : memref<2xindex>
|
|
// CHECK: %[[D1:.*]] = memref.load %[[S0]]{{\[}}%[[C1]]] : memref<2xindex>
|
|
// CHECK: %[[V:.*]] = memref.alloc(%[[D1]]) : memref<?xf64>
|
|
// CHECK: %[[B:.*]] = memref.alloc(%[[D1]]) : memref<?xi1>
|
|
// CHECK: %[[D:.*]] = memref.alloc(%[[D1]]) : memref<?xindex>
|
|
// CHECK: linalg.fill ins(%{{.*}} : f64) outs(%[[V]] : memref<?xf64>)
|
|
// CHECK: linalg.fill ins(%{{.*}} : i1) outs(%[[B]] : memref<?xi1>)
|
|
// CHECK: return %[[D]] : memref<?xindex>
|
|
func.func @sparse_expansion3(%arg0: index, %arg1: index) -> memref<?xindex> {
|
|
%0 = bufferization.alloc_tensor(%arg0, %arg1) : tensor<?x?xf64, #CSC>
|
|
%values, %filled, %added, %count = sparse_tensor.expand %0
|
|
: tensor<?x?xf64, #CSC> to memref<?xf64>, memref<?xi1>, memref<?xindex>
|
|
return %added : memref<?xindex>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func private @_insert_C_100_f64_0_0(
|
|
// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
|
|
// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
|
|
// CHECK-SAME: %[[A2:.*2]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A3:.*3]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A5:.*5]]: index,
|
|
// CHECK-SAME: %[[A6:.*6]]: f64)
|
|
// CHECK: %[[PV:.*]] = sparse_tensor.push_back %[[A1]], %[[A4]], %[[A6]] {idx = 2 : index} : memref<3xindex>, memref<?xf64>, f64
|
|
// CHECK: return %[[A0]], %[[A1]], %[[A2]], %{{.*}}, %[[PV]]
|
|
//
|
|
// CHECK-LABEL: func @sparse_compression_1d(
|
|
// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
|
|
// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
|
|
// CHECK-SAME: %[[A2:.*2]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A3:.*3]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A5:.*5]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A6:.*6]]: memref<?xi1>,
|
|
// CHECK-SAME: %[[A7:.*7]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A8:.*8]]: index)
|
|
// CHECK-DAG: %[[B0:.*]] = arith.constant false
|
|
// CHECK-DAG: %[[F0:.*]] = arith.constant 0.000000e+00 : f64
|
|
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK: sparse_tensor.sort %[[A8]], %[[A7]] : memref<?xindex>
|
|
// CHECK: %[[R:.*]]:5 = scf.for %[[I:.*]] = %[[C0]] to %[[A8]] step %[[C1]]
|
|
// CHECK-SAME: iter_args(%[[P0:.*]] = %[[A0]], %[[P1:.*]] = %[[A1]], %[[P2:.*]] = %[[A2]], %[[P3:.*]] = %[[A3]], %[[P4:.*]] = %[[A4]]) -> (memref<1xindex>, memref<3xindex>, memref<?xindex>, memref<?xindex>, memref<?xf64>) {
|
|
// CHECK: %[[INDEX:.*]] = memref.load %[[A7]][%[[I]]] : memref<?xindex>
|
|
// CHECK: %[[VAL:.*]] = memref.load %[[A5]][%[[INDEX]]] : memref<?xf64>
|
|
// CHECK: %[[C:.*]]:5 = func.call @_insert_C_100_f64_0_0(%[[P0]], %[[P1]], %[[P2]], %[[P3]], %[[P4]], %[[INDEX]], %[[VAL]])
|
|
// CHECK: memref.store %[[F0]], %[[A5]][%[[INDEX]]] : memref<?xf64>
|
|
// CHECK: memref.store %[[B0]], %[[A6]][%[[INDEX]]] : memref<?xi1>
|
|
// CHECK: scf.yield %[[C]]#0, %[[C]]#1, %[[C]]#2, %[[C]]#3, %[[C]]#4 : memref<1xindex>, memref<3xindex>, memref<?xindex>, memref<?xindex>, memref<?xf64>
|
|
// CHECK: }
|
|
// CHECK: memref.dealloc %[[A5]] : memref<?xf64>
|
|
// CHECK: memref.dealloc %[[A6]] : memref<?xi1>
|
|
// CHECK: memref.dealloc %[[A7]] : memref<?xindex>
|
|
// CHECK: return %[[R]]#0, %[[R]]#1, %[[R]]#2, %[[R]]#3, %[[R]]#4
|
|
// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xindex>, memref<?xindex>, memref<?xf64>
|
|
func.func @sparse_compression_1d(%tensor: tensor<100xf64, #SV>,
|
|
%values: memref<?xf64>,
|
|
%filled: memref<?xi1>,
|
|
%added: memref<?xindex>,
|
|
%count: index) -> tensor<100xf64, #SV> {
|
|
%0 = sparse_tensor.compress %values, %filled, %added, %count into %tensor[]
|
|
: memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<100xf64, #SV>
|
|
%1 = sparse_tensor.load %0 hasInserts : tensor<100xf64, #SV>
