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Differential D133190

[MLIR] Fix runner library paths for integration tests
AbandonedPublic

Authored by csigg on Sep 2 2022, 2:12 AM.

Details

Reviewers
mehdi_amini
aartbik
ftynse
nicolasvasilache
dcaballe
Summary

The shared library paths were set to %mlir_integration_test_dir, when they really should be %linalg_test_lib_dir (which I will rename in a separate change).

This happened to work for cmake builds, but is in the way for enabling these tests in bazel.

Diff Detail

Event Timeline

csigg created this revision.Sep 2 2022, 2:12 AM
Herald added a reviewer: aartbik. · View Herald TranscriptSep 2 2022, 2:12 AM
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csigg requested review of this revision.Sep 2 2022, 2:12 AM
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csigg edited the summary of this revision. (Show Details)Sep 2 2022, 2:16 AM
Harbormaster completed remote builds in B184782: Diff 457534.Sep 2 2022, 2:27 AM
aartbik requested changes to this revision.Sep 2 2022, 9:07 AM

Why can't we have a change that fixes what you need for mlir_integration_test_dir (the right name for this suite) rather than going through this linalg_test_lib_dir renaming first (which really is a misnomer)

This revision now requires changes to proceed.Sep 2 2022, 9:07 AM
csigg added a comment.Sep 2 2022, 9:17 AM
In D133190#3767164, @aartbik wrote:

Why can't we have a change that fixes what you need for mlir_integration_test_dir (the right name for this suite) rather than going through this linalg_test_lib_dir renaming first (which really is a misnomer)

%mlir_integration_test_dir is supposed to contain the build artifacts of that package, not all files that are needed by this test suite.

I agree that the %linalg_test_lib_dir is a misnomer. As I said in the description, I will fix that in a separate change.

aartbik added a comment.EditedSep 2 2022, 9:46 AM
In D133190#3767181, @csigg wrote:
In D133190#3767164, @aartbik wrote:

Why can't we have a change that fixes what you need for mlir_integration_test_dir (the right name for this suite) rather than going through this linalg_test_lib_dir renaming first (which really is a misnomer)

%mlir_integration_test_dir is supposed to contain the build artifacts of that package, not all files that are needed by this test suite.

I agree that the %linalg_test_lib_dir is a misnomer. As I said in the description, I will fix that in a separate change.

I don't disagree with your need for an improvement :-), apologies for not articulating my concerns more clearly.

Let me state it differently, you are touching 136 now with the guarantee that you will touch the same 136 files again in the near future.
It seems to me we could up with a solution where, with some prep work, you only touch these 136 files once....

Changes in the testing set up are slightly disruptive, as they potentially break new tests that are in flight.
Also, it adds a confusing history to each individual file.

That is why I was asking for a "one touch"s fix for these files.

csigg added a comment.Sep 2 2022, 10:05 AM

Point taken, let me fix the %linalg_test_lib_dir misnomer first.

aartbik added a comment.Sep 2 2022, 10:07 AM
In D133190#3767306, @csigg wrote:

Point taken, let me fix the %linalg_test_lib_dir misnomer first.

Thanks!

csigg abandoned this revision.Sep 4 2022, 2:11 AM

Subsumed by D133270.

Revision Contents

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Diff 457534

mlir/test/Integration/Dialect/Async/CPU/microbench-linalg-async-parallel-for.mlir

// RUN: mlir-opt %s \ // RUN: mlir-opt %s \
// RUN: -convert-linalg-to-parallel-loops \ // RUN: -convert-linalg-to-parallel-loops \
// RUN: -async-parallel-for \ // RUN: -async-parallel-for \
// RUN: -async-to-async-runtime \ // RUN: -async-to-async-runtime \
// RUN: -async-runtime-ref-counting \ // RUN: -async-runtime-ref-counting \
// RUN: -async-runtime-ref-counting-opt \ // RUN: -async-runtime-ref-counting-opt \
// RUN: -convert-async-to-llvm \ // RUN: -convert-async-to-llvm \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -arith-expand \ // RUN: -arith-expand \
// RUN: -memref-expand \ // RUN: -memref-expand \
// RUN: -convert-vector-to-llvm \ // RUN: -convert-vector-to-llvm \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O3 \ // RUN: -e entry -entry-point-result=void -O3 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext\
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext \
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
// RUN: mlir-opt %s \ // RUN: mlir-opt %s \
// RUN: -convert-linalg-to-loops \ // RUN: -convert-linalg-to-loops \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -convert-vector-to-llvm \ // RUN: -convert-vector-to-llvm \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O3 \ // RUN: -e entry -entry-point-result=void -O3 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext\
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext \
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
#map0 = affine_map<(d0, d1) -> (d0, d1)> #map0 = affine_map<(d0, d1) -> (d0, d1)>
func.func @linalg_generic(%lhs: memref<?x?xf32>, func.func @linalg_generic(%lhs: memref<?x?xf32>,
%rhs: memref<?x?xf32>, %rhs: memref<?x?xf32>,
%sum: memref<?x?xf32>) { %sum: memref<?x?xf32>) {
linalg.generic { linalg.generic {
▲ Show 20 Lines • Show All 93 Lines • Show Last 20 Lines

mlir/test/Integration/Dialect/Async/CPU/microbench-scf-async-parallel-for.mlir

// RUN: mlir-opt %s \ // RUN: mlir-opt %s \
// RUN: -async-parallel-for \ // RUN: -async-parallel-for \
// RUN: -async-to-async-runtime \ // RUN: -async-to-async-runtime \
// RUN: -async-runtime-ref-counting \ // RUN: -async-runtime-ref-counting \
// RUN: -async-runtime-ref-counting-opt \ // RUN: -async-runtime-ref-counting-opt \
// RUN: -convert-async-to-llvm \ // RUN: -convert-async-to-llvm \
// RUN: -convert-linalg-to-loops \ // RUN: -convert-linalg-to-loops \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -arith-expand \ // RUN: -arith-expand \
// RUN: -memref-expand \ // RUN: -memref-expand \
// RUN: -convert-vector-to-llvm \ // RUN: -convert-vector-to-llvm \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O3 \ // RUN: -e entry -entry-point-result=void -O3 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext\
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext \
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
// RUN: mlir-opt %s \ // RUN: mlir-opt %s \
// RUN: -async-parallel-for=async-dispatch=false \ // RUN: -async-parallel-for=async-dispatch=false \
// RUN: -async-to-async-runtime \ // RUN: -async-to-async-runtime \
// RUN: -async-runtime-ref-counting \ // RUN: -async-runtime-ref-counting \
// RUN: -async-runtime-ref-counting-opt \ // RUN: -async-runtime-ref-counting-opt \
// RUN: -convert-async-to-llvm \ // RUN: -convert-async-to-llvm \
// RUN: -convert-linalg-to-loops \ // RUN: -convert-linalg-to-loops \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -arith-expand \ // RUN: -arith-expand \
// RUN: -memref-expand \ // RUN: -memref-expand \
// RUN: -convert-vector-to-llvm \ // RUN: -convert-vector-to-llvm \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O3 \ // RUN: -e entry -entry-point-result=void -O3 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext\
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext \
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
// RUN: mlir-opt %s \ // RUN: mlir-opt %s \
// RUN: -convert-linalg-to-loops \ // RUN: -convert-linalg-to-loops \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -convert-vector-to-llvm \ // RUN: -convert-vector-to-llvm \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O3 \ // RUN: -e entry -entry-point-result=void -O3 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext\
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext \
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
#map0 = affine_map<(d0, d1) -> (d0, d1)> #map0 = affine_map<(d0, d1) -> (d0, d1)>
func.func @scf_parallel(%lhs: memref<?x?xf32>, func.func @scf_parallel(%lhs: memref<?x?xf32>,
%rhs: memref<?x?xf32>, %rhs: memref<?x?xf32>,
%sum: memref<?x?xf32>) { %sum: memref<?x?xf32>) {
%c0 = arith.constant 0 : index %c0 = arith.constant 0 : index
▲ Show 20 Lines • Show All 94 Lines • Show Last 20 Lines

mlir/test/Integration/Dialect/Async/CPU/test-async-parallel-for-1d.mlir

// RUN: mlir-opt %s -async-parallel-for \ // RUN: mlir-opt %s -async-parallel-for \
// RUN: -async-to-async-runtime \ // RUN: -async-to-async-runtime \
// RUN: -async-runtime-ref-counting \ // RUN: -async-runtime-ref-counting \
// RUN: -async-runtime-ref-counting-opt \ // RUN: -async-runtime-ref-counting-opt \
// RUN: -convert-async-to-llvm \ // RUN: -convert-async-to-llvm \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -arith-expand \ // RUN: -arith-expand \
// RUN: -memref-expand \ // RUN: -memref-expand \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O0 \ // RUN: -e entry -entry-point-result=void -O0 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext\
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
// RUN: mlir-opt %s -async-parallel-for \ // RUN: mlir-opt %s -async-parallel-for \
// RUN: -async-to-async-runtime \ // RUN: -async-to-async-runtime \
// RUN: -async-runtime-policy-based-ref-counting \ // RUN: -async-runtime-policy-based-ref-counting \
// RUN: -convert-async-to-llvm \ // RUN: -convert-async-to-llvm \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -arith-expand \ // RUN: -arith-expand \
// RUN: -memref-expand \ // RUN: -memref-expand \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O0 \ // RUN: -e entry -entry-point-result=void -O0 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext\
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
// RUN: mlir-opt %s -async-parallel-for="async-dispatch=false \ // RUN: mlir-opt %s -async-parallel-for="async-dispatch=false \
// RUN: num-workers=20 \ // RUN: num-workers=20 \
// RUN: min-task-size=1" \ // RUN: min-task-size=1" \
// RUN: -async-to-async-runtime \ // RUN: -async-to-async-runtime \
// RUN: -async-runtime-ref-counting \ // RUN: -async-runtime-ref-counting \
// RUN: -async-runtime-ref-counting-opt \ // RUN: -async-runtime-ref-counting-opt \
// RUN: -convert-async-to-llvm \ // RUN: -convert-async-to-llvm \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -arith-expand \ // RUN: -arith-expand \
// RUN: -memref-expand \ // RUN: -memref-expand \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O0 \ // RUN: -e entry -entry-point-result=void -O0 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext\
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
// Suppress constant folding by introducing "dynamic" zero value at runtime. // Suppress constant folding by introducing "dynamic" zero value at runtime.
func.func private @zero() -> index { func.func private @zero() -> index {
%0 = arith.constant 0 : index %0 = arith.constant 0 : index
return %0 : index return %0 : index
} }
▲ Show 20 Lines • Show All 77 Lines • Show Last 20 Lines

