101 Commits

Author SHA1 Message Date
Aart Bik
657f60a07b [mlir][vector] add support for printing f16 and bf16
Love or hate it, but the vector.print operation was the very
first operation that actually made "end-to-end" CHECK integration
testing possible for MLIR. This revision adds support for
the -until recently- less common but important floating-point
types f16 and bf16.

This will become useful for accelerator specific testing (e.g. NVidia GPUs)

Reviewed By: wrengr

Differential Revision: https://reviews.llvm.org/D145207
2023-03-03 08:58:25 -08:00
Benjamin Chetioui
55fd1a05b9 [mlir][NFC] Address filecheck_lint findings in Vector/CPU/test-broadcast.mlir.
Differential Revision: https://reviews.llvm.org/D144972
2023-03-01 08:18:28 +00:00
Markus Böck
9048ea28da Reland "[mlir] Make the vast majority of intgration and runner tests work on Windows"
This reverts commit 5561e174117ff395d65b6978d04b62c1a1275138

The logic was moved from cmake into lit fixing the issue that lead to the revert and potentially others with multi-config cmake generators

Differential Revision: https://reviews.llvm.org/D143925
2023-02-15 19:14:43 +01:00
Aart Bik
5561e17411 Revert "[mlir] Make the vast majority of integration and runner tests work on Windows"
This reverts commit 161b9d741a3c25f7bd79620598c5a2acf3f0f377.

REASON:

cmake --build . --target check-mlir-integration

Failed Tests (186):
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-addi-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-cmpi-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-compare-results-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-constants-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-max-min-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-muli-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-shli-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-shrsi-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-shrui-i16.mlir
  MLIR :: Integration/Dialect/Async/CPU/microbench-linalg-async-parallel-for.mlir
  MLIR :: Integration/Dialect/Async/CPU/microbench-scf-async-parallel-for.mlir
  MLIR :: Integration/Dialect/Async/CPU/test-async-parallel-for-1d.mlir
  MLIR :: Integration/Dialect/Async/CPU/test-async-parallel-for-2d.mlir
  MLIR :: Integration/Dialect/Complex/CPU/correctness.mlir
  MLIR :: Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm-vector.mlir
  MLIR :: Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm.mlir
  MLIR :: Integration/Dialect/LLVMIR/CPU/test-vector-reductions-fp.mlir
  MLIR :: Integration/Dialect/LLVMIR/CPU/test-vector-reductions-int.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/matmul-vs-matvec.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/rank-reducing-subview.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-collapse-tensor.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-1d-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-1d-nwc-wcf-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-2d-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-2d-nhwc-hwcf-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-3d-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-3d-ndhwc-dhwcf-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-elementwise.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-expand-tensor.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-one-shot-bufferize.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-padtensor.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-subtensor-insert-multiple-uses.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-subtensor-insert.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-tensor-e2e.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-tensor-matmul.mlir
  MLIR :: Integration/Dialect/Memref/cast-runtime-verification.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/concatenate.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/dense_output.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/dense_output_bf16.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_cast.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_codegen_dim.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_codegen_foreach.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_complex32.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_complex64.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_complex_ops.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_constant_to_sparse_tensor.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_1d_nwc_wcf.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_2d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_2d_nhwc_hwcf.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_3d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_3d_ndhwc_dhwcf.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_dyn.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_ptr.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2sparse.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_dot.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_expand.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_file_io.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_filter_conv2d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_flatten.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_foreach_slices.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_index.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_insert_1d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_insert_2d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_insert_3d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_matmul.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_matrix_ops.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_mttkrp.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_out_mult_elt.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_out_reduction.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_out_simple.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_pack.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_quantized_matmul.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_re_im.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reduce_custom.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reduce_custom_prod.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reductions.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reductions_prod.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_rewrite_push_back.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_rewrite_sort.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_rewrite_sort_coo.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sampled_matmul.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sampled_mm_fusion.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_scale.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_scf_nested.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_select.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sign.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_storage.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_tanh.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_tensor_mul.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_tensor_ops.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_transpose.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_unary.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_vector_ops.mlir
  MLIR :: Integration/Dialect/SparseTensor/python/test_SDDMM.py
  MLIR :: Integration/Dialect/SparseTensor/python/test_SpMM.py
  MLIR :: Integration/Dialect/SparseTensor/python/test_elementwise_add_sparse_output.py
  MLIR :: Integration/Dialect/SparseTensor/python/test_output.py
  MLIR :: Integration/Dialect/SparseTensor/python/test_stress.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_MTTKRP.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_SDDMM.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_SpMM.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_SpMV.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_Tensor.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_scalar_tensor_algebra.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_simple_tensor_algebra.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_tensor_complex.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_tensor_types.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_tensor_unary_ops.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_true_dense_tensor_algebra.py
  MLIR :: Integration/Dialect/SparseTensor/taco/unit_test_tensor_core.py
  MLIR :: Integration/Dialect/SparseTensor/taco/unit_test_tensor_io.py
  MLIR :: Integration/Dialect/SparseTensor/taco/unit_test_tensor_utils.py
  MLIR :: Integration/Dialect/Standard/CPU/test-ceil-floor-pos-neg.mlir
  MLIR :: Integration/Dialect/Standard/CPU/test_subview.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-mulf-full.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-mulf.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-muli-ext.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-muli-full.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-muli.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-tilezero-block.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-tilezero.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-dot.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-inline-asm-vector-avx512.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-mask-compress.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-rsqrt.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-sparse-dot-product.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-vp2intersect-i32.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-0-d-vectors.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-broadcast.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-compress.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-constant-mask.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-contraction.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-create-mask-v4i1.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-create-mask.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-expand.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-extract-strided-slice.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-flat-transpose-col.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-flat-transpose-row.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-fma.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-gather.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-index-vectors.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-insert-strided-slice.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-maskedload.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-maskedstore.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-matrix-multiply-col.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-matrix-multiply-row.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-outerproduct-f32.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-outerproduct-i64.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-print-int.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-realloc.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-f32-reassoc.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-f32.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-f64-reassoc.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-f64.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-i32.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-i4.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-i64.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-si4.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-ui4.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-scan.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-scatter.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-shape-cast.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-shuffle.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-sparse-dot-matvec.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-sparse-saxpy-jagged-matvec.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-read-1d.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-read-2d.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-read-3d.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-read.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-to-loops.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-write.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transpose.mlir

