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llvm-project/mlir/test/CMakeLists.txt

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Enable EDSC API test running through lit EDSC subsystem contains an API test which is a .cpp file calling the API in question and producing IR. This IR is further checked using FileCheck and should plug into lit. Provide a CMakeLists.txt to build the test and modify the lit configuration to process the source file. -- PiperOrigin-RevId: 248794443
2019-05-18 06:03:39 +08:00
add_subdirectory(EDSC)
Move SDBM infrastructure into a new SDBM dialect We now have sufficient extensibility in dialects to move attribute components such as SDBM out of the core IR into a dedicated dialect and make them optional. Introduce an SDBM dialect and move the code. This is a mostly non-functional change. -- PiperOrigin-RevId: 249244802
2019-05-21 22:22:35 +08:00
add_subdirectory(mlir-cpu-runner)
add_subdirectory(SDBM)
Split test-specific passes out of mlir-opt Instead put their impl in test/lib and link them into mlir-test-opt PiperOrigin-RevId: 254837439
2019-06-25 05:35:21 +08:00
add_subdirectory(lib)
Pipe Linalg to a cblas call via mlir-cpu-runner This CL extends the execution engine to allow the additional resolution of symbols names that have been registered explicitly. This allows linking static library symbols that have not been explicitly exported with the -rdynamic linking flag (which is deemed too intrusive). -- PiperOrigin-RevId: 247969504
2019-05-14 01:59:04 +08:00
Initial version for chapter 1 of the Toy tutorial -- PiperOrigin-RevId: 241549247
2019-04-03 01:02:07 +08:00
llvm_canonicalize_cmake_booleans(
LLVM_BUILD_EXAMPLES
)
Cleanup linalg integration test This CL performs post-commit cleanups. It adds the ability to specify which shared libraries to load dynamically in ExecutionEngine. The linalg integration test is updated to use a shared library. Additional minor cleanups related to LLVM lowering of Linalg are also included. -- PiperOrigin-RevId: 248346589
2019-05-16 00:26:27 +08:00
# Passed to lit.site.cfg.py.in to set up the path where to find the libraries
# for linalg integration tests.
Automated rollback of commit d60133f89bb08341718bb3132b19bc891f7d4f4d PiperOrigin-RevId: 282574110
2019-11-27 00:47:14 +08:00
set(MLIR_DIALECT_LINALG_INTEGRATION_TEST_LIB_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY})
[MLIR] Add simple runner utilities for timing Add utilities print_flops, rtclock for timing / benchmarking. Add mlir_runner_utils_dir test conf variable. Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Differential Revision: https://reviews.llvm.org/D76912
2020-03-27 17:20:05 +08:00
set(MLIR_RUNNER_UTILS_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY})
Cleanup linalg integration test This CL performs post-commit cleanups. It adds the ability to specify which shared libraries to load dynamically in ExecutionEngine. The linalg integration test is updated to use a shared library. Additional minor cleanups related to LLVM lowering of Linalg are also included. -- PiperOrigin-RevId: 248346589
2019-05-16 00:26:27 +08:00
Add an mlir-cuda-runner tool. This tool allows to execute MLIR IR snippets written in the GPU dialect on a CUDA capable GPU. For this to work, a working CUDA install is required and the build has to be configured with MLIR_CUDA_RUNNER_ENABLED set to 1. PiperOrigin-RevId: 256551415
2019-07-04 22:49:52 +08:00
# Passed to lit.site.cfg.py.in to set up the path where to find the libraries
[mlir][gpu] Introduce mlir-rocm-runner. Summary: `mlir-rocm-runner` is introduced in this commit to execute GPU modules on ROCm platform. A small wrapper to encapsulate ROCm's HIP runtime API is also inside the commit. Due to behavior of ROCm, raw pointers inside memrefs passed to `gpu.launch` must be modified on the host side to properly capture the pointer values addressable on the GPU. LLVM MC is used to assemble AMD GCN ISA coming out from `ConvertGPUKernelToBlobPass` to binary form, and LLD is used to produce a shared ELF object which could be loaded by ROCm HIP runtime. gfx900 is the default target be used right now, although it could be altered via an option in `mlir-rocm-runner`. Future revisions may consider using ROCm Agent Enumerator to detect the right target on the system. Notice AMDGPU Code Object V2 is used in this revision. Future enhancements may upgrade to AMDGPU Code Object V3. Bitcode libraries in ROCm-Device-Libs, which implements math routines exposed in `rocdl` dialect are not yet linked, and is left as a TODO in the logic. Reviewers: herhut Subscribers: mgorny, tpr, dexonsmith, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, csigg, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, llvm-commits Tags: #mlir, #llvm Differential Revision: https://reviews.llvm.org/D80676
