92 lines
3.5 KiB
MLIR
92 lines
3.5 KiB
MLIR
// RUN: mlir-opt %s --stage-sparse-ops --lower-sparse-ops-to-foreach --canonicalize --cse | FileCheck %s
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#SparseVector = #sparse_tensor.encoding<{
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map = (d0) -> (d0 : compressed)
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}>
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#CSR = #sparse_tensor.encoding<{
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map = (d0, d1) -> (d0 : dense, d1 : compressed)
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}>
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#CSC = #sparse_tensor.encoding<{
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map = (d0, d1) -> (d1 : dense, d0 : compressed)
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}>
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#SparseTensor = #sparse_tensor.encoding<{
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map = (d0, d1, d2) -> (d2 : dense, d0 : compressed, d1 : compressed)
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}>
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// CHECK-LABEL: func.func @sparse_convert_1d
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// CHECK: sparse_tensor.foreach
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// CHECK: scf.if
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// CHECK: tensor.insert
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// CHECK-NOT: sparse_tensor.reorder_coo
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// CHECK: sparse_tensor.load
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func.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.func @sparse_convert_complex
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// CHECK: sparse_tensor.foreach
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// CHECK: scf.if
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// CHECK: tensor.insert
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// CHECK-NOT: sparse_tensor.reorder_coo
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// CHECK: sparse_tensor.load
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func.func @sparse_convert_complex(%arg0: tensor<100xcomplex<f64>>) -> tensor<100xcomplex<f64>, #SparseVector> {
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%0 = sparse_tensor.convert %arg0 : tensor<100xcomplex<f64>> to tensor<100xcomplex<f64>, #SparseVector>
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return %0 : tensor<100xcomplex<f64>, #SparseVector>
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}
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// CHECK-LABEL: func.func @sparse_convert_2d
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// CHECK: sparse_tensor.foreach
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// CHECK: scf.if
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// CHECK: tensor.insert
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// CHECK-NOT: sparse_tensor.reorder_coo
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// CHECK: sparse_tensor.load
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func.func @sparse_convert_2d(%arg0: tensor<2x4xf64>) -> tensor<2x4xf64, #CSR> {
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%0 = sparse_tensor.convert %arg0 : tensor<2x4xf64> to tensor<2x4xf64, #CSR>
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return %0 : tensor<2x4xf64, #CSR>
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}
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// CHECK-LABEL: func.func @sparse_constant
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// CHECK: sparse_tensor.foreach
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// CHECK-NOT: scf.if
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// CHECK: tensor.insert
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// CHECK-NOT: sparse_tensor.reorder_coo
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// CHECK: sparse_tensor.load
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func.func @sparse_constant() -> tensor<8x7xf32, #CSR>{
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// Initialize a tensor.
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%0 = arith.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.func @sparse_constant_csc
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// CHECK: sparse_tensor.foreach
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// CHECK-NOT: scf.if
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// CHECK: tensor.insert
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// CHECK-NOT: sparse_tensor.reorder_coo
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// CHECK: sparse_tensor.load
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func.func @sparse_constant_csc() -> tensor<8x7xf32, #CSC>{
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// Initialize a tensor.
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%0 = arith.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, #CSC>
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return %1 : tensor<8x7xf32, #CSC>
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}
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// CHECK-LABEL: func.func @sparse_convert_3d
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// CHECK: sparse_tensor.foreach
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// CHECK: scf.if
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// CHECK: tensor.insert
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// CHECK: sparse_tensor.load
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// CHECK: sparse_tensor.reorder_coo
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// CHECK: sparse_tensor.foreach
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// CHECK: tensor.insert
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// CHECK: sparse_tensor.load
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func.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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