Testing Time: 0.29s
  Unsupported:  31
  Passed     :   5
  Failed     : 186

Differential Revision: https://reviews.llvm.org/D143970
2023-02-13 18:30:52 -08:00
Markus Böck
161b9d741a [mlir] Make the vast majority of integration and runner tests work on Windows
This patch contains the changes required to make the vast majority of integration and runner tests run on Windows.
Historically speaking, the JIT support for Windows has been lacking behind, but recent versions of ORC JIT have now caught up and works for basically all examples in repo.

Sadly due to these tests previously not working on Windows, basically all of them are making unix-like assumptions about things like filenames, paths, shell syntax etc.
This patch fixes all these issues in one big swoop and enables Windows support for the vast majority of integration tests.

More specifically, following changes had to be done:
* The various JIT runners used paths to the runtime libraries that assumed a Unix toolchain layout and filenames. I abstracted the specific path and filename of these runtime libraries away by making the paths to the runtime libraries be passed from cmake into lit. This now also allows a much more convenient syntax: `--shared-libs=%mlir_c_runner_utils` instead of `--shared-libs=%mlir_lib_dir/lib/libmlir_c_runner_utils%shlibext`
* Some tests using python set environment variables using the `ENV=VALUE cmd` format. This works on Unix, but on Windows it has to prefixed using `env ENV=VALUE cmd`
* Some tests used C functions that are simply not available or exported on Windows (`fabsf`, `aligned_alloc`). These tests have either been adjusted or explicitly marked as `UNSUPPORTED`

Some tests remain disabled on Windows as before:
* In SparseTensor some tests have non-trivial logic for finding the runtime libraries which seems to be required for the use of emulators. I do not have the time to port these so I simply kept them disabled
* Some tests requiring special hardware which I simply cannot test remain disabled on Windows. These include usage of AVX512 or AMX

The tests for `mlir-vulkan-runner` and `mlir-spirv-runner` all work now as well and so do the vast majority of `mlir-cpu-runner`.