mlir/test/Integration/Dialect/Async/CPU/test-async-parallel-for-2d.mlir

// RUN: mlir-opt %s -async-parallel-for \ // RUN: mlir-opt %s -async-parallel-for \
// RUN: -async-to-async-runtime \ // RUN: -async-to-async-runtime \
// RUN: -async-runtime-ref-counting \ // RUN: -async-runtime-ref-counting \
// RUN: -async-runtime-ref-counting-opt \ // RUN: -async-runtime-ref-counting-opt \
// RUN: -arith-expand \ // RUN: -arith-expand \
// RUN: -convert-async-to-llvm \ // RUN: -convert-async-to-llvm \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O0 \ // RUN: -e entry -entry-point-result=void -O0 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext\
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
// RUN: mlir-opt %s -async-parallel-for \ // RUN: mlir-opt %s -async-parallel-for \
// RUN: -async-to-async-runtime \ // RUN: -async-to-async-runtime \
// RUN: -async-runtime-policy-based-ref-counting \ // RUN: -async-runtime-policy-based-ref-counting \
// RUN: -arith-expand \ // RUN: -arith-expand \
// RUN: -convert-async-to-llvm \ // RUN: -convert-async-to-llvm \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O0 \ // RUN: -e entry -entry-point-result=void -O0 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext\
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
// RUN: mlir-opt %s -async-parallel-for="async-dispatch=false \ // RUN: mlir-opt %s -async-parallel-for="async-dispatch=false \
// RUN: num-workers=20 \ // RUN: num-workers=20 \
// RUN: min-task-size=1" \ // RUN: min-task-size=1" \
// RUN: -async-to-async-runtime \ // RUN: -async-to-async-runtime \
// RUN: -async-runtime-ref-counting \ // RUN: -async-runtime-ref-counting \
// RUN: -async-runtime-ref-counting-opt \ // RUN: -async-runtime-ref-counting-opt \
// RUN: -arith-expand \ // RUN: -arith-expand \
// RUN: -convert-async-to-llvm \ // RUN: -convert-async-to-llvm \
// RUN: -convert-scf-to-cf \ // RUN: -convert-scf-to-cf \
// RUN: -convert-memref-to-llvm \ // RUN: -convert-memref-to-llvm \
// RUN: -convert-func-to-llvm \ // RUN: -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts \ // RUN: -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner \ // RUN: | mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void -O0 \ // RUN: -e entry -entry-point-result=void -O0 \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_async_runtime%shlibext\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_async_runtime%shlibext\
// RUN: | FileCheck %s --dump-input=always // RUN: | FileCheck %s --dump-input=always
func.func @entry() { func.func @entry() {
%c0 = arith.constant 0.0 : f32 %c0 = arith.constant 0.0 : f32
%c1 = arith.constant 1 : index %c1 = arith.constant 1 : index
%c2 = arith.constant 2 : index %c2 = arith.constant 2 : index
%c8 = arith.constant 8 : index %c8 = arith.constant 8 : index
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mlir/test/Integration/Dialect/Complex/CPU/correctness.mlir

// RUN: mlir-opt %s \ // RUN: mlir-opt %s \
// RUN: -func-bufferize -tensor-bufferize -arith-bufferize --canonicalize \ // RUN: -func-bufferize -tensor-bufferize -arith-bufferize --canonicalize \
// RUN: -convert-scf-to-cf --convert-complex-to-standard \ // RUN: -convert-scf-to-cf --convert-complex-to-standard \
// RUN: -convert-memref-to-llvm -convert-math-to-llvm -convert-math-to-libm \ // RUN: -convert-memref-to-llvm -convert-math-to-llvm -convert-math-to-libm \
// RUN: -convert-vector-to-llvm -convert-complex-to-llvm \ // RUN: -convert-vector-to-llvm -convert-complex-to-llvm \
// RUN: -convert-func-to-llvm -reconcile-unrealized-casts |\ // RUN: -convert-func-to-llvm -reconcile-unrealized-casts |\
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext |\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext |\
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @test_unary(%input: tensor<?xcomplex<f32>>, func.func @test_unary(%input: tensor<?xcomplex<f32>>,
%func: (complex<f32>) -> complex<f32>) { %func: (complex<f32>) -> complex<f32>) {
%c0 = arith.constant 0 : index %c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index %c1 = arith.constant 1 : index
%size = tensor.dim %input, %c0: tensor<?xcomplex<f32>> %size = tensor.dim %input, %c0: tensor<?xcomplex<f32>>
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mlir/test/Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm-vector.mlir

// RUN: mlir-opt %s -convert-vector-to-llvm | \ // RUN: mlir-opt %s -convert-vector-to-llvm | \
// RUN: mlir-cpu-runner -e entry_point_with_all_constants -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry_point_with_all_constants -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext
module { module {
llvm.func @function_to_run(%a: vector<8xf32>, %b: vector<8xf32>) { llvm.func @function_to_run(%a: vector<8xf32>, %b: vector<8xf32>) {
// CHECK: ( 8, 10, 12, 14, 16, 18, 20, 22 ) // CHECK: ( 8, 10, 12, 14, 16, 18, 20, 22 )
%r0 = llvm.inline_asm asm_dialect = intel %r0 = llvm.inline_asm asm_dialect = intel
"vaddps $0, $1, $2", "=x,x,x" %a, %b: "vaddps $0, $1, $2", "=x,x,x" %a, %b:
(vector<8xf32>, vector<8xf32>) -> vector<8xf32> (vector<8xf32>, vector<8xf32>) -> vector<8xf32>
vector.print %r0: vector<8xf32> vector.print %r0: vector<8xf32>
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mlir/test/Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm.mlir

// RUN: mlir-cpu-runner %s -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner %s -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
module { module {
llvm.func @printI64(i64) llvm.func @printI64(i64)
llvm.func @entry() { llvm.func @entry() {
%c2 = llvm.mlir.constant(-42: i64) :i64 %c2 = llvm.mlir.constant(-42: i64) :i64
%val = llvm.inline_asm "xor $0, $0", "=r,r" %c2 : %val = llvm.inline_asm "xor $0, $0", "=r,r" %c2 :
(i64) -> i64 (i64) -> i64
// CHECK: 0 // CHECK: 0
llvm.call @printI64(%val) : (i64) -> () llvm.call @printI64(%val) : (i64) -> ()
llvm.return llvm.return
} }
} }

mlir/test/Integration/Dialect/LLVMIR/CPU/test-vector-reductions-fp.mlir

// RUN: mlir-cpu-runner %s -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner %s -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// End-to-end test of all fp reduction intrinsics (not exhaustive unit tests). // End-to-end test of all fp reduction intrinsics (not exhaustive unit tests).
module { module {
llvm.func @printNewline() llvm.func @printNewline()
llvm.func @printF32(f32) llvm.func @printF32(f32)
llvm.func @entry() { llvm.func @entry() {
// Setup (1,2,3,4). // Setup (1,2,3,4).
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mlir/test/Integration/Dialect/LLVMIR/CPU/test-vector-reductions-int.mlir

// RUN: mlir-cpu-runner %s -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner %s -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// End-to-end test of all int reduction intrinsics (not exhaustive unit tests). // End-to-end test of all int reduction intrinsics (not exhaustive unit tests).
module { module {
llvm.func @printNewline() llvm.func @printNewline()
llvm.func @printI64(i64) llvm.func @printI64(i64)
llvm.func @entry() { llvm.func @entry() {
// Setup (1,2,3,4). // Setup (1,2,3,4).
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mlir/test/Integration/Dialect/Linalg/CPU/matmul-vs-matvec.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
func.func @matmul(%A: memref<?x?xf32>, %B: memref<?x?xf32>) -> (memref<?x?xf32>) { func.func @matmul(%A: memref<?x?xf32>, %B: memref<?x?xf32>) -> (memref<?x?xf32>) {
%c0 = arith.constant 0 : index %c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index %c1 = arith.constant 1 : index
%f0 = arith.constant 0.0 : f32 %f0 = arith.constant 0.0 : f32
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mlir/test/Integration/Dialect/Linalg/CPU/rank-reducing-subview.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
func.func @main() { func.func @main() {
%c0 = arith.constant 0 : index %c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index %c1 = arith.constant 1 : index
%c2 = arith.constant 2 : index %c2 = arith.constant 2 : index
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mlir/test/Integration/Dialect/Linalg/CPU/test-collapse-tensor.mlir

// RUN: mlir-opt %s -linalg-bufferize \ // RUN: mlir-opt %s -linalg-bufferize \
// RUN: -arith-bufferize -tensor-bufferize -func-bufferize \ // RUN: -arith-bufferize -tensor-bufferize -func-bufferize \
// RUN: -finalizing-bufferize -buffer-deallocation -convert-linalg-to-llvm \ // RUN: -finalizing-bufferize -buffer-deallocation -convert-linalg-to-llvm \
// RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func @main() { func.func @main() {
%const = arith.constant dense<[[[[-3.9058,0.9072],[-2.9470,-2.2055],[18.3946,8.2997]],[[3.4700,5.9006],[-17.2267,4.9777],[1.0450,-0.8201]]],[[[17.6996,-11.1763],[26.7775,-3.8823],[-4.2492,-5.8966]],[[2.1259,13.1794],[-10.7136,0.8428],[16.4233,9.4589]]]]> : tensor<2x2x3x2xf32> %const = arith.constant dense<[[[[-3.9058,0.9072],[-2.9470,-2.2055],[18.3946,8.2997]],[[3.4700,5.9006],[-17.2267,4.9777],[1.0450,-0.8201]]],[[[17.6996,-11.1763],[26.7775,-3.8823],[-4.2492,-5.8966]],[[2.1259,13.1794],[-10.7136,0.8428],[16.4233,9.4589]]]]> : tensor<2x2x3x2xf32>
%dynamic = tensor.cast %const: tensor<2x2x3x2xf32> to tensor<2x?x?x?xf32> %dynamic = tensor.cast %const: tensor<2x2x3x2xf32> to tensor<2x?x?x?xf32>
%collapsed = call @collapse_dynamic_shape(%dynamic) : (tensor<2x?x?x?xf32>) -> (tensor<2x?x?xf32>) %collapsed = call @collapse_dynamic_shape(%dynamic) : (tensor<2x?x?x?xf32>) -> (tensor<2x?x?xf32>)
%unranked = tensor.cast %collapsed: tensor<2x?x?xf32> to tensor<*xf32> %unranked = tensor.cast %collapsed: tensor<2x?x?xf32> to tensor<*xf32>
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="tile-sizes=4" -convert-linalg-to-loops -convert-scf-to-cf \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=4" -convert-linalg-to-loops -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
// Creates and returns a 1-D buffer of size %s1 filled with the value %f // Creates and returns a 1-D buffer of size %s1 filled with the value %f
func.func @alloc_1d_filled_f32(%s1 : index, %f : f32) -> memref<?xf32> { func.func @alloc_1d_filled_f32(%s1 : index, %f : f32) -> memref<?xf32> {
%buf = memref.alloc(%s1) : memref<?xf32> %buf = memref.alloc(%s1) : memref<?xf32>
linalg.fill ins(%f : f32) outs(%buf : memref<?xf32>) linalg.fill ins(%f : f32) outs(%buf : memref<?xf32>)
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-nwc-wcf-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="tile-sizes=2,4" -convert-linalg-to-loops -convert-scf-to-cf \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,4" -convert-linalg-to-loops -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
// Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f // Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f
func.func @alloc_3d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %f : f32) -> memref<?x?x?xf32> { func.func @alloc_3d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %f : f32) -> memref<?x?x?xf32> {
%buf = memref.alloc(%s1, %s2, %s3) : memref<?x?x?xf32> %buf = memref.alloc(%s1, %s2, %s3) : memref<?x?x?xf32>
linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?xf32>) linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?xf32>)
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2" -convert-linalg-to-loops -convert-scf-to-cf \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2" -convert-linalg-to-loops -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
// Creates and returns a 2-D buffer of size (%s1, %s2) filled with the value %f // Creates and returns a 2-D buffer of size (%s1, %s2) filled with the value %f
func.func @alloc_2d_filled_f32(%s1 : index, %s2 : index, %f : f32) -> memref<?x?xf32> { func.func @alloc_2d_filled_f32(%s1 : index, %s2 : index, %f : f32) -> memref<?x?xf32> {
%buf = memref.alloc(%s1, %s2) : memref<?x?xf32> %buf = memref.alloc(%s1, %s2) : memref<?x?xf32>
linalg.fill ins(%f : f32) outs(%buf : memref<?x?xf32>) linalg.fill ins(%f : f32) outs(%buf : memref<?x?xf32>)
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-nhwc-hwcf-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,3,2" -convert-linalg-to-loops -convert-scf-to-cf \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,3,3,2" -convert-linalg-to-loops -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
// Creates and returns 4-D buffer of size (%s1, %s2, %s3, %s4) filled with the value %f // Creates and returns 4-D buffer of size (%s1, %s2, %s3, %s4) filled with the value %f
func.func @alloc_4d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %s4 : index, %f : f32) -> memref<?x?x?x?xf32> { func.func @alloc_4d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %s4 : index, %f : f32) -> memref<?x?x?x?xf32> {
%buf = memref.alloc(%s1, %s2, %s3, %s4) : memref<?x?x?x?xf32> %buf = memref.alloc(%s1, %s2, %s3, %s4) : memref<?x?x?x?xf32>
linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?x?xf32>) linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?x?xf32>)
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2,2" -convert-linalg-to-loops -convert-scf-to-cf \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=2,2,2" -convert-linalg-to-loops -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
// Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f // Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f
func.func @alloc_3d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %f : f32) -> memref<?x?x?xf32> { func.func @alloc_3d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %f : f32) -> memref<?x?x?xf32> {
%buf = memref.alloc(%s1, %s2, %s3) : memref<?x?x?xf32> %buf = memref.alloc(%s1, %s2, %s3) : memref<?x?x?xf32>
linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?xf32>) linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?xf32>)
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mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-ndhwc-dhwcf-call.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="tile-sizes=0,5,5,5" -convert-linalg-to-loops -convert-scf-to-cf \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=0,5,5,5" -convert-linalg-to-loops -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
// Creates and returns 5-D buffer of size (%s1, %s2, %s3, %s4, %s5) filled with the value %f // Creates and returns 5-D buffer of size (%s1, %s2, %s3, %s4, %s5) filled with the value %f
func.func @alloc_5d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %s4 : index, %s5 : index, %f : f32) -> memref<?x?x?x?x?xf32> { func.func @alloc_5d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %s4 : index, %s5 : index, %f : f32) -> memref<?x?x?x?x?xf32> {
%buf = memref.alloc(%s1, %s2, %s3, %s4, %s5) : memref<?x?x?x?x?xf32> %buf = memref.alloc(%s1, %s2, %s3, %s4, %s5) : memref<?x?x?x?x?xf32>
linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?x?x?xf32>) linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?x?x?xf32>)
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mlir/test/Integration/Dialect/Linalg/CPU/test-elementwise.mlir