|
|
return %1 : tensor<100xf64, #SV>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func private @_insert_D_C_8_8_f64_64_32(
|
|
// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
|
|
// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
|
|
// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
|
|
// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
|
|
// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A5:.*5]]: index,
|
|
// CHECK-SAME: %[[A6:.*6]]: index,
|
|
// CHECK-SAME: %[[A7:.*7]]: f64)
|
|
// CHECK: %[[PV:.*]] = sparse_tensor.push_back %[[A1]], %[[A4]], %[[A7]] {idx = 2 : index} : memref<3xindex>, memref<?xf64>, f64
|
|
// CHECK: return %[[A0]], %[[A1]], %[[A2]], %{{.*}}, %[[PV]]
|
|
//
|
|
// CHECK-LABEL: func @sparse_compression(
|
|
// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
|
|
// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
|
|
// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
|
|
// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
|
|
// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A5:.*5]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A6:.*6]]: memref<?xi1>,
|
|
// CHECK-SAME: %[[A7:.*7]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A8:.*8]]: index,
|
|
// CHECK-SAME: %[[A9:.*9]]: index)
|
|
// CHECK-DAG: %[[B0:.*]] = arith.constant false
|
|
// CHECK-DAG: %[[F0:.*]] = arith.constant 0.000000e+00 : f64
|
|
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK: sparse_tensor.sort %[[A8]], %[[A7]] : memref<?xindex>
|
|
// CHECK: %[[R:.*]]:5 = scf.for %[[I:.*]] = %[[C0]] to %[[A8]] step %[[C1]]
|
|
// CHECK-SAME: iter_args(%[[P0:.*]] = %[[A0]], %[[P1:.*]] = %[[A1]], %[[P2:.*]] = %[[A2]], %[[P3:.*]] = %[[A3]], %[[P4:.*]] = %[[A4]]) -> (memref<2xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf64>) {
|
|
// CHECK: %[[INDEX:.*]] = memref.load %[[A7]][%[[I]]] : memref<?xindex>
|
|
// CHECK: %[[VAL:.*]] = memref.load %[[A5]][%[[INDEX]]] : memref<?xf64>
|
|
// CHECK: %[[C:.*]]:5 = func.call @_insert_D_C_8_8_f64_64_32(%[[P0]], %[[P1]], %[[P2]], %[[P3]], %[[P4]], %[[A9]], %[[INDEX]], %[[VAL]])
|
|
// CHECK: memref.store %[[F0]], %[[A5]][%[[INDEX]]] : memref<?xf64>
|
|
// CHECK: memref.store %[[B0]], %[[A6]][%[[INDEX]]] : memref<?xi1>
|
|
// CHECK: scf.yield %[[C]]#0, %[[C]]#1, %[[C]]#2, %[[C]]#3, %[[C]]#4 : memref<2xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf64>
|
|
// CHECK: }
|
|
// CHECK: memref.dealloc %[[A5]] : memref<?xf64>
|
|
// CHECK: memref.dealloc %[[A6]] : memref<?xi1>
|
|
// CHECK: memref.dealloc %[[A7]] : memref<?xindex>
|
|
// CHECK: return %[[R]]#0, %[[R]]#1, %[[R]]#2, %[[R]]#3, %[[R]]#4
|
|
// CHECK-SAME: memref<2xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf64>
|
|
func.func @sparse_compression(%tensor: tensor<8x8xf64, #CSR>,
|
|
%values: memref<?xf64>,
|
|
%filled: memref<?xi1>,
|
|
%added: memref<?xindex>,
|
|
%count: index,
|
|
%i: index) -> tensor<8x8xf64, #CSR> {
|
|
%0 = sparse_tensor.compress %values, %filled, %added, %count into %tensor[%i]
|
|
: memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<8x8xf64, #CSR>
|
|
%1 = sparse_tensor.load %0 hasInserts : tensor<8x8xf64, #CSR>
|
|
return %1 : tensor<8x8xf64, #CSR>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func private @_insert_D_C_8_8_f64_0_0(
|
|
// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
|
|
// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
|
|
// CHECK-SAME: %[[A2:.*2]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A3:.*3]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A5:.*5]]: index,
|
|
// CHECK-SAME: %[[A6:.*6]]: index,
|
|
// CHECK-SAME: %[[A7:.*7]]: f64)
|
|
// CHECK: %[[PV:.*]] = sparse_tensor.push_back %[[A1]], %[[A4]], %[[A7]] {idx = 2 : index} : memref<3xindex>, memref<?xf64>, f64
