Andrzej Warzynski 23e5130ebf [mlir][test] Reland: Refactor SparseTensor CPU integration tests
CHANGES SINCE THE ORIGINAL VERSION
----------------------------------
The default test set-up was extracted from
  * SparseTensor/CPU/lit.local.cfg.
and duplicated in all tests. This is to support downstream users that
don't use these local LIT config files.

SUMMARY OF CHANGES
------------------
This patch aims to reduce test duplication. This is a direct follow-up of:
  1. https://reviews.llvm.org/D155403 (test duplication), and
  2. https://reviews.llvm.org/D155405 (code re-use),

All SVE/VLA tests are now enabled _conditionally_ and refactored to use
`mlir-cpu-runner` rather than `lli`. The former helps with test
duplication and the latter with code re-use.

A few additional refactoring changes are included.

1. The reduce verbosity, long runtime library names like:

  %mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext

are replaced with:

  %mlir_c_runner_utils

2. In order to keep the code and the comments in sync, and to maintain
   consistency across the tests, the following:

  enable-runtime-library=true

is swapped with (and vice-versa):

  enable-runtime-library=false

Note that this change won't affect test coverage. Only few tests
required such update.

3. A VLS vectorization `RUN` line is added in tests where there was a
   VLA/VLS `RUN` line, but no VLS `RUN` line (with a few exceptions of
   tests that only contained one `RUN` line to begin with).

4. A few test variables are renamed/added. Most notable example:
  * %{options}` --> %{sparse_compiler_opts}

TEST RUNTIME IMPROVEMENT
------------------------
Tl;Dr This change improves test execution time by ~25%.

At the moment, the following `llvm-lit` invocation takes ~7.30s on my
AArch64 workstation (with SVE):

  llvm-lit  <llvm-project>/mlir/test/Integration/Dialect/SparseTensor/CPU/

This timing doesn't change no matter what the value of the following
CMake variable is (that should disable some tests):

  MLIR_RUN_ARM_SVE_TESTS

With this patch, the execution time will indeed depend on the value of
the above CMake variable:
  * with `MLIR_RUN_ARM_SVE_TESTS=true` the timing remains intact,
  * with `MLIR_RUN_ARM_SVE_TESTS=false` the timing drops to ~5.40s (~25%
    improvement).
This is expected:
  * on average there are 4 `RUN` lines per test,
  * _without this change_ (and with `MLIR_RUN_ARM_SVE_TESTS=false`) the
    4th `RUN` line would in most cases duplicate the 3rd `RUN` line,
  * _with this change) (and with `MLIR_RUN_ARM_SVE_TESTS=false`) the
    4th `RUN` line becomes empty.

PATCH SIZE
----------
While rather large and touching many files, most changes in this patch
are rather mechanical. All test configurations have been preserved and
only in a handful of cases new `RUN` lines added.

Differential Revision: https://reviews.llvm.org/D156625
2023-08-11 08:16:01 +00:00