// RUN: mlir-opt %s -convert-elementwise-to-linalg \ // RUN: mlir-opt %s -convert-elementwise-to-linalg \
// RUN: -arith-bufferize -linalg-bufferize -tensor-bufferize \ // RUN: -arith-bufferize -linalg-bufferize -tensor-bufferize \
// RUN: -func-bufferize -buffer-deallocation -convert-linalg-to-loops \ // RUN: -func-bufferize -buffer-deallocation -convert-linalg-to-loops \
// RUN: -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm \ // RUN: -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm \
// RUN: -reconcile-unrealized-casts | \ // RUN: -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func @main() { func.func @main() {
%a = arith.constant dense<[1.0, 2.0, 3.0]> : tensor<3xf32> %a = arith.constant dense<[1.0, 2.0, 3.0]> : tensor<3xf32>
%b = arith.constant dense<[10.0, 20.0, 30.0]> : tensor<3xf32> %b = arith.constant dense<[10.0, 20.0, 30.0]> : tensor<3xf32>
%addf = arith.addf %a, %b : tensor<3xf32> %addf = arith.addf %a, %b : tensor<3xf32>
%addf_unranked = tensor.cast %addf : tensor<3xf32> to tensor<*xf32> %addf_unranked = tensor.cast %addf : tensor<3xf32> to tensor<*xf32>
call @printMemrefF32(%addf_unranked) : (tensor<*xf32>) -> () call @printMemrefF32(%addf_unranked) : (tensor<*xf32>) -> ()
// CHECK: Unranked Memref base@ = {{.*}} rank = 1 offset = 0 sizes = [3] strides = [1] data = // CHECK: Unranked Memref base@ = {{.*}} rank = 1 offset = 0 sizes = [3] strides = [1] data =
// CHECK-NEXT: [11, 22, 33] // CHECK-NEXT: [11, 22, 33]
return return
} }
func.func private @printMemrefF32(%ptr : tensor<*xf32>) func.func private @printMemrefF32(%ptr : tensor<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-expand-tensor.mlir

// RUN: mlir-opt %s -linalg-bufferize \ // RUN: mlir-opt %s -linalg-bufferize \
// RUN: -arith-bufferize -tensor-bufferize -func-bufferize \ // RUN: -arith-bufferize -tensor-bufferize -func-bufferize \
// RUN: -finalizing-bufferize -buffer-deallocation -convert-linalg-to-llvm \ // RUN: -finalizing-bufferize -buffer-deallocation -convert-linalg-to-llvm \
// RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func @main() { func.func @main() {
%const = arith.constant dense<[[[-3.9058,0.9072],[-2.9470,-2.2055],[18.3946,8.2997],[3.4700,5.9006],[-17.2267,4.9777],[1.0450,-0.8201]],[[17.6996,-11.1763],[26.7775,-3.8823],[-4.2492,-5.8966],[2.1259,13.1794],[-10.7136,0.8428],[16.4233,9.4589]]]> : tensor<2x6x2xf32> %const = arith.constant dense<[[[-3.9058,0.9072],[-2.9470,-2.2055],[18.3946,8.2997],[3.4700,5.9006],[-17.2267,4.9777],[1.0450,-0.8201]],[[17.6996,-11.1763],[26.7775,-3.8823],[-4.2492,-5.8966],[2.1259,13.1794],[-10.7136,0.8428],[16.4233,9.4589]]]> : tensor<2x6x2xf32>
%dynamic = tensor.cast %const: tensor<2x6x2xf32> to tensor<2x?x?xf32> %dynamic = tensor.cast %const: tensor<2x6x2xf32> to tensor<2x?x?xf32>
%expanded = call @expand_dynamic_shape(%dynamic) : (tensor<2x?x?xf32>) -> (tensor<2x2x?x1x?xf32>) %expanded = call @expand_dynamic_shape(%dynamic) : (tensor<2x?x?xf32>) -> (tensor<2x2x?x1x?xf32>)
%unranked = tensor.cast %expanded: tensor<2x2x?x1x?xf32> to tensor<*xf32> %unranked = tensor.cast %expanded: tensor<2x2x?x1x?xf32> to tensor<*xf32>
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mlir/test/Integration/Dialect/Linalg/CPU/test-one-shot-bufferize.mlir

// RUN: mlir-opt %s -pass-pipeline="func.func(canonicalize,cse),one-shot-bufferize{bufferize-function-boundaries}" |\ // RUN: mlir-opt %s -pass-pipeline="func.func(canonicalize,cse),one-shot-bufferize{bufferize-function-boundaries}" |\
// RUN: mlir-opt -pass-pipeline="func.func(buffer-deallocation,convert-vector-to-scf,lower-affine,convert-linalg-to-loops)" |\ // RUN: mlir-opt -pass-pipeline="func.func(buffer-deallocation,convert-vector-to-scf,lower-affine,convert-linalg-to-loops)" |\
// RUN: mlir-opt -pass-pipeline="func.func(canonicalize,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt -pass-pipeline="func.func(canonicalize,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext |\ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext,%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext |\
// RUN: FileCheck %s // RUN: FileCheck %s
#map0 = affine_map<(d0, d1)[s0] -> ((d1 - d0) ceildiv s0)> #map0 = affine_map<(d0, d1)[s0] -> ((d1 - d0) ceildiv s0)>
#map1 = affine_map<(d0, d1)[s0] -> ((d0 - d1) ceildiv s0)> #map1 = affine_map<(d0, d1)[s0] -> ((d0 - d1) ceildiv s0)>
func.func @init_and_dot(%arg0: tensor<64xf32>, %arg1: tensor<64xf32>, %arg2: tensor<f32>) -> tensor<f32> { func.func @init_and_dot(%arg0: tensor<64xf32>, %arg1: tensor<64xf32>, %arg2: tensor<f32>) -> tensor<f32> {
%c64 = arith.constant 64 : index %c64 = arith.constant 64 : index
%cst = arith.constant 0.000000e+00 : f32 %cst = arith.constant 0.000000e+00 : f32
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mlir/test/Integration/Dialect/Linalg/CPU/test-padtensor.mlir

// RUN: mlir-opt %s -test-linalg-transform-patterns=test-linalg-to-vector-patterns \ // RUN: mlir-opt %s -test-linalg-transform-patterns=test-linalg-to-vector-patterns \
// RUN: -linalg-init-tensor-to-alloc-tensor -linalg-bufferize -arith-bufferize \ // RUN: -linalg-init-tensor-to-alloc-tensor -linalg-bufferize -arith-bufferize \
// RUN: -bufferization-bufferize -tensor-bufferize -func-bufferize \ // RUN: -bufferization-bufferize -tensor-bufferize -func-bufferize \
// RUN: -finalizing-bufferize -buffer-deallocation \ // RUN: -finalizing-bufferize -buffer-deallocation \
// RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext,%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func @main() { func.func @main() {
%const = arith.constant dense<[[[1.0, 2.0, 3.0], [2.0, 3.0, 4.0]]]> : tensor<1x2x3xf32> %const = arith.constant dense<[[[1.0, 2.0, 3.0], [2.0, 3.0, 4.0]]]> : tensor<1x2x3xf32>
%dynamic = tensor.cast %const: tensor<1x2x3xf32> to tensor<1x?x3xf32> %dynamic = tensor.cast %const: tensor<1x2x3xf32> to tensor<1x?x3xf32>
%offset = arith.constant 2 : index %offset = arith.constant 2 : index
%cst = arith.constant 2.3 : f32 %cst = arith.constant 2.3 : f32
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mlir/test/Integration/Dialect/Linalg/CPU/test-subtensor-insert-multiple-uses.mlir

// RUN: mlir-opt %s -linalg-bufferize \ // RUN: mlir-opt %s -linalg-bufferize \
// RUN: -arith-bufferize -tensor-bufferize -func-bufferize \ // RUN: -arith-bufferize -tensor-bufferize -func-bufferize \
// RUN: -finalizing-bufferize -buffer-deallocation \ // RUN: -finalizing-bufferize -buffer-deallocation \
// RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext,%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func @main() { func.func @main() {
%const = arith.constant dense<10.0> : tensor<2xf32> %const = arith.constant dense<10.0> : tensor<2xf32>
%insert_val = arith.constant dense<20.0> : tensor<1xf32> %insert_val = arith.constant dense<20.0> : tensor<1xf32>
// Both of these insert_slice ops insert into the same original tensor // Both of these insert_slice ops insert into the same original tensor
// value `%const`. This can easily cause bugs if at the memref level // value `%const`. This can easily cause bugs if at the memref level
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mlir/test/Integration/Dialect/Linalg/CPU/test-subtensor-insert.mlir

// RUN: mlir-opt %s -linalg-bufferize \ // RUN: mlir-opt %s -linalg-bufferize \
// RUN: -arith-bufferize -tensor-bufferize -func-bufferize \ // RUN: -arith-bufferize -tensor-bufferize -func-bufferize \
// RUN: -finalizing-bufferize -buffer-deallocation \ // RUN: -finalizing-bufferize -buffer-deallocation \
// RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func @main() { func.func @main() {
%const = arith.constant dense<10.0> : tensor<2xf32> %const = arith.constant dense<10.0> : tensor<2xf32>
%insert_val = arith.constant dense<20.0> : tensor<1xf32> %insert_val = arith.constant dense<20.0> : tensor<1xf32>
%inserted = tensor.insert_slice %insert_val into %const[0][1][1] : tensor<1xf32> into tensor<2xf32> %inserted = tensor.insert_slice %insert_val into %const[0][1][1] : tensor<1xf32> into tensor<2xf32>
%unranked = tensor.cast %inserted : tensor<2xf32> to tensor<*xf32> %unranked = tensor.cast %inserted : tensor<2xf32> to tensor<*xf32>
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mlir/test/Integration/Dialect/Linalg/CPU/test-tensor-e2e.mlir