Differential Revision: https://reviews.llvm.org/D143925
2023-02-13 22:24:20 +01:00
Quentin Colombet
cb4ccd38fa [mlir][Conversion] Rename the MemRefToLLVM pass
Since the recent MemRef refactoring that centralizes the lowering of
complex MemRef operations outside of the conversion framework, the
MemRefToLLVM pass doesn't directly convert these complex operations.

Instead, to fully convert the whole MemRef dialect space, MemRefToLLVM
needs to run after `expand-strided-metadata`.

Make this more obvious by changing the name of the pass and the option
associated with it from `convert-memref-to-llvm` to
`finalize-memref-to-llvm`.
The word "finalize" conveys that this pass needs to run after something
else and that something else is documented in its tablegen description.

This is a follow-up patch related to the conversation at:
https://discourse.llvm.org/t/psa-you-need-to-run-expand-strided-metadata-before-memref-to-llvm-now/66956/14

Differential Revision: https://reviews.llvm.org/D142463
2023-01-27 09:10:10 +00:00
Aart Bik
f6b87c0029 [asan] fix two memory leaks in integration tests
Note that I did not track why this started failing exactly,
which is why I CC Matthias on this fix. But at least we run
asan clean again for the whole suite after this change.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D142496
2023-01-24 12:35:34 -08:00
Thomas Raoux
6dc9725471 [mlir][vector] Fix lowering of permutation maps for transfer_write op
The lowering of transfer write permutation maps didn't match the op definition:
93ccccb00d/mlir/include/mlir/Dialect/Vector/IR/VectorOps.td (L1476)

Fix the lowering and add a case to the integration test in
order to enforce the correct semantic.

Differential Revision: https://reviews.llvm.org/D141801
2023-01-17 17:04:04 +00:00
Quentin Colombet
786cbb09ed Re-apply "[mlir][MemRefToLLVM] Remove the code for lowering subview"
This reverts commit d0650d108929985760d536d59e9927838dccc9b8.

Original commit message:
Subviews are supposed to be expanded before we hit the lowering
code.
The expansion is done with the pass called
expand-strided-metadata.

Add a test that demonstrate how these passes can be linked up to achieve
the desired lowering.

This patch is NFC in spirit but not in practice because `subview` gets
lowered into `reinterpret_cast(extract_strided_metadata, <some math>)`
which lowers in two memref descriptors (one for `reinterpert_cast` and
one for `extract_strided_metadata`), which creates some noise of the
form: `extractvalue(unrealized_cast(extractvalue[0]))[0]` that is
currently not simplified within MLIR but that is really just noop in
that case.

Differential Revision: https://reviews.llvm.org/D136377
2022-12-02 15:26:58 +00:00
Diego Caballero
eb7e2998d1 Reland "[mlir][Vector] Re-define masking semantics in vector.transfer ops""
This relands commit 847b5f82a4a34218bf16d6f83f1b7c32df3117ba.

Differential Revision: https://reviews.llvm.org/D138079
2022-11-29 03:36:54 +00:00
Diego Caballero
f6d90055fd [mlir][Vector] Remove 'lower-permutation-maps' option from VectorToSCF
This patch is part of a larger simplification effort of vector transfer
operations. It removes the flag `lower-permutation-maps` from
VectorToSCF conversion and enables the lowering of permutation maps
by default. This means that VectorToSCF will always lower permutation
maps to independent broadcast/transpose operations before lowering
vector operations to SCF.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D138742
2022-11-28 23:56:43 +00:00
Hanhan Wang
0a1569a400 [mlir][NFC] Remove trailing whitespaces from *.td and *.mlir files.
This is generated by running

```
sed --in-place 's/[[:space:]]\+$//' mlir/**/*.td
sed --in-place 's/[[:space:]]\+$//' mlir/**/*.mlir
```

Reviewed By: rriddle, dcaballe

Differential Revision: https://reviews.llvm.org/D138866
2022-11-28 15:26:30 -08:00
rkayaith
13bd410962 [mlir][Pass] Include anchor op in -pass-pipeline
In D134622 the printed form of a pass manager is changed to include the
name of the op that the pass manager is anchored on. This updates the
`-pass-pipeline` argument format to include the anchor op as well, so
that the printed form of a pipeline can be directly passed to
`-pass-pipeline`. In most cases this requires updating
`-pass-pipeline='pipeline'` to
`-pass-pipeline='builtin.module(pipeline)'`.