|
|
// CHECK: return %[[A0]], %[[A1]], %[[A2]], %{{.*}}, %[[PV]]
|
|
//
|
|
// CHECK-LABEL: func @sparse_compression_unordered(
|
|
// CHECK-SAME: %[[A0:.*0]]: memref<2xindex>,
|
|
// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
|
|
// CHECK-SAME: %[[A2:.*2]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A3:.*3]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A5:.*5]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A6:.*6]]: memref<?xi1>,
|
|
// CHECK-SAME: %[[A7:.*7]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A8:.*8]]: index,
|
|
// CHECK-SAME: %[[A9:.*9]]: index)
|
|
// CHECK-DAG: %[[B0:.*]] = arith.constant false
|
|
// CHECK-DAG: %[[F0:.*]] = arith.constant 0.000000e+00 : f64
|
|
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK-NOT: sparse_tensor.sort
|
|
// CHECK: %[[R:.*]]:5 = scf.for %[[I:.*]] = %[[C0]] to %[[A8]] step %[[C1]]
|
|
// CHECK-SAME: iter_args(%[[P0:.*]] = %[[A0]], %[[P1:.*]] = %[[A1]], %[[P2:.*]] = %[[A2]], %[[P3:.*]] = %[[A3]], %[[P4:.*]] = %[[A4]]) -> (memref<2xindex>, memref<3xindex>, memref<?xindex>, memref<?xindex>, memref<?xf64>) {
|
|
// CHECK: %[[INDEX:.*]] = memref.load %[[A7]][%[[I]]] : memref<?xindex>
|
|
// CHECK: %[[VAL:.*]] = memref.load %[[A5]][%[[INDEX]]] : memref<?xf64>
|
|
// CHECK: %[[C:.*]]:5 = func.call @_insert_D_C_8_8_f64_0_0(%[[P0]], %[[P1]], %[[P2]], %[[P3]], %[[P4]], %[[A9]], %[[INDEX]], %[[VAL]])
|
|
// CHECK: memref.store %[[F0]], %[[A5]][%[[INDEX]]] : memref<?xf64>
|
|
// CHECK: memref.store %[[B0]], %[[A6]][%[[INDEX]]] : memref<?xi1>
|
|
// CHECK: scf.yield %[[C]]#0, %[[C]]#1, %[[C]]#2, %[[C]]#3, %[[C]]#4 : memref<2xindex>, memref<3xindex>, memref<?xindex>, memref<?xindex>, memref<?xf64>
|
|
// CHECK: }
|
|
// CHECK: memref.dealloc %[[A5]] : memref<?xf64>
|
|
// CHECK: memref.dealloc %[[A6]] : memref<?xi1>
|
|
// CHECK: memref.dealloc %[[A7]] : memref<?xindex>
|
|
// CHECK: return %[[R]]#0, %[[R]]#1, %[[R]]#2, %[[R]]#3, %[[R]]#4
|
|
// CHECK-SAME: memref<2xindex>, memref<3xindex>, memref<?xindex>, memref<?xindex>, memref<?xf64>
|
|
func.func @sparse_compression_unordered(%tensor: tensor<8x8xf64, #UCSR>,
|
|
%values: memref<?xf64>,
|
|
%filled: memref<?xi1>,
|
|
%added: memref<?xindex>,
|
|
%count: index,
|
|
%i: index) -> tensor<8x8xf64, #UCSR> {
|
|
%0 = sparse_tensor.compress %values, %filled, %added, %count into %tensor[%i]
|
|
: memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<8x8xf64, #UCSR>
|
|
%1 = sparse_tensor.load %0 hasInserts : tensor<8x8xf64, #UCSR>
|
|
return %1 : tensor<8x8xf64, #UCSR>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func private @_insert_C_128_f64_0_0(
|
|
// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
|
|
// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
|
|
// CHECK-SAME: %[[A2:.*2]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A3:.*3]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A5:.*5]]: index,
|
|
// CHECK-SAME: %[[A6:.*6]]: f64)
|
|
// CHECK: %[[P:.*]] = sparse_tensor.push_back %[[A1]], %[[A4]], %[[A6]] {idx = 2 : index} : memref<3xindex>, memref<?xf64>, f64
|
|
// CHECK: return %[[A0]], %[[A1]], %[[A2]], %{{.*}}, %[[P]] :
|
|
// CHECK: func @sparse_insert(
|
|
// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
|
|
// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
|
|
// CHECK-SAME: %[[A2:.*2]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A3:.*3]]: memref<?xindex>,
|
|
// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A5:.*5]]: index,
|
|
// CHECK-SAME: %[[A6:.*6]]: f64)
|
|
// CHECK: %[[R:.*]]:5 = call @_insert_C_128_f64_0_0(%[[A0]], %[[A1]], %[[A2]], %[[A3]], %[[A4]], %[[A5]], %[[A6]])
|
|
// CHECK: return %[[R]]#0, %[[R]]#1, %[[R]]#2, %[[R]]#3, %[[R]]#4
|
|
// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xindex>, memref<?xindex>, memref<?xf64>