// RUN: mlir-opt %s -arith-bufferize -linalg-bufferize \ // RUN: mlir-opt %s -arith-bufferize -linalg-bufferize \
// RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -buffer-deallocation -convert-linalg-to-loops \ // RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -buffer-deallocation -convert-linalg-to-loops \
// RUN: -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func @foo() -> tensor<4xf32> { func.func @foo() -> tensor<4xf32> {
%0 = arith.constant dense<[1.0, 2.0, 3.0, 4.0]> : tensor<4xf32> %0 = arith.constant dense<[1.0, 2.0, 3.0, 4.0]> : tensor<4xf32>
return %0 : tensor<4xf32> return %0 : tensor<4xf32>
} }
func.func @main() { func.func @main() {
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mlir/test/Integration/Dialect/Linalg/CPU/test-tensor-matmul.mlir

// UNSUPPORTED: asan // UNSUPPORTED: asan
// RUN: mlir-opt %s -linalg-bufferize -arith-bufferize \ // RUN: mlir-opt %s -linalg-bufferize -arith-bufferize \
// RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -buffer-deallocation -convert-linalg-to-loops -convert-scf-to-cf \ // RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -buffer-deallocation -convert-linalg-to-loops -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext,%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
// RUN: mlir-opt %s -linalg-tile="tile-sizes=1,2,3" -linalg-bufferize \ // RUN: mlir-opt %s -linalg-tile="tile-sizes=1,2,3" -linalg-bufferize \
// RUN: -scf-bufferize -arith-bufferize -tensor-bufferize \ // RUN: -scf-bufferize -arith-bufferize -tensor-bufferize \
// RUN: -func-bufferize \ // RUN: -func-bufferize \
// RUN: -finalizing-bufferize -convert-linalg-to-loops -convert-scf-to-cf -convert-scf-to-cf \ // RUN: -finalizing-bufferize -convert-linalg-to-loops -convert-scf-to-cf -convert-scf-to-cf \
// RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-linalg-to-llvm -lower-affine -convert-scf-to-cf --convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext,%linalg_test_lib_dir/libmlir_runner_utils%shlibext \
// RUN: | FileCheck %s // RUN: | FileCheck %s
func.func @main() { func.func @main() {
%A = arith.constant dense<[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]> : tensor<2x3xf32> %A = arith.constant dense<[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]> : tensor<2x3xf32>
%B = arith.constant dense<[[1.0, 2.0, 3.0, 4.0], %B = arith.constant dense<[[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0], [5.0, 6.0, 7.0, 8.0],
[9.0, 10.0, 11.0, 12.0]]> : tensor<3x4xf32> [9.0, 10.0, 11.0, 12.0]]> : tensor<3x4xf32>
%C = arith.constant dense<1000.0> : tensor<2x4xf32> %C = arith.constant dense<1000.0> : tensor<2x4xf32>
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mlir/test/Integration/Dialect/SparseTensor/CPU/concatenate.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#MAT_C_C = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> #MAT_C_C = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>
#MAT_D_C = #sparse_tensor.encoding<{dimLevelType = ["dense", "compressed"]}> #MAT_D_C = #sparse_tensor.encoding<{dimLevelType = ["dense", "compressed"]}>
#MAT_C_D = #sparse_tensor.encoding<{dimLevelType = ["compressed", "dense"]}> #MAT_C_D = #sparse_tensor.encoding<{dimLevelType = ["compressed", "dense"]}>
#MAT_C_C_P = #sparse_tensor.encoding<{ #MAT_C_C_P = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ], dimLevelType = [ "compressed", "compressed" ],
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mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#DenseMatrix = #sparse_tensor.encoding<{ #DenseMatrix = #sparse_tensor.encoding<{
dimLevelType = [ "dense", "dense" ], dimLevelType = [ "dense", "dense" ],
dimOrdering = affine_map<(i,j) -> (i,j)> dimOrdering = affine_map<(i,j) -> (i,j)>
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_bf16.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#DenseVector = #sparse_tensor.encoding<{dimLevelType = ["dense"]}> #DenseVector = #sparse_tensor.encoding<{dimLevelType = ["dense"]}>
#trait_vec_op = { #trait_vec_op = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // a (in) affine_map<(i) -> (i)>, // a (in)
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mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#DenseVector = #sparse_tensor.encoding<{dimLevelType = ["dense"]}> #DenseVector = #sparse_tensor.encoding<{dimLevelType = ["dense"]}>
#trait_vec_op = { #trait_vec_op = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // a (in) affine_map<(i) -> (i)>, // a (in)
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }> #SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>
#trait_op = { #trait_op = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // a affine_map<(i) -> (i)>, // a
affine_map<(i) -> (i)> // x (out) affine_map<(i) -> (i)> // x (out)
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> #DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>
// //
// Traits for tensor operations. // Traits for tensor operations.
// //
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_cast.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SV = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }> #SV = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>
#trait_cast = { #trait_cast = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // A (in) affine_map<(i) -> (i)>, // A (in)
affine_map<(i) -> (i)> // X (out) affine_map<(i) -> (i)> // X (out)
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex32.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#trait_op = { #trait_op = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // a (in) affine_map<(i) -> (i)>, // a (in)
affine_map<(i) -> (i)>, // b (in) affine_map<(i) -> (i)>, // b (in)
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex64.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#trait_op = { #trait_op = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // a (in) affine_map<(i) -> (i)>, // a (in)
affine_map<(i) -> (i)>, // b (in) affine_map<(i) -> (i)>, // b (in)
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex_ops.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#trait_op1 = { #trait_op1 = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // a (in) affine_map<(i) -> (i)>, // a (in)
affine_map<(i) -> (i)> // x (out) affine_map<(i) -> (i)> // x (out)
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_constant_to_sparse_tensor.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#Tensor1 = #sparse_tensor.encoding<{ #Tensor1 = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed"] dimLevelType = [ "compressed", "compressed"]
}> }>
// //
// Integration tests for conversions from sparse constants to sparse tensors. // Integration tests for conversions from sparse constants to sparse tensors.
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#Tensor1 = #sparse_tensor.encoding<{ #Tensor1 = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed", "compressed" ], dimLevelType = [ "compressed", "compressed", "compressed" ],
dimOrdering = affine_map<(i,j,k) -> (i,j,k)> dimOrdering = affine_map<(i,j,k) -> (i,j,k)>
}> }>
#Tensor2 = #sparse_tensor.encoding<{ #Tensor2 = #sparse_tensor.encoding<{
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_dyn.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#DCSR = #sparse_tensor.encoding<{ #DCSR = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed" ]
}> }>
#DCSC = #sparse_tensor.encoding<{ #DCSC = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ], dimLevelType = [ "compressed", "compressed" ],
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_ptr.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#DCSR = #sparse_tensor.encoding<{ #DCSR = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ], dimLevelType = [ "compressed", "compressed" ],
pointerBitWidth = 8, pointerBitWidth = 8,
indexBitWidth = 8 indexBitWidth = 8
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext \
// RUN: | \ // RUN: | \
// RUN: FileCheck %s // RUN: FileCheck %s
#Tensor1 = #sparse_tensor.encoding<{ #Tensor1 = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed", "compressed" ], dimLevelType = [ "compressed", "compressed", "compressed" ],
dimOrdering = affine_map<(i,j,k) -> (i,j,k)> dimOrdering = affine_map<(i,j,k) -> (i,j,k)>
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2sparse.mlir

