//--------------------------------------------------------------------------------------------------
// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.
//
// Set-up that's shared across all tests in this directory. In principle, this
// config could be moved to lit.local.cfg. However, there are downstream users that
// do not use these LIT config files. Hence why this is kept inline.
//
// DEFINE: %{sparsifier_opts} = enable-runtime-library=true
// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}
// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils
// DEFINE: %{run_opts} = -e main -entry-point-result=void
// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs_sve}
//
// DEFINE: %{env} =
//--------------------------------------------------------------------------------------------------
// REDEFINE: %{env} = TENSOR0="%mlir_src_dir/test/Integration/data/block.mtx"
// RUN: %{compile} | env %{env} %{run} | FileCheck %s
//
// Do the same run, but now with direct IR generation.
// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false
// RUN: %{compile} | env %{env} %{run} | FileCheck %s
//
// Do the same run, but now with direct IR generation and vectorization.
// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true vl=2 reassociate-fp-reductions=true enable-index-optimizations=true
// RUN: %{compile} | env %{env} %{run} | FileCheck %s
!Filename = !llvm.ptr
#BSR = #sparse_tensor.encoding<{
map = (i, j) ->
( i floordiv 2 : dense
, j floordiv 2 : compressed
, i mod 2 : dense
, j mod 2 : dense
)
}>
#DSDD = #sparse_tensor.encoding<{
map = (i, j, k, l) -> ( i : dense, j : compressed, k : dense, l : dense)
}>
#trait_scale_inplace = {
indexing_maps = [
affine_map<(i,j) -> (i,j)> // X (out)
],
iterator_types = ["parallel", "parallel"]
}
//
// Example 2x2 block storage:
//
// +-----+-----+-----+ +-----+-----+-----+
// | 1 2 | . . | 4 . | | 1 2 | | 4 0 |
// | . 3 | . . | . 5 | | 0 3 | | 0 5 |
// +-----+-----+-----+ => +-----+-----+-----+
// | . . | 6 7 | . . | | | 6 7 | |
// | . . | 8 . | . . | | | 8 0 | |
// +-----+-----+-----+ +-----+-----+-----+
//
// Stored as:
//
// positions[1] : 0 2 3
// coordinates[1] : 0 2 1
// values : 1.000000 2.000000 0.000000 3.000000 4.000000 0.000000 0.000000 5.000000 6.000000 7.000000 8.000000 0.000000
//
module {
func.func private @getTensorFilename(index) -> (!Filename)
func.func @scale(%arg0: tensor<?x?xf64, #BSR>) -> tensor<?x?xf64, #BSR> {
%c = arith.constant 3.0 : f64
%0 = linalg.generic #trait_scale_inplace
outs(%arg0: tensor<?x?xf64, #BSR>) {
^bb(%x: f64):
%1 = arith.mulf %x, %c : f64
linalg.yield %1 : f64
} -> tensor<?x?xf64, #BSR>
return %0 : tensor<?x?xf64, #BSR>
}
func.func @main() {
%c0 = arith.constant 0 : index
%f0 = arith.constant 0.0 : f64
%fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
%A = sparse_tensor.new %fileName : !Filename to tensor<?x?xf64, #BSR>
// CHECK: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 12
// CHECK-NEXT: dim = ( 4, 6 )
// CHECK-NEXT: lvl = ( 2, 3, 2, 2 )
// CHECK-NEXT: pos[1] : ( 0, 2, 3 )
// CHECK-NEXT: crd[1] : ( 0, 2, 1 )
// CHECK-NEXT: values : ( 1, 2, 0, 3, 4, 0, 0, 5, 6, 7, 8, 0 )
// CHECK-NEXT: ----
sparse_tensor.print %A : tensor<?x?xf64, #BSR>
// CHECK-NEXT: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 12
// CHECK-NEXT: dim = ( 2, 3, 2, 2 )
// CHECK-NEXT: lvl = ( 2, 3, 2, 2 )
// CHECK-NEXT: pos[1] : ( 0, 2, 3 )
// CHECK-NEXT: crd[1] : ( 0, 2, 1 )
// CHECK-NEXT: values : ( 1, 2, 0, 3, 4, 0, 0, 5, 6, 7, 8, 0 )
// CHECK-NEXT: ----
%t1 = sparse_tensor.reinterpret_map %A : tensor<?x?xf64, #BSR>
to tensor<?x?x2x2xf64, #DSDD>
sparse_tensor.print %t1 : tensor<?x?x2x2xf64, #DSDD>
// CHECK-NEXT: ---- Sparse Tensor ----
// CHECK-NEXT: nse = 12
// CHECK-NEXT: dim = ( 4, 6 )
// CHECK-NEXT: lvl = ( 2, 3, 2, 2 )
// CHECK-NEXT: pos[1] : ( 0, 2, 3 )
// CHECK-NEXT: crd[1] : ( 0, 2, 1 )
// CHECK-NEXT: values : ( 3, 6, 0, 9, 12, 0, 0, 15, 18, 21, 24, 0 )
// CHECK-NEXT: ----
%As = call @scale(%A) : (tensor<?x?xf64, #BSR>) -> (tensor<?x?xf64, #BSR>)
sparse_tensor.print %As : tensor<?x?xf64, #BSR>
// Release the resources.
bufferization.dealloc_tensor %A: tensor<?x?xf64, #BSR>
return
}
}
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