|
|
func.func @sparse_insert(%arg0: tensor<128xf64, #SV>, %arg1: index, %arg2: f64) -> tensor<128xf64, #SV> {
|
|
%0 = sparse_tensor.insert %arg2 into %arg0[%arg1] : tensor<128xf64, #SV>
|
|
%1 = sparse_tensor.load %0 hasInserts : tensor<128xf64, #SV>
|
|
return %1 : tensor<128xf64, #SV>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func private @_insert_C_128_f64_64_32(
|
|
// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
|
|
// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
|
|
// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
|
|
// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
|
|
// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
|
|
// CHECK-SAME: %[[A5:.*5]]: index,
|
|
// CHECK-SAME: %[[A6:.*6]]: f64)
|
|
// CHECK: %[[P:.*]] = sparse_tensor.push_back %[[A1]], %[[A4]], %[[A6]] {idx = 2 : index} : memref<3xindex>, memref<?xf64>, f64
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// CHECK: return %[[A0]], %[[A1]], %[[A2]], %{{.*}}, %[[P]] :
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// CHECK: func @sparse_insert_typed(
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// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf64>,
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// CHECK-SAME: %[[A5:.*5]]: index,
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// CHECK-SAME: %[[A6:.*6]]: f64)
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// CHECK: %[[R:.*]]:5 = call @_insert_C_128_f64_64_32(%[[A0]], %[[A1]], %[[A2]], %[[A3]], %[[A4]], %[[A5]], %[[A6]])
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// CHECK: return %[[R]]#0, %[[R]]#1, %[[R]]#2, %[[R]]#3, %[[R]]#4
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// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf64>
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func.func @sparse_insert_typed(%arg0: tensor<128xf64, #SparseVector>, %arg1: index, %arg2: f64) -> tensor<128xf64, #SparseVector> {
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%0 = sparse_tensor.insert %arg2 into %arg0[%arg1] : tensor<128xf64, #SparseVector>
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%1 = sparse_tensor.load %0 hasInserts : tensor<128xf64, #SparseVector>
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return %1 : tensor<128xf64, #SparseVector>
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}
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|
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// CHECK-LABEL: func.func @sparse_nop_convert(
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// CHECK-SAME: %[[A0:.*0]]: memref<1xindex>,
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// CHECK-SAME: %[[A1:.*1]]: memref<3xindex>,
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// CHECK-SAME: %[[A2:.*2]]: memref<?xi32>,
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// CHECK-SAME: %[[A3:.*3]]: memref<?xi64>,
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// CHECK-SAME: %[[A4:.*4]]: memref<?xf32>)
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// CHECK: return %[[A0]], %[[A1]], %[[A2]], %[[A3]], %[[A4]] :
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// CHECK-SAME: memref<1xindex>, memref<3xindex>, memref<?xi32>, memref<?xi64>, memref<?xf32>
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func.func @sparse_nop_convert(%arg0: tensor<32xf32, #SparseVector>) -> tensor<?xf32, #SparseVector> {
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%0 = sparse_tensor.convert %arg0 : tensor<32xf32, #SparseVector> to tensor<?xf32, #SparseVector>
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return %0 : tensor<?xf32, #SparseVector>
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} |