// Force this file to use the kDirect method for sparse2sparse. // Force this file to use the kDirect method for sparse2sparse.
// RUN: mlir-opt %s --sparse-compiler="s2s-strategy=2" | \ // RUN: mlir-opt %s --sparse-compiler="s2s-strategy=2" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#Tensor1 = #sparse_tensor.encoding<{ #Tensor1 = #sparse_tensor.encoding<{
dimLevelType = [ "dense", "dense", "compressed" ] dimLevelType = [ "dense", "dense", "compressed" ]
}> }>
// NOTE: dense after compressed is not currently supported for the target // NOTE: dense after compressed is not currently supported for the target
// of direct-sparse2sparse conversion. (It's fine for the source though.) // of direct-sparse2sparse conversion. (It's fine for the source though.)
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dot.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }> #SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>
module { module {
// //
// Sparse kernel. // Sparse kernel.
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_filter_conv2d.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#DCSR = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }> #DCSR = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>
// An example of a 2D convolution with a sparse filter. // An example of a 2D convolution with a sparse filter.
module { module {
func.func @conv2d(%input: tensor<8x8xi32>, func.func @conv2d(%input: tensor<8x8xi32>,
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_flatten.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test.tns" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test.tns" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test.tns" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test.tns" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#SparseTensor = #sparse_tensor.encoding<{ #SparseTensor = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed", "compressed", "compressed", dimLevelType = [ "compressed", "compressed", "compressed", "compressed",
"compressed", "compressed", "compressed", "compressed" ], "compressed", "compressed", "compressed", "compressed" ],
// Note that any dimOrdering permutation should give the same results // Note that any dimOrdering permutation should give the same results
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{ #SparseVector = #sparse_tensor.encoding<{
dimLevelType = ["compressed"] dimLevelType = ["compressed"]
}> }>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = ["compressed", "compressed"] dimLevelType = ["compressed", "compressed"]
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{ #SparseVector = #sparse_tensor.encoding<{
dimLevelType = ["compressed"] dimLevelType = ["compressed"]
}> }>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = ["compressed", "compressed"] dimLevelType = ["compressed", "compressed"]
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matmul.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#CSR = #sparse_tensor.encoding<{ #CSR = #sparse_tensor.encoding<{
dimLevelType = [ "dense", "compressed" ], dimLevelType = [ "dense", "compressed" ],
dimOrdering = affine_map<(i,j) -> (i,j)> dimOrdering = affine_map<(i,j) -> (i,j)>
}> }>
#DCSR = #sparse_tensor.encoding<{ #DCSR = #sparse_tensor.encoding<{
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matrix_ops.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> #DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>
// //
// Traits for 2-d tensor (aka matrix) operations. // Traits for 2-d tensor (aka matrix) operations.
// //
#trait_scale = { #trait_scale = {
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s \ // RUN: mlir-opt %s \
// RUN: --sparse-compiler="vectorization-strategy=2 vl=16 enable-simd-index32" | \ // RUN: --sparse-compiler="vectorization-strategy=2 vl=16 enable-simd-index32" | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = [ "dense", "compressed" ], dimLevelType = [ "dense", "compressed" ],
pointerBitWidth = 8, pointerBitWidth = 8,
indexBitWidth = 8 indexBitWidth = 8
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_mttkrp.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/mttkrp_b.tns" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/mttkrp_b.tns" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/mttkrp_b.tns" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/mttkrp_b.tns" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#SparseTensor = #sparse_tensor.encoding<{ #SparseTensor = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed", "compressed" ]
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_mult_elt.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#DCSR = #sparse_tensor.encoding<{ #DCSR = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed" ]
}> }>
#trait_mult_elt = { #trait_mult_elt = {
indexing_maps = [ indexing_maps = [
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_reduction.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed" ]
}> }>
#SparseTensor = #sparse_tensor.encoding<{ #SparseTensor = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed", "compressed" ]
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_simple.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#DCSR = #sparse_tensor.encoding<{ #DCSR = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ], dimLevelType = [ "compressed", "compressed" ],
dimOrdering = affine_map<(i,j) -> (i,j)> dimOrdering = affine_map<(i,j) -> (i,j)>
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_quantized_matmul.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#DCSR = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }> #DCSR = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>
// An example of a quantized sparse matmul. With the zero offset for the // An example of a quantized sparse matmul. With the zero offset for the
// sparse input, the sparse compiler generates very efficient code for the // sparse input, the sparse compiler generates very efficient code for the
// x(i,j) += (ext(a(i,k)) - 2) * ext(b(k,j)) // x(i,j) += (ext(a(i,k)) - 2) * ext(b(k,j))
// operation. // operation.
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_re_im.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#trait_op = { #trait_op = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // a (in) affine_map<(i) -> (i)>, // a (in)
affine_map<(i) -> (i)> // x (out) affine_map<(i) -> (i)> // x (out)
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reduce_custom.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#CSR = #sparse_tensor.encoding<{dimLevelType = ["dense", "compressed"]}> #CSR = #sparse_tensor.encoding<{dimLevelType = ["dense", "compressed"]}>
#CSC = #sparse_tensor.encoding<{ #CSC = #sparse_tensor.encoding<{
dimLevelType = [ "dense", "compressed" ], dimLevelType = [ "dense", "compressed" ],
dimOrdering = affine_map<(i,j) -> (j,i)> dimOrdering = affine_map<(i,j) -> (j,i)>
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reductions.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=8" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=8" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SV = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }> #SV = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>
#DV = #sparse_tensor.encoding<{ dimLevelType = [ "dense" ] }> #DV = #sparse_tensor.encoding<{ dimLevelType = [ "dense" ] }>
#trait_reduction = { #trait_reduction = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // a affine_map<(i) -> (i)>, // a
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{ #SparseVector = #sparse_tensor.encoding<{
dimLevelType = ["compressed"] dimLevelType = ["compressed"]
}> }>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = ["compressed", "compressed"] dimLevelType = ["compressed", "compressed"]
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_matmul.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s \ // RUN: mlir-opt %s \
// RUN: --sparse-compiler="vectorization-strategy=2 vl=4 enable-simd-index32" | \ // RUN: --sparse-compiler="vectorization-strategy=2 vl=4 enable-simd-index32" | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ], dimLevelType = [ "compressed", "compressed" ],
pointerBitWidth = 32, pointerBitWidth = 32,
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_mm_fusion.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=8" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=8" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SM = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }> #SM = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>
#trait_sampled_dense_dense = { #trait_sampled_dense_dense = {
indexing_maps = [ indexing_maps = [
affine_map<(i,j,k) -> (i,j)>, // S affine_map<(i,j,k) -> (i,j)>, // S
affine_map<(i,j,k) -> (i,k)>, // A affine_map<(i,j,k) -> (i,k)>, // A
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scale.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=4" | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#CSR = #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ] }> #CSR = #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ] }>
#trait_scale = { #trait_scale = {
indexing_maps = [ indexing_maps = [
affine_map<(i,j) -> (i,j)> // X (out) affine_map<(i,j) -> (i,j)> // X (out)
], ],
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scf_nested.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#map = affine_map<(d0, d1, d2) -> (d0, d1, d2)> #map = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
#SparseMatrix = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed", "compressed" ] }> #SparseMatrix = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed", "compressed" ] }>
module @func_sparse.2 { module @func_sparse.2 {
// Do elementwise x+1 when true, x-1 when false // Do elementwise x+1 when true, x-1 when false
func.func public @condition(%cond: i1, %arg0: tensor<2x3x4xf64, #SparseMatrix>) -> tensor<2x3x4xf64, #SparseMatrix> { func.func public @condition(%cond: i1, %arg0: tensor<2x3x4xf64, #SparseMatrix>) -> tensor<2x3x4xf64, #SparseMatrix> {
▲ Show 20 Lines • Show All 62 Lines • ▼ Show 20 Lines func.func public @entry() {
call @dump(%sm_f) : (tensor<2x3x4xf64, #SparseMatrix>) -> () call @dump(%sm_f) : (tensor<2x3x4xf64, #SparseMatrix>) -> ()
bufferization.dealloc_tensor %sm : tensor<2x3x4xf64, #SparseMatrix> bufferization.dealloc_tensor %sm : tensor<2x3x4xf64, #SparseMatrix>
bufferization.dealloc_tensor %sm_t : tensor<2x3x4xf64, #SparseMatrix> bufferization.dealloc_tensor %sm_t : tensor<2x3x4xf64, #SparseMatrix>
bufferization.dealloc_tensor %sm_f : tensor<2x3x4xf64, #SparseMatrix> bufferization.dealloc_tensor %sm_f : tensor<2x3x4xf64, #SparseMatrix>
return return
} }
} }
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sign.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }> #SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>
#trait_op = { #trait_op = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)>, // a affine_map<(i) -> (i)>, // a
affine_map<(i) -> (i)> // x (out) affine_map<(i) -> (i)> // x (out)
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/wide.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = [ "dense", "compressed" ] dimLevelType = [ "dense", "compressed" ]
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_storage.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Several common sparse storage schemes. // Several common sparse storage schemes.
// //
#Dense = #sparse_tensor.encoding<{ #Dense = #sparse_tensor.encoding<{
dimLevelType = [ "dense", "dense" ] dimLevelType = [ "dense", "dense" ]
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test_symmetric.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test_symmetric.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Do the same run, but now with SIMDization as well. This should not change the outcome. // Do the same run, but now with SIMDization as well. This should not change the outcome.
// //
// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \ // RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=2 vl=2" | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test_symmetric.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test_symmetric.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed" ]
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed" ]
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: TENSOR0="%mlir_integration_test_dir/data/test_symmetric_complex.mtx" \ // RUN: TENSOR0="%mlir_integration_test_dir/data/test_symmetric_complex.mtx" \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed" ]
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!Filename = !llvm.ptr<i8> !Filename = !llvm.ptr<i8>
#SparseMatrix = #sparse_tensor.encoding<{ #SparseMatrix = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed" ]
}> }>
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tanh.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }> #SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }>
#trait_op = { #trait_op = {
indexing_maps = [ indexing_maps = [
affine_map<(i) -> (i)> // X (out) affine_map<(i) -> (i)> // X (out)
], ],
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_mul.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#ST = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed", "compressed"]}> #ST = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed", "compressed"]}>
// //
// Trait for 3-d tensor element wise multiplication. // Trait for 3-d tensor element wise multiplication.
// //
#trait_mul = { #trait_mul = {
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_ops.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#ST1 = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed", "compressed"]}> #ST1 = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed", "compressed"]}>
#ST2 = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed", "dense"]}> #ST2 = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed", "dense"]}>
// //
// Trait for 3-d tensor operation. // Trait for 3-d tensor operation.
// //
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#DCSR = #sparse_tensor.encoding<{ #DCSR = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ] dimLevelType = [ "compressed", "compressed" ]
}> }>
#DCSC = #sparse_tensor.encoding<{ #DCSC = #sparse_tensor.encoding<{
dimLevelType = [ "compressed", "compressed" ], dimLevelType = [ "compressed", "compressed" ],
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_unary.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}> #DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>
// //
// Traits for tensor operations. // Traits for tensor operations.
// //
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mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_vector_ops.mlir

// RUN: mlir-opt %s --sparse-compiler | \ // RUN: mlir-opt %s --sparse-compiler | \
// RUN: mlir-cpu-runner \ // RUN: mlir-cpu-runner \
// RUN: -e entry -entry-point-result=void \ // RUN: -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}> #SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
#DenseVector = #sparse_tensor.encoding<{dimLevelType = ["dense"]}> #DenseVector = #sparse_tensor.encoding<{dimLevelType = ["dense"]}>
// //
// Traits for 1-d tensor (aka vector) operations. // Traits for 1-d tensor (aka vector) operations.
// //
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mlir/test/Integration/Dialect/Standard/CPU/test-ceil-floor-pos-neg.mlir

// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf,memref-expand,arith-expand),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf,memref-expand,arith-expand),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @transfer_read_2d(%A : memref<40xi32>, %base1: index) { func.func @transfer_read_2d(%A : memref<40xi32>, %base1: index) {
%i42 = arith.constant -42: i32 %i42 = arith.constant -42: i32
%f = vector.transfer_read %A[%base1], %i42 %f = vector.transfer_read %A[%base1], %i42
{permutation_map = affine_map<(d0) -> (d0)>} : {permutation_map = affine_map<(d0) -> (d0)>} :
memref<40xi32>, vector<40xi32> memref<40xi32>, vector<40xi32>
vector.print %f: vector<40xi32> vector.print %f: vector<40xi32>
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mlir/test/Integration/Dialect/Standard/CPU/test_subview.mlir

// RUN: mlir-opt %s -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext | FileCheck %s // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext | FileCheck %s
memref.global "private" constant @__constant_5x3xf32 : memref<5x3xf32> = memref.global "private" constant @__constant_5x3xf32 : memref<5x3xf32> =
dense<[[0.0, 1.0, 2.0], dense<[[0.0, 1.0, 2.0],
[3.0, 4.0, 5.0], [3.0, 4.0, 5.0],
[6.0, 7.0, 8.0], [6.0, 7.0, 8.0],
[9.0, 10.0, 11.0], [9.0, 10.0, 11.0],
[12.0, 13.0, 14.0]]> [12.0, 13.0, 14.0]]>
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mlir/test/Integration/Dialect/Vector/CPU/AMX/test-mulf-full.mlir

// RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf \ // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf \
// RUN: -arith-bufferize -convert-vector-to-llvm="enable-amx" \ // RUN: -arith-bufferize -convert-vector-to-llvm="enable-amx" \
// RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate -mlir-to-llvmir | \ // RUN: mlir-translate -mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" \ // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" \
// RUN: --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Note: To run this test, your CPU must support AMX. // Note: To run this test, your CPU must support AMX.
// Multiply full size tiles into zero destination. // Multiply full size tiles into zero destination.
func.func @kernel(%arg0: memref<16x32xbf16>, func.func @kernel(%arg0: memref<16x32xbf16>,
%arg1: memref<16x32xbf16>, %arg1: memref<16x32xbf16>,
%arg2: memref<16x16xf32>) { %arg2: memref<16x16xf32>) {
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mlir/test/Integration/Dialect/Vector/CPU/AMX/test-mulf.mlir

// RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate -mlir-to-llvmir | \ // RUN: mlir-translate -mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Note: To run this test, your CPU must support AMX. // Note: To run this test, your CPU must support AMX.
// Multiply into zeroed destination. // Multiply into zeroed destination.
func.func @kernel1(%arg0: memref<2x4xbf16>, func.func @kernel1(%arg0: memref<2x4xbf16>,
%arg1: memref<2x4xbf16>, %arg1: memref<2x4xbf16>,
%arg2: memref<2x2xf32>) { %arg2: memref<2x2xf32>) {
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mlir/test/Integration/Dialect/Vector/CPU/AMX/test-muli-ext.mlir

// RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate -mlir-to-llvmir | \ // RUN: mlir-translate -mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Note: To run this test, your CPU must support AMX. // Note: To run this test, your CPU must support AMX.
func.func @print(%arg0: memref<16x4xi32>) { func.func @print(%arg0: memref<16x4xi32>) {
%iu = arith.constant -1: i32 %iu = arith.constant -1: i32
%c0 = arith.constant 0: index %c0 = arith.constant 0: index
%c1 = arith.constant 1: index %c1 = arith.constant 1: index
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mlir/test/Integration/Dialect/Vector/CPU/AMX/test-muli-full.mlir

// RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf \ // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf \
// RUN: -arith-bufferize -convert-vector-to-llvm="enable-amx" \ // RUN: -arith-bufferize -convert-vector-to-llvm="enable-amx" \
// RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate -mlir-to-llvmir | \ // RUN: mlir-translate -mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" \ // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" \
// RUN: --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Note: To run this test, your CPU must support AMX. // Note: To run this test, your CPU must support AMX.
// Multiply full size tiles into zero destination. // Multiply full size tiles into zero destination.
func.func @kernel(%arg0: memref<16x64xi8>, func.func @kernel(%arg0: memref<16x64xi8>,
%arg1: memref<16x64xi8>, %arg1: memref<16x64xi8>,
%arg2: memref<16x16xi32>) { %arg2: memref<16x16xi32>) {
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mlir/test/Integration/Dialect/Vector/CPU/AMX/test-muli.mlir

// RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate -mlir-to-llvmir | \ // RUN: mlir-translate -mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Note: To run this test, your CPU must support AMX. // Note: To run this test, your CPU must support AMX.
// Multiply into zeroed destination. // Multiply into zeroed destination.
func.func @kernel1(%arg0: memref<2x8xi8>, func.func @kernel1(%arg0: memref<2x8xi8>,
%arg1: memref<2x8xi8>, %arg1: memref<2x8xi8>,
%arg2: memref<2x2xi32>) { %arg2: memref<2x2xi32>) {
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mlir/test/Integration/Dialect/Vector/CPU/AMX/test-tilezero-block.mlir

// RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate -mlir-to-llvmir | \ // RUN: mlir-translate -mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Note: To run this test, your CPU must support AMX. // Note: To run this test, your CPU must support AMX.
func.func @print(%arg0: memref<4x32xf32>) { func.func @print(%arg0: memref<4x32xf32>) {
%fu = arith.constant -1.0: f32 %fu = arith.constant -1.0: f32
%c0 = arith.constant 0: index %c0 = arith.constant 0: index
%c1 = arith.constant 1: index %c1 = arith.constant 1: index
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mlir/test/Integration/Dialect/Vector/CPU/AMX/test-tilezero.mlir

// RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate -mlir-to-llvmir | \ // RUN: mlir-translate -mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Note: To run this test, your CPU must support AMX. // Note: To run this test, your CPU must support AMX.
func.func @tilezero(%arg0: memref<?x?xi32>, %i: index, %j: index) { func.func @tilezero(%arg0: memref<?x?xi32>, %i: index, %j: index) {
%1 = amx.tile_zero : vector<16x16xi32> %1 = amx.tile_zero : vector<16x16xi32>
amx.tile_store %arg0[%i, %j], %1 : memref<?x?xi32>, vector<16x16xi32> amx.tile_store %arg0[%i, %j], %1 : memref<?x?xi32>, vector<16x16xi32>
return return
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mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-dot.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate --mlir-to-llvmir | \ // RUN: mlir-translate --mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="avx" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="avx" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() -> i32 { func.func @entry() -> i32 {
%i0 = arith.constant 0 : i32 %i0 = arith.constant 0 : i32
%i4 = arith.constant 4 : i32 %i4 = arith.constant 4 : i32
%a = arith.constant dense<[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]> : vector<8xf32> %a = arith.constant dense<[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]> : vector<8xf32>
%b = arith.constant dense<[9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0]> : vector<8xf32> %b = arith.constant dense<[9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0]> : vector<8xf32>
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mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-inline-asm-vector-avx512.mlir

// RUN: mlir-opt %s -convert-linalg-to-loops -convert-vector-to-scf='full-unroll=true' -lower-affine -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm='use-bare-ptr-memref-call-conv=1' -convert-arith-to-llvm -reconcile-unrealized-casts |\ // RUN: mlir-opt %s -convert-linalg-to-loops -convert-vector-to-scf='full-unroll=true' -lower-affine -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm='use-bare-ptr-memref-call-conv=1' -convert-arith-to-llvm -reconcile-unrealized-casts |\
// RUN: mlir-translate --mlir-to-llvmir |\ // RUN: mlir-translate --mlir-to-llvmir |\
// RUN: %lli --entry-function=entry --mattr="avx512f" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext |\ // RUN: %lli --entry-function=entry --mattr="avx512f" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext |\
// RUN: FileCheck %s // RUN: FileCheck %s
module { module {
// an array of 16 i32 of values [0..15] // an array of 16 i32 of values [0..15]
llvm.mlir.global private @const16( llvm.mlir.global private @const16(
dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : tensor<16 x i32>) dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : tensor<16 x i32>)
: !llvm.array<16 x i32> : !llvm.array<16 x i32>
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mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-mask-compress.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate --mlir-to-llvmir | \ // RUN: mlir-translate --mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="avx512bw" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="avx512bw" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() -> i32 { func.func @entry() -> i32 {
%i0 = arith.constant 0 : i32 %i0 = arith.constant 0 : i32
%a = arith.constant dense<[1., 0., 0., 2., 4., 3., 5., 7., 8., 1., 5., 5., 3., 1., 0., 7.]> : vector<16xf32> %a = arith.constant dense<[1., 0., 0., 2., 4., 3., 5., 7., 8., 1., 5., 5., 3., 1., 0., 7.]> : vector<16xf32>
%k = arith.constant dense<[1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0]> : vector<16xi1> %k = arith.constant dense<[1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0]> : vector<16xi1>
%r1 = x86vector.avx512.mask.compress %k, %a : vector<16xf32> %r1 = x86vector.avx512.mask.compress %k, %a : vector<16xf32>
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mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-rsqrt.mlir

// RUN: mlir-opt %s -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm | \ // RUN: mlir-opt %s -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm | \
// RUN: mlir-translate --mlir-to-llvmir | \ // RUN: mlir-translate --mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="avx" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="avx" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() -> i32 { func.func @entry() -> i32 {
%i0 = arith.constant 0 : i32 %i0 = arith.constant 0 : i32
%v = arith.constant dense<[0.125, 0.25, 0.5, 1.0, 2.0, 4.0, 8.0, 16.0]> : vector<8xf32> %v = arith.constant dense<[0.125, 0.25, 0.5, 1.0, 2.0, 4.0, 8.0, 16.0]> : vector<8xf32>
%r = x86vector.avx.rsqrt %v : vector<8xf32> %r = x86vector.avx.rsqrt %v : vector<8xf32>
// `rsqrt` may produce slightly different results on Intel and AMD machines: accept both results here. // `rsqrt` may produce slightly different results on Intel and AMD machines: accept both results here.
// CHECK: {{( 2.82[0-9]*, 1.99[0-9]*, 1.41[0-9]*, 0.99[0-9]*, 0.70[0-9]*, 0.49[0-9]*, 0.35[0-9]*, 0.24[0-9]* )}} // CHECK: {{( 2.82[0-9]*, 1.99[0-9]*, 1.41[0-9]*, 0.99[0-9]*, 0.70[0-9]*, 0.49[0-9]*, 0.35[0-9]*, 0.24[0-9]* )}}
vector.print %r : vector<8xf32> vector.print %r : vector<8xf32>
return %i0 : i32 return %i0 : i32
} }

mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-sparse-dot-product.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate --mlir-to-llvmir | \ // RUN: mlir-translate --mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="avx512bw,avx512vp2intersect" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="avx512bw,avx512vp2intersect" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// This test shows how to implement a sparse vector-vector dot product with // This test shows how to implement a sparse vector-vector dot product with
// AVX512. It uses vp2intersect, mask.compress and vector.contract to compute // AVX512. It uses vp2intersect, mask.compress and vector.contract to compute
// the dot product of two sparse HW vectors of 8 float64 elements ("segment"). // the dot product of two sparse HW vectors of 8 float64 elements ("segment").
// Each sparse vector is represented by an index memref (A or C) and by a data // Each sparse vector is represented by an index memref (A or C) and by a data
// memref (B or D), containing M or N elements. // memref (B or D), containing M or N elements.
// //
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mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-vp2intersect-i32.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-translate --mlir-to-llvmir | \ // RUN: mlir-translate --mlir-to-llvmir | \
// RUN: %lli --entry-function=entry --mattr="avx512bw,avx512vp2intersect" --dlopen=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: %lli --entry-function=entry --mattr="avx512bw,avx512vp2intersect" --dlopen=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Note: To run this test, your CPU must support AVX512 vp2intersect. // Note: To run this test, your CPU must support AVX512 vp2intersect.
func.func @entry() -> i32 { func.func @entry() -> i32 {
%i0 = arith.constant 0 : i32 %i0 = arith.constant 0 : i32
%i1 = arith.constant 1: i32 %i1 = arith.constant 1: i32
%i2 = arith.constant 2: i32 %i2 = arith.constant 2: i32
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mlir/test/Integration/Dialect/Vector/CPU/test-0-d-vectors.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @extract_element_0d(%a: vector<f32>) { func.func @extract_element_0d(%a: vector<f32>) {
%1 = vector.extractelement %a[] : vector<f32> %1 = vector.extractelement %a[] : vector<f32>
// CHECK: 42 // CHECK: 42
vector.print %1: f32 vector.print %1: f32
return return
} }
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mlir/test/Integration/Dialect/Vector/CPU/test-broadcast.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%i = arith.constant 2147483647: i32 %i = arith.constant 2147483647: i32
%l = arith.constant 9223372036854775807 : i64 %l = arith.constant 9223372036854775807 : i64
%f0 = arith.constant 0.0: f32 %f0 = arith.constant 0.0: f32
%f1 = arith.constant 1.0: f32 %f1 = arith.constant 1.0: f32
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mlir/test/Integration/Dialect/Vector/CPU/test-compress.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @compress16(%base: memref<?xf32>, func.func @compress16(%base: memref<?xf32>,
%mask: vector<16xi1>, %value: vector<16xf32>) { %mask: vector<16xi1>, %value: vector<16xf32>) {
%c0 = arith.constant 0: index %c0 = arith.constant 0: index
vector.compressstore %base[%c0], %mask, %value vector.compressstore %base[%c0], %mask, %value
: memref<?xf32>, vector<16xi1>, vector<16xf32> : memref<?xf32>, vector<16xi1>, vector<16xf32>
return return
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mlir/test/Integration/Dialect/Vector/CPU/test-constant-mask.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%0 = vector.constant_mask [4] : vector<8xi1> %0 = vector.constant_mask [4] : vector<8xi1>
vector.print %0 : vector<8xi1> vector.print %0 : vector<8xi1>
// CHECK: ( 1, 1, 1, 1, 0, 0, 0, 0 ) // CHECK: ( 1, 1, 1, 1, 0, 0, 0, 0 )
%1 = vector.constant_mask [1, 3] : vector<4x4xi1> %1 = vector.constant_mask [1, 3] : vector<4x4xi1>
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mlir/test/Integration/Dialect/Vector/CPU/test-contraction.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#dotp_accesses = [ #dotp_accesses = [
affine_map<(i) -> (i)>, affine_map<(i) -> (i)>,
affine_map<(i) -> (i)>, affine_map<(i) -> (i)>,
affine_map<(i) -> ()> affine_map<(i) -> ()>
] ]
#dotp_trait = { #dotp_trait = {
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mlir/test/Integration/Dialect/Vector/CPU/test-create-mask-v4i1.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// NOTE: This is similar to test-create-mask.mlir, but with a different length, // NOTE: This is similar to test-create-mask.mlir, but with a different length,
// because the v4i1 vector specifically exposed bugs in the LLVM backend. // because the v4i1 vector specifically exposed bugs in the LLVM backend.
func.func @entry() { func.func @entry() {
%c0 = arith.constant 0 : index %c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index %c1 = arith.constant 1 : index
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mlir/test/Integration/Dialect/Vector/CPU/test-create-mask.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%cneg1 = arith.constant -1 : index %cneg1 = arith.constant -1 : index
%c0 = arith.constant 0 : index %c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index %c1 = arith.constant 1 : index
%c2 = arith.constant 2 : index %c2 = arith.constant 2 : index
%c3 = arith.constant 3 : index %c3 = arith.constant 3 : index
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mlir/test/Integration/Dialect/Vector/CPU/test-expand.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @expand16(%base: memref<?xf32>, func.func @expand16(%base: memref<?xf32>,
%mask: vector<16xi1>, %mask: vector<16xi1>,
%pass_thru: vector<16xf32>) -> vector<16xf32> { %pass_thru: vector<16xf32>) -> vector<16xf32> {
%c0 = arith.constant 0: index %c0 = arith.constant 0: index
%e = vector.expandload %base[%c0], %mask, %pass_thru %e = vector.expandload %base[%c0], %mask, %pass_thru
: memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32> : memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-extract-strided-slice.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f0 = arith.constant 0.0: f32 %f0 = arith.constant 0.0: f32
%f1 = arith.constant 1.0: f32 %f1 = arith.constant 1.0: f32
%f2 = arith.constant 2.0: f32 %f2 = arith.constant 2.0: f32
%f3 = arith.constant 3.0: f32 %f3 = arith.constant 3.0: f32
%f4 = arith.constant 4.0: f32 %f4 = arith.constant 4.0: f32
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mlir/test/Integration/Dialect/Vector/CPU/test-flat-transpose-col.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=column-major \ // RUN: -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=column-major \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f0 = arith.constant 0.0: f64 %f0 = arith.constant 0.0: f64
%f1 = arith.constant 1.0: f64 %f1 = arith.constant 1.0: f64
%f2 = arith.constant 2.0: f64 %f2 = arith.constant 2.0: f64
%f3 = arith.constant 3.0: f64 %f3 = arith.constant 3.0: f64
%f4 = arith.constant 4.0: f64 %f4 = arith.constant 4.0: f64
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mlir/test/Integration/Dialect/Vector/CPU/test-flat-transpose-row.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=row-major \ // RUN: -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=row-major \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f0 = arith.constant 0.0: f64 %f0 = arith.constant 0.0: f64
%f1 = arith.constant 1.0: f64 %f1 = arith.constant 1.0: f64
%f2 = arith.constant 2.0: f64 %f2 = arith.constant 2.0: f64
%f3 = arith.constant 3.0: f64 %f3 = arith.constant 3.0: f64
%f4 = arith.constant 4.0: f64 %f4 = arith.constant 4.0: f64
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mlir/test/Integration/Dialect/Vector/CPU/test-fma.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f1 = arith.constant 1.0: f32 %f1 = arith.constant 1.0: f32
%f3 = arith.constant 3.0: f32 %f3 = arith.constant 3.0: f32
%f7 = arith.constant 7.0: f32 %f7 = arith.constant 7.0: f32
%v1 = vector.broadcast %f1 : f32 to vector<8xf32> %v1 = vector.broadcast %f1 : f32 to vector<8xf32>
%v3 = vector.broadcast %f3 : f32 to vector<8xf32> %v3 = vector.broadcast %f3 : f32 to vector<8xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-gather.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @gather8(%base: memref<?xf32>, %indices: vector<8xi32>, func.func @gather8(%base: memref<?xf32>, %indices: vector<8xi32>,
%mask: vector<8xi1>, %pass_thru: vector<8xf32>) -> vector<8xf32> { %mask: vector<8xi1>, %pass_thru: vector<8xf32>) -> vector<8xf32> {
%c0 = arith.constant 0: index %c0 = arith.constant 0: index
%g = vector.gather %base[%c0][%indices], %mask, %pass_thru %g = vector.gather %base[%c0][%indices], %mask, %pass_thru
: memref<?xf32>, vector<8xi32>, vector<8xi1>, vector<8xf32> into vector<8xf32> : memref<?xf32>, vector<8xi32>, vector<8xi1>, vector<8xf32> into vector<8xf32>
return %g : vector<8xf32> return %g : vector<8xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-index-vectors.mlir