This also fixes an outdated assert that prevented running a
`PassManager` anchored on `'any'`.

Reviewed By: rriddle

Differential Revision: https://reviews.llvm.org/D134900
2022-11-03 11:36:12 -04:00
Andrzej Warzynski
dd109f6159 [mlir][sve] Canonicalise MLIR_RUN_ARM_SVE_TESTS
Similarly to other CMake variables used to configure LIT tests, this
patch makes sure that MLIR_RUN_ARM_SVE_TESTS is canonicalised. The
corresponding LIT configuration is updated accordingly.

Differential Revision: https://reviews.llvm.org/D136967
2022-10-28 21:13:43 +00:00
bixia1
9f13b9346b [mlir][memref] Add realloc op.
Add memref.realloc and canonicalization of the op. Add conversion patterns for
lowering the op to LLVM using unaligned alloc or aligned alloc based on the
conversion option.

Add filecheck tests for parsing and converting the op. Add an integration test.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D133424
2022-09-21 08:04:00 -07:00
Alex Zinenko
f3fae035c7 [mlir] use strided layout in structured codegen-related tests
All relevant operations have been switched to primarily use the strided
layout, but still support the affine map layout. Update the relevant
tests to use the strided format instead for compatibility with how ops
now print by default.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D134045
2022-09-17 08:11:28 +02:00
Thomas Raoux
54db8cc7b1 [mlir][vector] Remove ExtractMap/InsertMap operations
As discussed on discourse: https://discourse.llvm.org/t/vector-vector-distribution-large-vector-to-small-vector/1983/22
removing insert_map/extract_map op as vector distribution now uses
warp_execute_on_lane_0 op.

Differential Revision: https://reviews.llvm.org/D134000
2022-09-16 17:41:26 +00:00
Christian Sigg
0f2ec35691 [MLIR] Switch lit tests to %mlir_lib_dir and %mlir_src_dir replacements.
The old replacements will be removed soon:
- `%linalg_test_lib_dir`
- `%cuda_wrapper_library_dir`
- `%spirv_wrapper_library_dir`
- `%vulkan_wrapper_library_dir`
- `%mlir_runner_utils_dir`
- `%mlir_integration_test_dir`

Reviewed By: herhut

Differential Revision: https://reviews.llvm.org/D133270
2022-09-06 12:34:14 +02:00
Christian Sigg
f43c81470b [MLIR] Single lit config attribute for CMAKE_LIBRARY_OUTPUT_DIRECTORY
Replace the following config attributes with `mlir_lib_dir`:
- `mlir_runner_utils_dir`
- `linalg_test_lib_dir`
- `spirv_wrapper_library_dir`
- `vulkan_wrapper_library_dir`
- `mlir_integration_test_dir`

I'm going to clean up substitutions in separate changes.

Reviewed By: aartbik, mehdi_amini

Differential Revision: https://reviews.llvm.org/D133217
2022-09-03 16:04:07 +02:00
Alex Zinenko
519847fefc [mlir] materialize strided memref layout as attribute
Introduce a new attribute to represent the strided memref layout. Strided
layouts are omnipresent in code generation flows and are the only kind of
layouts produced and supported by a half of operation in the memref dialect
(view-related, shape-related). However, they are internally represented as
affine maps that require a somewhat fragile extraction of the strides from the
linear form that also comes with an overhead. Furthermore, textual
representation of strided layouts as affine maps is difficult to read: compare
`affine_map<(d0, d1, d2)[s0, s1] -> (d0*32 + d1*s0 + s1 + d2)>` with
`strides: [32, ?, 1], offset: ?`. While a rudimentary support for parsing a
syntactically sugared version of the strided layout has existed in the codebase
for a long time, it does not go as far as this commit to make the strided
layout a first-class attribute in the IR.