103 lines
4.7 KiB
MLIR

//--------------------------------------------------------------------------------------------------
// 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: %{sparse_compiler_opts} = enable-runtime-library=true
// DEFINE: %{sparse_compiler_opts_sve} = enable-arm-sve=true %{sparse_compiler_opts}
// DEFINE: %{compile} = mlir-opt %s --sparse-compiler="%{sparse_compiler_opts}"
// DEFINE: %{compile_sve} = mlir-opt %s --sparse-compiler="%{sparse_compiler_opts_sve}"
// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
// DEFINE: %{run_opts} = -e entry -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}
//
// DEFINE: %{env} =
//--------------------------------------------------------------------------------------------------
// RUN: %{compile} | %{run} | FileCheck %s
//
// Do the same run, but now with direct IR generation.
// REDEFINE: %{sparse_compiler_opts} = enable-runtime-library=false
// RUN: %{compile} | %{run} | FileCheck %s
//
// Do the same run, but now with direct IR generation and vectorization.
// REDEFINE: %{sparse_compiler_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true
// RUN: %{compile} | %{run} | FileCheck %s
//
// Do the same run, but now with direct IR generation and VLA vectorization.
// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %}
#SparseVector = #sparse_tensor.encoding<{
lvlTypes = ["compressed"]
}>
#SparseMatrix = #sparse_tensor.encoding<{
lvlTypes = ["compressed", "compressed"]
}>
#Sparse3dTensor = #sparse_tensor.encoding<{
lvlTypes = ["compressed", "compressed", "compressed"]
}>
module {
func.func @reshape0(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<2x6xf64, #SparseMatrix> {
%shape = arith.constant dense <[ 2, 6 ]> : tensor<2xi32>
%0 = tensor.reshape %arg0(%shape) : (tensor<3x4xf64, #SparseMatrix>, tensor<2xi32>) -> tensor<2x6xf64, #SparseMatrix>
return %0 : tensor<2x6xf64, #SparseMatrix>
}
func.func @reshape1(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64, #SparseVector> {
%shape = arith.constant dense <[ 12 ]> : tensor<1xi32>
%0 = tensor.reshape %arg0(%shape) : (tensor<3x4xf64, #SparseMatrix>, tensor<1xi32>) -> tensor<12xf64, #SparseVector>
return %0 : tensor<12xf64, #SparseVector>
}
func.func @reshape2(%arg0: tensor<3x4xf64, #SparseMatrix>) -> tensor<2x3x2xf64, #Sparse3dTensor> {
%shape = arith.constant dense <[ 2, 3, 2 ]> : tensor<3xi32>
%0 = tensor.reshape %arg0(%shape) : (tensor<3x4xf64, #SparseMatrix>, tensor<3xi32>) -> tensor<2x3x2xf64, #Sparse3dTensor>
return %0 : tensor<2x3x2xf64, #Sparse3dTensor>
}
func.func @entry() {
%m = arith.constant dense <[ [ 1.1, 0.0, 1.3, 0.0 ],
[ 2.1, 0.0, 2.3, 0.0 ],
[ 3.1, 0.0, 3.3, 0.0 ]]> : tensor<3x4xf64>
%sm = sparse_tensor.convert %m : tensor<3x4xf64> to tensor<3x4xf64, #SparseMatrix>
%reshaped0 = call @reshape0(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<2x6xf64, #SparseMatrix>
%reshaped1 = call @reshape1(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<12xf64, #SparseVector>
%reshaped2 = call @reshape2(%sm) : (tensor<3x4xf64, #SparseMatrix>) -> tensor<2x3x2xf64, #Sparse3dTensor>
%c0 = arith.constant 0 : index
%df = arith.constant -1.0 : f64
// CHECK: ( 1.1, 1.3, 2.1, 2.3, 3.1, 3.3
%b0 = sparse_tensor.values %reshaped0: tensor<2x6xf64, #SparseMatrix> to memref<?xf64>
%v0 = vector.transfer_read %b0[%c0], %df: memref<?xf64>, vector<12xf64>
vector.print %v0 : vector<12xf64>
// CHECK: ( 1.1, 1.3, 2.1, 2.3, 3.1, 3.3
%b1 = sparse_tensor.values %reshaped1: tensor<12xf64, #SparseVector> to memref<?xf64>
%v1 = vector.transfer_read %b1[%c0], %df: memref<?xf64>, vector<12xf64>
vector.print %v1 : vector<12xf64>
// CHECK: ( 1.1, 1.3, 2.1, 2.3, 3.1, 3.3
%b2 = sparse_tensor.values %reshaped2: tensor<2x3x2xf64, #Sparse3dTensor> to memref<?xf64>
%v2 = vector.transfer_read %b2[%c0], %df: memref<?xf64>, vector<12xf64>
vector.print %v2: vector<12xf64>
bufferization.dealloc_tensor %sm : tensor<3x4xf64, #SparseMatrix>
bufferization.dealloc_tensor %reshaped0 : tensor<2x6xf64, #SparseMatrix>
bufferization.dealloc_tensor %reshaped1 : tensor<12xf64, #SparseVector>
bufferization.dealloc_tensor %reshaped2 : tensor<2x3x2xf64, #Sparse3dTensor>
return
}
}