// RUN: mlir-opt %s -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%c0 = arith.constant dense<[0, 1, 2, 3]>: vector<4xindex> %c0 = arith.constant dense<[0, 1, 2, 3]>: vector<4xindex>
%c1 = arith.constant dense<[0, 1]>: vector<2xindex> %c1 = arith.constant dense<[0, 1]>: vector<2xindex>
%c2 = arith.constant 2 : index %c2 = arith.constant 2 : index
%v1 = vector.broadcast %c0 : vector<4xindex> to vector<2x4xindex> %v1 = vector.broadcast %c0 : vector<4xindex> to vector<2x4xindex>
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mlir/test/Integration/Dialect/Vector/CPU/test-insert-strided-slice.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f1 = arith.constant 1.0: f32 %f1 = arith.constant 1.0: f32
%f2 = arith.constant 2.0: f32 %f2 = arith.constant 2.0: f32
%f3 = arith.constant 3.0: f32 %f3 = arith.constant 3.0: f32
%f4 = arith.constant 4.0: f32 %f4 = arith.constant 4.0: f32
%v1 = vector.broadcast %f1 : f32 to vector<4xf32> %v1 = vector.broadcast %f1 : f32 to vector<4xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-maskedload.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @maskedload16(%base: memref<?xf32>, %mask: vector<16xi1>, func.func @maskedload16(%base: memref<?xf32>, %mask: vector<16xi1>,
%pass_thru: vector<16xf32>) -> vector<16xf32> { %pass_thru: vector<16xf32>) -> vector<16xf32> {
%c0 = arith.constant 0: index %c0 = arith.constant 0: index
%ld = vector.maskedload %base[%c0], %mask, %pass_thru %ld = vector.maskedload %base[%c0], %mask, %pass_thru
: memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32> : memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32>
return %ld : vector<16xf32> return %ld : vector<16xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-maskedstore.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @maskedstore16(%base: memref<?xf32>, func.func @maskedstore16(%base: memref<?xf32>,
%mask: vector<16xi1>, %value: vector<16xf32>) { %mask: vector<16xi1>, %value: vector<16xf32>) {
%c0 = arith.constant 0: index %c0 = arith.constant 0: index
vector.maskedstore %base[%c0], %mask, %value vector.maskedstore %base[%c0], %mask, %value
: memref<?xf32>, vector<16xi1>, vector<16xf32> : memref<?xf32>, vector<16xi1>, vector<16xf32>
return return
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mlir/test/Integration/Dialect/Vector/CPU/test-matrix-multiply-col.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=column-major \ // RUN: -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=column-major \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f0 = arith.constant 0.0: f64 %f0 = arith.constant 0.0: f64
%f1 = arith.constant 1.0: f64 %f1 = arith.constant 1.0: f64
%f2 = arith.constant 2.0: f64 %f2 = arith.constant 2.0: f64
%f3 = arith.constant 3.0: f64 %f3 = arith.constant 3.0: f64
%f4 = arith.constant 4.0: f64 %f4 = arith.constant 4.0: f64
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mlir/test/Integration/Dialect/Vector/CPU/test-matrix-multiply-row.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=row-major \ // RUN: -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=row-major \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f0 = arith.constant 0.0: f64 %f0 = arith.constant 0.0: f64
%f1 = arith.constant 1.0: f64 %f1 = arith.constant 1.0: f64
%f2 = arith.constant 2.0: f64 %f2 = arith.constant 2.0: f64
%f3 = arith.constant 3.0: f64 %f3 = arith.constant 3.0: f64
%f4 = arith.constant 4.0: f64 %f4 = arith.constant 4.0: f64
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mlir/test/Integration/Dialect/Vector/CPU/test-outerproduct-f32.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!vector_type_A = vector<8xf32> !vector_type_A = vector<8xf32>
!vector_type_B = vector<8xf32> !vector_type_B = vector<8xf32>
!vector_type_C = vector<8x8xf32> !vector_type_C = vector<8x8xf32>
!vector_type_X = vector<2xf32> !vector_type_X = vector<2xf32>
!vector_type_Y = vector<3xf32> !vector_type_Y = vector<3xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-outerproduct-i64.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
!vector_type_A = vector<8xi64> !vector_type_A = vector<8xi64>
!vector_type_B = vector<8xi64> !vector_type_B = vector<8xi64>
!vector_type_C = vector<8x8xi64> !vector_type_C = vector<8x8xi64>
!vector_type_X = vector<2xi64> !vector_type_X = vector<2xi64>
!vector_type_Y = vector<3xi64> !vector_type_Y = vector<3xi64>
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mlir/test/Integration/Dialect/Vector/CPU/test-print-int.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// //
// Test various signless, signed, unsigned integer types. // Test various signless, signed, unsigned integer types.
// //
func.func @entry() { func.func @entry() {
%0 = arith.constant dense<[true, false, -1, 0, 1]> : vector<5xi1> %0 = arith.constant dense<[true, false, -1, 0, 1]> : vector<5xi1>
vector.print %0 : vector<5xi1> vector.print %0 : vector<5xi1>
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mlir/test/Integration/Dialect/Vector/CPU/test-reductions-f32-reassoc.mlir

// RUN: mlir-opt %s -convert-scf-to-cf \ // RUN: mlir-opt %s -convert-scf-to-cf \
// RUN: -convert-vector-to-llvm='reassociate-fp-reductions' \ // RUN: -convert-vector-to-llvm='reassociate-fp-reductions' \
// RUN: -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
// Construct test vector, numerically very stable. // Construct test vector, numerically very stable.
%f1 = arith.constant 1.0: f32 %f1 = arith.constant 1.0: f32
%f2 = arith.constant 2.0: f32 %f2 = arith.constant 2.0: f32
%f3 = arith.constant 3.0: f32 %f3 = arith.constant 3.0: f32
%v0 = vector.broadcast %f1 : f32 to vector<64xf32> %v0 = vector.broadcast %f1 : f32 to vector<64xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-reductions-f32.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
// Construct test vector. // Construct test vector.
%f1 = arith.constant 1.5: f32 %f1 = arith.constant 1.5: f32
%f2 = arith.constant 2.0: f32 %f2 = arith.constant 2.0: f32
%f3 = arith.constant 3.0: f32 %f3 = arith.constant 3.0: f32
%f4 = arith.constant 4.0: f32 %f4 = arith.constant 4.0: f32
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mlir/test/Integration/Dialect/Vector/CPU/test-reductions-f64-reassoc.mlir

