xref: /llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_codegen_dim.mlir (revision eb206e9ea84eff0a0596fed2de8316d924f946d1)
1//--------------------------------------------------------------------------------------------------
2// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.
3//
4// Set-up that's shared across all tests in this directory. In principle, this
5// config could be moved to lit.local.cfg. However, there are downstream users that
6//  do not use these LIT config files. Hence why this is kept inline.
7//
8// DEFINE: %{sparsifier_opts} = enable-runtime-library=true
9// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}
10// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
11// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
12// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
13// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils
14// DEFINE: %{run_opts} = -e main -entry-point-result=void
15// DEFINE: %{run} = mlir-runner %{run_opts} %{run_libs}
16// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs_sve}
17//
18// DEFINE: %{env} =
19//--------------------------------------------------------------------------------------------------
20
21// RUN: %{compile} | %{run} | FileCheck %s
22//
23// Do the same run, but now with direct IR generation.
24// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false
25// RUN: %{compile} | %{run} | FileCheck %s
26//
27// Do the same run, but now with direct IR generation and vectorization.
28// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true
29// RUN: %{compile} | %{run} | FileCheck %s
30//
31// Do the same run, but now with direct IR generation and VLA vectorization.
32// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %}
33
34#DCSR  = #sparse_tensor.encoding<{
35  map = (d0, d1) -> (d0 : compressed, d1 : compressed)
36}>
37
38module {
39  //
40  // Main driver.
41  //
42  func.func @main() {
43    %c0 = arith.constant 0 : index
44    %c1 = arith.constant 1 : index
45    %c2 = arith.constant 2 : index
46    %c3 = arith.constant 3 : index
47    %t1 = tensor.empty() : tensor<4x5xf64, #DCSR>
48    %t2 = tensor.empty(%c2, %c3) : tensor<?x?xf64, #DCSR>
49
50    %d1_0 = tensor.dim %t1, %c0 : tensor<4x5xf64, #DCSR>
51    %d2_0 = tensor.dim %t2, %c0 : tensor<?x?xf64, #DCSR>
52    %d1_1 = tensor.dim %t1, %c1 : tensor<4x5xf64, #DCSR>
53    %d2_1 = tensor.dim %t2, %c1 : tensor<?x?xf64, #DCSR>
54
55    // CHECK: 4
56    vector.print %d1_0 : index
57    // CHECK-NEXT: 2
58    vector.print %d2_0 : index
59    // CHECK-NEXT: 5
60    vector.print %d1_1 : index
61    // CHECK-NEXT: 3
62    vector.print %d2_1 : index
63
64    // Release resources.
65    bufferization.dealloc_tensor %t1 : tensor<4x5xf64, #DCSR>
66    bufferization.dealloc_tensor %t2 : tensor<?x?xf64, #DCSR>
67
68    return
69  }
70}
71
72