This introduces the attribute and updates the tests that using the pre-existing
sugared form to use the new attribute instead. Most memref created
programmatically, e.g., in passes, still use the affine form with further
extraction of strides and will be updated separately.

Update and clean-up the memref type documentation that has gotten stale and has
been referring to the details of affine map composition that are long gone.

See https://discourse.llvm.org/t/rfc-materialize-strided-memref-layout-as-an-attribute/64211.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D132864
2022-08-30 17:19:58 +02:00
Nicolas Vasilache
db6f8ebe06 [mlir][Vector] Support 0-D vectors in ShuffleOp
Co-authored-by: Michal Terepeta <michalt@google.com>

Reviewed-by: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D115744
2022-08-29 00:39:57 -07:00
Nicolas Vasilache
6e81eae2f7 [mlir][Vector] Support 0-D vectors in TransposeOp
Co-authored-by: Michal Terepeta <michalt@google.com>

Reviewed-by: ftynse

Differential Revision: https://reviews.llvm.org/D115743
2022-08-26 03:40:21 -07:00
Michal Terepeta
ab45a4329b [mlir][Vector] Support 0-D vectors in FMAOp
Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D115742
2022-08-24 08:49:58 -07:00
Güray Özen
85882e7d64 [mlir][Vector] Support 0-D vectors in ReductionOp
This commit adds support for 0-D vectors in ReductionOp.

Reviewed By: nicolasvasilache, dcaballe

Differential Revision: https://reviews.llvm.org/D131896
2022-08-18 09:12:47 +00:00
River Riddle
a6cef03f66 [mlir] Remove the type keyword from type alias definitions
This was carry over from LLVM IR where the alias definition can
be ambiguous, but MLIR type aliases have no such problems.
Having the `type` keyword is superfluous and doesn't add anything.
This commit drops it, which also nicely aligns with the syntax for
attribute aliases (which doesn't have a keyword).

Differential Revision: https://reviews.llvm.org/D125501
2022-05-16 13:54:02 -07:00
Mehdi Amini
25cd6fba98 Fix MLIR integration test after a8308020 (func. prefix is required bythe parser now) 2022-05-07 09:09:24 +00:00
Stella Stamenova
d4555698f8 [mlir] Fix the names of exported functions
The names of the functions that are supposed to be exported do not match the implementations. This is due in part to cac7aabbd8.

This change makes the implementations and declarations match and adds a couple missing declarations.

The new names follow the pattern of the existing `verify` functions where the prefix is maintained as `_mlir_ciface_` but the suffix follows the new naming convention.

Reviewed By: rriddle

Differential Revision: https://reviews.llvm.org/D124891
2022-05-05 13:46:15 -07:00
River Riddle
87db8e4439 [mlir][NFC] Update textual references of func to func.func in Integration tests
The special case parsing of `func` operations is being removed.
2022-04-20 22:17:29 -07:00
Arthur Eubanks
7ccd026cf2 Reland [mlir] Remove uses of LLVM's legacy pass manager
Use the new pass manager.

This also removes the ability to run arbitrary sets of passes. Not sure if this functionality is used, but it doesn't seem to be tested.

No need to initialize passes outside of constructing the PassBuilder with the new pass manager.

Reland: Fixed custom calls to `-lower-matrix-intrinsics` in integration tests by replacing them with `-O0 -enable-matrix`.

Reviewed By: mehdi_amini

Differential Revision: https://reviews.llvm.org/D123425
2022-04-11 16:53:32 -07:00
Javier Setoain
ccb54d5b42 [mlir][Vector] Add integration tests for ArmSVE
In order to run these integration tests, it is required access to an
SVE-enabled CPU or and emulator with SVE support. In case of using
an emulator, aarch64 versions of lli and the MLIR C Runner Utils Library
are also required.