// RUN: mlir-opt %s -convert-scf-to-cf \ // RUN: mlir-opt %s -convert-scf-to-cf \
// RUN: -convert-vector-to-llvm='reassociate-fp-reductions' \ // RUN: -convert-vector-to-llvm='reassociate-fp-reductions' \
// RUN: -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
// Construct test vector, numerically very stable. // Construct test vector, numerically very stable.
%f1 = arith.constant 1.0: f64 %f1 = arith.constant 1.0: f64
%f2 = arith.constant 2.0: f64 %f2 = arith.constant 2.0: f64
%f3 = arith.constant 3.0: f64 %f3 = arith.constant 3.0: f64
%v0 = vector.broadcast %f1 : f64 to vector<64xf64> %v0 = vector.broadcast %f1 : f64 to vector<64xf64>
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mlir/test/Integration/Dialect/Vector/CPU/test-reductions-f64.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
// Construct test vector. // Construct test vector.
%f1 = arith.constant 1.5: f64 %f1 = arith.constant 1.5: f64
%f2 = arith.constant 2.0: f64 %f2 = arith.constant 2.0: f64
%f3 = arith.constant 3.0: f64 %f3 = arith.constant 3.0: f64
%f4 = arith.constant 4.0: f64 %f4 = arith.constant 4.0: f64
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mlir/test/Integration/Dialect/Vector/CPU/test-reductions-i32.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
// Construct test vector. // Construct test vector.
%i1 = arith.constant 1: i32 %i1 = arith.constant 1: i32
%i2 = arith.constant 2: i32 %i2 = arith.constant 2: i32
%i3 = arith.constant 3: i32 %i3 = arith.constant 3: i32
%i4 = arith.constant 4: i32 %i4 = arith.constant 4: i32
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mlir/test/Integration/Dialect/Vector/CPU/test-reductions-i4.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%v = arith.constant dense<[-8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : vector<24xi4> %v = arith.constant dense<[-8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : vector<24xi4>
vector.print %v : vector<24xi4> vector.print %v : vector<24xi4>
// //
// Test vector: // Test vector:
// //
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mlir/test/Integration/Dialect/Vector/CPU/test-reductions-i64.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
// Construct test vector. // Construct test vector.
%i1 = arith.constant 1: i64 %i1 = arith.constant 1: i64
%i2 = arith.constant 2: i64 %i2 = arith.constant 2: i64
%i3 = arith.constant 3: i64 %i3 = arith.constant 3: i64
%i4 = arith.constant 4: i64 %i4 = arith.constant 4: i64
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mlir/test/Integration/Dialect/Vector/CPU/test-reductions-si4.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%v0 = arith.constant dense<[-8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7]> : vector<16xi4> %v0 = arith.constant dense<[-8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7]> : vector<16xi4>
%v = vector.bitcast %v0 : vector<16xi4> to vector<16xsi4> %v = vector.bitcast %v0 : vector<16xi4> to vector<16xsi4>
vector.print %v : vector<16xsi4> vector.print %v : vector<16xsi4>
// //
// Test vector: // Test vector:
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mlir/test/Integration/Dialect/Vector/CPU/test-reductions-ui4.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%v0 = arith.constant dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : vector<16xi4> %v0 = arith.constant dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : vector<16xi4>
%v = vector.bitcast %v0 : vector<16xi4> to vector<16xui4> %v = vector.bitcast %v0 : vector<16xi4> to vector<16xui4>
vector.print %v : vector<16xui4> vector.print %v : vector<16xui4>
// //
// Test vector: // Test vector:
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mlir/test/Integration/Dialect/Vector/CPU/test-scan.mlir

// RUN: mlir-opt %s -test-vector-scan-lowering -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -test-vector-scan-lowering -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f1 = arith.constant 1.0: f32 %f1 = arith.constant 1.0: f32
%f2 = arith.constant 2.0: f32 %f2 = arith.constant 2.0: f32
%f3 = arith.constant 3.0: f32 %f3 = arith.constant 3.0: f32
%f4 = arith.constant 4.0: f32 %f4 = arith.constant 4.0: f32
%f5 = arith.constant 5.0: f32 %f5 = arith.constant 5.0: f32
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mlir/test/Integration/Dialect/Vector/CPU/test-scatter.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @scatter8(%base: memref<?xf32>, func.func @scatter8(%base: memref<?xf32>,
%indices: vector<8xi32>, %indices: vector<8xi32>,
%mask: vector<8xi1>, %value: vector<8xf32>) { %mask: vector<8xi1>, %value: vector<8xf32>) {
%c0 = arith.constant 0: index %c0 = arith.constant 0: index
vector.scatter %base[%c0][%indices], %mask, %value vector.scatter %base[%c0][%indices], %mask, %value
: memref<?xf32>, vector<8xi32>, vector<8xi1>, vector<8xf32> : memref<?xf32>, vector<8xi32>, vector<8xi1>, vector<8xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-shape-cast.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f1 = arith.constant 1.0: f32 %f1 = arith.constant 1.0: f32
%f2 = arith.constant 2.0: f32 %f2 = arith.constant 2.0: f32
%f3 = arith.constant 3.0: f32 %f3 = arith.constant 3.0: f32
%f4 = arith.constant 4.0: f32 %f4 = arith.constant 4.0: f32
%f5 = arith.constant 5.0: f32 %f5 = arith.constant 5.0: f32
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mlir/test/Integration/Dialect/Vector/CPU/test-shuffle.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f1 = arith.constant 1.0: f32 %f1 = arith.constant 1.0: f32
%f2 = arith.constant 2.0: f32 %f2 = arith.constant 2.0: f32
%v1 = vector.broadcast %f1 : f32 to vector<2x4xf32> %v1 = vector.broadcast %f1 : f32 to vector<2x4xf32>
%v2 = vector.broadcast %f2 : f32 to vector<2x4xf32> %v2 = vector.broadcast %f2 : f32 to vector<2x4xf32>
vector.print %v1 : vector<2x4xf32> vector.print %v1 : vector<2x4xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-sparse-dot-matvec.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Illustrates an 8x8 Sparse Matrix x Vector implemented with only operations // Illustrates an 8x8 Sparse Matrix x Vector implemented with only operations
// of the vector dialect (and some std/scf). Essentially, this example performs // of the vector dialect (and some std/scf). Essentially, this example performs
// the following multiplication: // the following multiplication:
// //
// 0 1 2 3 4 5 6 7 // 0 1 2 3 4 5 6 7
// +------------------------+ // +------------------------+
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mlir/test/Integration/Dialect/Vector/CPU/test-sparse-saxpy-jagged-matvec.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Illustrates an 8x8 Sparse Matrix x Vector implemented with only operations // Illustrates an 8x8 Sparse Matrix x Vector implemented with only operations
// of the vector dialect (and some std/scf). Essentially, this example performs // of the vector dialect (and some std/scf). Essentially, this example performs
// the following multiplication: // the following multiplication:
// //
// 0 1 2 3 4 5 6 7 // 0 1 2 3 4 5 6 7
// +------------------------+ // +------------------------+
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mlir/test/Integration/Dialect/Vector/CPU/test-transfer-read-1d.mlir

// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// Test for special cases of 1D vector transfer ops. // Test for special cases of 1D vector transfer ops.
memref.global "private" @gv : memref<5x6xf32> = memref.global "private" @gv : memref<5x6xf32> =
dense<[[0. , 1. , 2. , 3. , 4. , 5. ], dense<[[0. , 1. , 2. , 3. , 4. , 5. ],
[10., 11., 12., 13., 14., 15.], [10., 11., 12., 13., 14., 15.],
[20., 21., 22., 23., 24., 25.], [20., 21., 22., 23., 24., 25.],
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mlir/test/Integration/Dialect/Vector/CPU/test-transfer-read-2d.mlir

// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
memref.global "private" @gv : memref<3x4xf32> = dense<[[0. , 1. , 2. , 3. ], memref.global "private" @gv : memref<3x4xf32> = dense<[[0. , 1. , 2. , 3. ],
[10., 11., 12., 13.], [10., 11., 12., 13.],
[20., 21., 22., 23.]]> [20., 21., 22., 23.]]>
// Vector load. // Vector load.
func.func @transfer_read_2d(%A : memref<?x?xf32>, %base1: index, %base2: index) { func.func @transfer_read_2d(%A : memref<?x?xf32>, %base1: index, %base2: index) {
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mlir/test/Integration/Dialect/Vector/CPU/test-transfer-read-3d.mlir

// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true lower-permutation-maps=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @transfer_read_3d(%A : memref<?x?x?x?xf32>, func.func @transfer_read_3d(%A : memref<?x?x?x?xf32>,
%o: index, %a: index, %b: index, %c: index) { %o: index, %a: index, %b: index, %c: index) {
%fm42 = arith.constant -42.0: f32 %fm42 = arith.constant -42.0: f32
%f = vector.transfer_read %A[%o, %a, %b, %c], %fm42 %f = vector.transfer_read %A[%o, %a, %b, %c], %fm42
: memref<?x?x?x?xf32>, vector<2x5x3xf32> : memref<?x?x?x?xf32>, vector<2x5x3xf32>
vector.print %f: vector<2x5x3xf32> vector.print %f: vector<2x5x3xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-transfer-read.mlir

// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @transfer_read_1d(%A : memref<?xf32>, %base: index) { func.func @transfer_read_1d(%A : memref<?xf32>, %base: index) {
%fm42 = arith.constant -42.0: f32 %fm42 = arith.constant -42.0: f32
%f = vector.transfer_read %A[%base], %fm42 %f = vector.transfer_read %A[%base], %fm42
{permutation_map = affine_map<(d0) -> (d0)>} : {permutation_map = affine_map<(d0) -> (d0)>} :
memref<?xf32>, vector<13xf32> memref<?xf32>, vector<13xf32>
vector.print %f: vector<13xf32> vector.print %f: vector<13xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-transfer-to-loops.mlir

// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext,%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext,%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext,%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
#map0 = affine_map<(d0, d1) -> (d1, d0)> #map0 = affine_map<(d0, d1) -> (d1, d0)>
#map1 = affine_map<(d0, d1) -> (d1)> #map1 = affine_map<(d0, d1) -> (d1)>
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
func.func @alloc_2d_filled_f32(%arg0: index, %arg1: index) -> memref<?x?xf32> { func.func @alloc_2d_filled_f32(%arg0: index, %arg1: index) -> memref<?x?xf32> {
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mlir/test/Integration/Dialect/Vector/CPU/test-transfer-write.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @transfer_write16_inbounds_1d(%A : memref<?xf32>, %base: index) { func.func @transfer_write16_inbounds_1d(%A : memref<?xf32>, %base: index) {
%f = arith.constant 16.0 : f32 %f = arith.constant 16.0 : f32
%v = vector.splat %f : vector<16xf32> %v = vector.splat %f : vector<16xf32>
vector.transfer_write %v, %A[%base] vector.transfer_write %v, %A[%base]
{permutation_map = affine_map<(d0) -> (d0)>, in_bounds = [true]} {permutation_map = affine_map<(d0) -> (d0)>, in_bounds = [true]}
: vector<16xf32>, memref<?xf32> : vector<16xf32>, memref<?xf32>
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mlir/test/Integration/Dialect/Vector/CPU/test-transpose.mlir

// RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \ // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_c_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
func.func @entry() { func.func @entry() {
%f0 = arith.constant 0.0: f32 %f0 = arith.constant 0.0: f32
%f1 = arith.constant 1.0: f32 %f1 = arith.constant 1.0: f32
%f2 = arith.constant 2.0: f32 %f2 = arith.constant 2.0: f32
%f3 = arith.constant 3.0: f32 %f3 = arith.constant 3.0: f32
%f4 = arith.constant 4.0: f32 %f4 = arith.constant 4.0: f32
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mlir/test/Integration/Dialect/Vector/CPU/test-vector-distribute.mlir

// RUN: mlir-opt %s -pass-pipeline="func.func(test-vector-to-forloop,convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \ // RUN: mlir-opt %s -pass-pipeline="func.func(test-vector-to-forloop,convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | \
// RUN: mlir-cpu-runner -e main -entry-point-result=void \ // RUN: mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | mlir-cpu-runner -e main \ // RUN: mlir-opt %s -pass-pipeline="func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,convert-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts" | mlir-cpu-runner -e main \
// RUN: -entry-point-result=void \ // RUN: -entry-point-result=void \
// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext | \ // RUN: -shared-libs=%linalg_test_lib_dir/libmlir_runner_utils%shlibext | \
// RUN: FileCheck %s // RUN: FileCheck %s
// RUN: mlir-opt %s -pass-pipeline="func.func(test-vector-to-forloop)" | FileCheck %s -check-prefix=TRANSFORM // RUN: mlir-opt %s -pass-pipeline="func.func(test-vector-to-forloop)" | FileCheck %s -check-prefix=TRANSFORM
func.func private @printMemrefF32(memref<*xf32>) func.func private @printMemrefF32(memref<*xf32>)
func.func @alloc_1d_filled_inc_f32(%arg0: index, %arg1: f32) -> memref<?xf32> { func.func @alloc_1d_filled_inc_f32(%arg0: index, %arg1: f32) -> memref<?xf32> {
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