f56a7383f0
For some reason, even though D150822 passed the buildbot, it failed to catch this test Reviewed By: anlunx Differential Revision: https://reviews.llvm.org/D150830
88 lines
3.7 KiB
MLIR
88 lines
3.7 KiB
MLIR
// DEFINE: %{option} = enable-runtime-library=true
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// DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
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// DEFINE: %{run} = mlir-cpu-runner \
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// DEFINE: -e entry -entry-point-result=void \
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// DEFINE: -shared-libs=%mlir_c_runner_utils | \
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// DEFINE: FileCheck %s
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//
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// RUN: %{compile} | %{run}
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//
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// Do the same run, but now with direct IR generation.
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// REDEFINE: %{option} = enable-runtime-library=false
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// RUN: %{compile} | %{run}
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//
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// Do the same run, but now with direct IR generation and vectorization.
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// REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
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// RUN: %{compile} | %{run}
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#SparseVector = #sparse_tensor.encoding<{
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lvlTypes = ["compressed"]
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}>
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#SparseMatrix = #sparse_tensor.encoding<{
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lvlTypes = ["compressed", "compressed"]
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}>
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#Sparse3dTensor = #sparse_tensor.encoding<{
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lvlTypes = ["compressed", "compressed", "compressed"]
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}>
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module {
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func.func @reshape0(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<2x6xf64, #SparseMatrix> {
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%shape = arith.constant dense <[ 2, 6 ]> : tensor<2xi32>
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%0 = tensor.reshape %arg0(%shape) : (tensor<3x4xf64, #SparseMatrix>, tensor<2xi32>) -> tensor<2x6xf64, #SparseMatrix>
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return %0 : tensor<2x6xf64, #SparseMatrix>
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}
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func.func @reshape1(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64, #SparseVector> {
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%shape = arith.constant dense <[ 12 ]> : tensor<1xi32>
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%0 = tensor.reshape %arg0(%shape) : (tensor<3x4xf64, #SparseMatrix>, tensor<1xi32>) -> tensor<12xf64, #SparseVector>
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return %0 : tensor<12xf64, #SparseVector>
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}
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func.func @reshape2(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<2x3x2xf64, #Sparse3dTensor> {
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%shape = arith.constant dense <[ 2, 3, 2 ]> : tensor<3xi32>
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%0 = tensor.reshape %arg0(%shape) : (tensor<3x4xf64, #SparseMatrix>, tensor<3xi32>) -> tensor<2x3x2xf64, #Sparse3dTensor>
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return %0 : tensor<2x3x2xf64, #Sparse3dTensor>
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}
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func.func @entry() {
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%m = arith.constant dense <[ [ 1.1, 0.0, 1.3, 0.0 ],
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[ 2.1, 0.0, 2.3, 0.0 ],
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[ 3.1, 0.0, 3.3, 0.0 ]]> : tensor<3x4xf64>
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%sm = sparse_tensor.convert %m : tensor<3x4xf64> to tensor<3x4xf64, #SparseMatrix>
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%reshaped0 = call @reshape0(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<2x6xf64, #SparseMatrix>
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%reshaped1 = call @reshape1(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64, #SparseVector>
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%reshaped2 = call @reshape2(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<2x3x2xf64, #Sparse3dTensor>
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%c0 = arith.constant 0 : index
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%df = arith.constant -1.0 : f64
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// CHECK: ( 1.1, 1.3, 2.1, 2.3, 3.1, 3.3
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%b0 = sparse_tensor.values %reshaped0: tensor<2x6xf64, #SparseMatrix> to memref<?xf64>
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%v0 = vector.transfer_read %b0[%c0], %df: memref<?xf64>, vector<12xf64>
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vector.print %v0 : vector<12xf64>
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// CHECK: ( 1.1, 1.3, 2.1, 2.3, 3.1, 3.3
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%b1 = sparse_tensor.values %reshaped1: tensor<12xf64, #SparseVector> to memref<?xf64>
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%v1 = vector.transfer_read %b1[%c0], %df: memref<?xf64>, vector<12xf64>
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vector.print %v1 : vector<12xf64>
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// CHECK: ( 1.1, 1.3, 2.1, 2.3, 3.1, 3.3
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%b2 = sparse_tensor.values %reshaped2: tensor<2x3x2xf64, #Sparse3dTensor> to memref<?xf64>
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%v2 = vector.transfer_read %b2[%c0], %df: memref<?xf64>, vector<12xf64>
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vector.print %v2: vector<12xf64>
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bufferization.dealloc_tensor %sm : tensor<3x4xf64, #SparseMatrix>
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bufferization.dealloc_tensor %reshaped0 : tensor<2x6xf64, #SparseMatrix>
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bufferization.dealloc_tensor %reshaped1 : tensor<12xf64, #SparseVector>
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bufferization.dealloc_tensor %reshaped2 : tensor<2x3x2xf64, #Sparse3dTensor>
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return
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}
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}
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