Differential Revision: https://reviews.llvm.org/D104517
2022-03-25 13:21:27 +00:00
River Riddle
3655069234 [mlir] Move the Builtin FuncOp to the Func dialect
This commit moves FuncOp out of the builtin dialect, and into the Func
dialect. This move has been planned in some capacity from the moment
we made FuncOp an operation (years ago). This commit handles the
functional aspects of the move, but various aspects are left untouched
to ease migration: func::FuncOp is re-exported into mlir to reduce
the actual API churn, the assembly format still accepts the unqualified
`func`. These temporary measures will remain for a little while to
simplify migration before being removed.

Differential Revision: https://reviews.llvm.org/D121266
2022-03-16 17:07:03 -07:00
River Riddle
47f175b09b [mlir] Update FuncOp conversion passes to Pass/InterfacePass<FunctionOpInterface>
These passes generally don't rely on any special aspects of FuncOp, and moving allows
for these passes to be used in many more situations. The passes that obviously weren't
relying on invariants guaranteed by a "function" were updated to be generic pass, the
rest were updated to be FunctionOpinterface InterfacePasses.

The test updates are NFC switching from implicit nesting (-pass -pass2) form to
the -pass-pipeline form (generic passes do not implicitly nest as op-specific passes do).

Differential Revision: https://reviews.llvm.org/D121190
2022-03-08 12:25:32 -08:00
River Riddle
5a7b919409 [mlir][NFC] Rename StandardToLLVM to FuncToLLVM
The current StandardToLLVM conversion patterns only really handle
the Func dialect. The pass itself adds patterns for Arithmetic/CFToLLVM, but
those should be/will be split out in a followup. This commit focuses solely
on being an NFC rename.

Aside from the directory change, the pattern and pass creation API have been renamed:
 * populateStdToLLVMFuncOpConversionPattern -> populateFuncToLLVMFuncOpConversionPattern
 * populateStdToLLVMConversionPatterns -> populateFuncToLLVMConversionPatterns
 * createLowerToLLVMPass -> createConvertFuncToLLVMPass

Differential Revision: https://reviews.llvm.org/D120778
2022-03-07 11:25:23 -08:00
Matthias Springer
fe0bf7d469 [mlir][vector][NFC] Use CombiningKindAttr instead of StringAttr
This makes the op consistent with other ops in vector dialect.

Differential Revision: https://reviews.llvm.org/D119343
2022-02-10 19:13:29 +09:00
River Riddle
ace01605e0 [mlir] Split out a new ControlFlow dialect from Standard
This dialect is intended to model lower level/branch based control-flow constructs. The initial set
of operations are: AssertOp, BranchOp, CondBranchOp, SwitchOp; all split out from the current
standard dialect.

See https://discourse.llvm.org/t/standard-dialect-the-final-chapter/6061

Differential Revision: https://reviews.llvm.org/D118966
2022-02-06 14:51:16 -08:00
River Riddle
6a8ba3186e [mlir] Split std.splat into tensor.splat and vector.splat
This is part of the larger effort to split the standard dialect. This will also allow for pruning some
additional dependencies on Standard (done in a followup).

Differential Revision: https://reviews.llvm.org/D118202
2022-02-02 14:45:12 -08:00
Nicolas Vasilache
31b7f8857f [mlir][vector][integration] Reactivate LLI in vector integration test.
The test introduced in https://reviews.llvm.org/D118006 was missing a return and would
introduce a non-0 return which would fail tests.
2022-02-01 08:00:50 -05:00
Nicolas Vasilache
c2fa5ff5ad Temporarily disable LLI to investigate weird non 0 error code
Somehow the test introduced in https://reviews.llvm.org/D118006 produces the expected result but running
through lli with Intel SDE activated sneaks in an error code 2 (before this commit) or an error code 10
(after this commit).

The test as is is still meaningful in that the LLVMIR generation would crash if the `elementtype` is set
improperly.

Still, this should run with lli turned on.
2022-02-01 07:24:49 -05:00
Nicolas Vasilache
42398b5142 [mlir][LLVM] Add support for operand_attrs to InlineAsmOp
This revision adds enough support to allow InlineAsmOp to work properly with indirect memory constraints "*m".
These require an explicit "elementtype" TypeAttr on the operands to pass LLVM verification and need to be provided.

Reviewed By: bkramer

Differential Revision: https://reviews.llvm.org/D118006
2022-02-01 05:56:14 -05:00
Matthias Springer
dab72a35e9 [mlir][bufferize] Clean up remaining references to tensor-constant-bufferize 2022-01-31 05:02:11 +09:00
harsh
80e0bf1af1 Add vector.scan op
This patch adds the vector.scan op which computes the
scan for a given n-d vector. It requires specifying the operator,
the identity element and whether the scan is inclusive or
exclusive.

TEST: Added test in ops.mlir

Reviewed By: ThomasRaoux

Differential Revision: https://reviews.llvm.org/D117171
2022-01-28 20:07:57 +00:00
Aart Bik
11fb049954 [mlir][amx] add a full tile matrix mult integral example to integration tests
Reviewed By: dcaballe

Differential Revision: https://reviews.llvm.org/D118292
2022-01-26 17:10:01 -08:00
Aart Bik
19f67ee29e [mlir][amx] fix some whitespace issues in AMX tests
Reviewed By: dcaballe

Differential Revision: https://reviews.llvm.org/D118289
2022-01-26 16:00:03 -08:00
Mehdi Amini
7ebd22c504 Revert "[mlir][LLVM] Add support for operand_attrs to InlineAsmOp"
This reverts commit e6ce2c0b8d5f8253791bf87145669c58328c30db.

The test is failing in CI right now.
2022-01-26 23:59:24 +00:00
Aart Bik
a5257ae277 [mlir][amx] add a full tile matrix mult example to integration tests
Rationale:
Demonstrates the maximum tile size allowed for the f32 <= bf16 x bf16 op

Reviewed By: dcaballe

Differential Revision: https://reviews.llvm.org/D118277
2022-01-26 14:13:30 -08:00
Nicolas Vasilache
e6ce2c0b8d [mlir][LLVM] Add support for operand_attrs to InlineAsmOp
This revision adds enough support to allow InlineAsmOp to work properly with indirect memory constraints "*m".
These require an explicit "elementtype" TypeAttr on the operands to pass LLVM verification and need to be provided.

Reviewed By: bkramer

Differential Revision: https://reviews.llvm.org/D118006
2022-01-26 07:42:35 -05:00
Sergei Grechanik
5abf116322 [mlir][vector] Allow values outside of [0; dim-size] in create_mask
This commits explicitly states that negative values and values exceeding
vector dimensions are allowed in vector.create_mask (but not in
vector.constant_mask). These values are now truncated when
canonicalizing vector.create_mask to vector.constant_mask.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D116069
2022-01-20 09:34:42 -08:00
Nicolas Vasilache
408553dd96 [mlir][Vector] Support 0-D vectors in CreateMaskOp
The 0-D case gets lowered in almost the same way that the 1-D case does
in VectorCreateMaskOpConversion. I also had to slightly update the
verifier for the op to always require exactly 1 operand in the 0-D case.

Depends On D115220

Reviewed by: ftynse

Differential revision: https://reviews.llvm.org/D115221
2021-12-12 13:32:29 +00:00
Michal Terepeta
a0c930d312 [mlir][Vector] Support 0-D vectors in CmpIOp
Following the example of `VectorOfAnyRankOf`, I've done a few changes in the
`.td` files to help with adding the support for the 0-D case gradually.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D115220
2021-12-12 13:28:26 +00:00
Michal Terepeta
caf89c0db6 [mlir][Vector] Support 0-D vectors in ConstantMaskOp
To support creating both a mask with just a single `true` and `false` values,
I had to relax the restriction in the verifier that the rank is always equal to
the length of the attribute array, in other words, we now allow:

- `vector.constant_mask [0] : vector<i1>` which gets lowered to
  `arith.constant dense<false> : vector<i1>`
- `vector.constant_mask [1] : vector<i1>` which gets lowered to
  `arith.constant dense<true> : vector<i1>`

(the attribute list for the 0-D case must be a singleton containing
either `0` or `1`)

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D115023
2021-12-06 08:03:04 +00:00