2020-05-21 05:07:49 +08:00
# for the mlir cuda / rocm / vulkan runner tests.
Automated rollback of commit d60133f89bb08341718bb3132b19bc891f7d4f4d PiperOrigin-RevId: 282574110
2019-11-27 00:47:14 +08:00
set(MLIR_CUDA_WRAPPER_LIBRARY_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY})
[mlir][gpu] Introduce mlir-rocm-runner. Summary: `mlir-rocm-runner` is introduced in this commit to execute GPU modules on ROCm platform. A small wrapper to encapsulate ROCm's HIP runtime API is also inside the commit. Due to behavior of ROCm, raw pointers inside memrefs passed to `gpu.launch` must be modified on the host side to properly capture the pointer values addressable on the GPU. LLVM MC is used to assemble AMD GCN ISA coming out from `ConvertGPUKernelToBlobPass` to binary form, and LLD is used to produce a shared ELF object which could be loaded by ROCm HIP runtime. gfx900 is the default target be used right now, although it could be altered via an option in `mlir-rocm-runner`. Future revisions may consider using ROCm Agent Enumerator to detect the right target on the system. Notice AMDGPU Code Object V2 is used in this revision. Future enhancements may upgrade to AMDGPU Code Object V3. Bitcode libraries in ROCm-Device-Libs, which implements math routines exposed in `rocdl` dialect are not yet linked, and is left as a TODO in the logic. Reviewers: herhut Subscribers: mgorny, tpr, dexonsmith, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, csigg, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, llvm-commits Tags: #mlir, #llvm Differential Revision: https://reviews.llvm.org/D80676
2020-05-21 05:07:49 +08:00
set(MLIR_ROCM_WRAPPER_LIBRARY_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY})
[mlir][spirv] Add mlir-vulkan-runner Add an initial version of mlir-vulkan-runner execution driver. A command line utility that executes a MLIR file on the Vulkan by translating MLIR GPU module to SPIR-V and host part to LLVM IR before JIT-compiling and executing the latter. Differential Revision: https://reviews.llvm.org/D72696
2020-02-19 22:11:22 +08:00
set(MLIR_VULKAN_WRAPPER_LIBRARY_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY})
Add an mlir-cuda-runner tool. This tool allows to execute MLIR IR snippets written in the GPU dialect on a CUDA capable GPU. For this to work, a working CUDA install is required and the build has to be configured with MLIR_CUDA_RUNNER_ENABLED set to 1. PiperOrigin-RevId: 256551415
2019-07-04 22:49:52 +08:00
Add build files and update README. * Add initial version of build files; * Update README with instructions to download and build MLIR from github; -- PiperOrigin-RevId: 241102092
2019-03-30 13:10:12 +08:00
configure_lit_site_cfg(
${CMAKE_CURRENT_SOURCE_DIR}/lit.site.cfg.py.in
${CMAKE_CURRENT_BINARY_DIR}/lit.site.cfg.py
MAIN_CONFIG
${CMAKE_CURRENT_SOURCE_DIR}/lit.cfg.py
)
configure_lit_site_cfg(
${CMAKE_CURRENT_SOURCE_DIR}/Unit/lit.site.cfg.py.in
${CMAKE_CURRENT_BINARY_DIR}/Unit/lit.site.cfg.py
MAIN_CONFIG
${CMAKE_CURRENT_SOURCE_DIR}/Unit/lit.cfg.py
)
set(MLIR_TEST_DEPENDS
FileCheck count not
MLIRUnitTests
mlir-cpu-runner
Make EDSC builder test more robust to the order of evaluation EDSC builder test uses FileCheck to match the IR produced by EDSC in the textual order. For mathematical operations, EDSC relies on overloaded operators. Since they are essentially function calls, the order of evaluation of their operands is unspecified and differs between compilers. Do not rely on a specific order of operands and just check they are all emitted before the last operation. Give names to matched SSA values in order to make sure the right operands are used in relevant places. -- PiperOrigin-RevId: 249494995
2019-05-23 03:13:54 +08:00
mlir-edsc-builder-api-test
[mlir][Linalg] Create a tool to generate named Linalg ops from a Tensor Comprehensions-like specification. Summary: This revision adds a tool that generates the ODS and C++ implementation for "named" Linalg ops according to the [RFC discussion](https://llvm.discourse.group/t/rfc-declarative-named-ops-in-the-linalg-dialect/745). While the mechanisms and language aspects are by no means set in stone, this revision allows connecting the pieces end-to-end from a mathematical-like specification. Some implementation details and short-term decisions taken for the purpose of bootstrapping and that are not set in stone include: 1. using a "[Tensor Comprehension](https://arxiv.org/abs/1802.04730)-inspired" syntax 2. implicit and eager discovery of dims and symbols when parsing 3. using EDSC ops to specify the computation (e.g. std_addf, std_mul_f, ...) A followup revision will connect this tool to tablegen mechanisms and allow the emission of named Linalg ops that automatically lower to various loop forms and run end to end. For the following "Tensor Comprehension-inspired" string: ``` def batch_matmul(A: f32(Batch, M, K), B: f32(K, N)) -> (C: f32(Batch, M, N)) { C(b, m, n) = std_addf<k>(std_mulf(A(b, m, k), B(k, n))); } ``` With -gen-ods-decl=1, this emits (modulo formatting): ``` def batch_matmulOp : LinalgNamedStructured_Op<"batch_matmul", [ NInputs<2>, NOutputs<1>, NamedStructuredOpTraits]> { let arguments = (ins Variadic<LinalgOperand>:$views); let results = (outs Variadic<AnyRankedTensor>:$output_tensors); let extraClassDeclaration = [{ llvm::Optional<SmallVector<StringRef, 8>> referenceIterators(); llvm::Optional<SmallVector<AffineMap, 8>> referenceIndexingMaps(); void regionBuilder(ArrayRef<BlockArgument> args); }]; let hasFolder = 1; } ``` With -gen-ods-impl, this emits (modulo formatting): ``` llvm::Optional<SmallVector<StringRef, 8>> batch_matmul::referenceIterators() { return SmallVector<StringRef, 8>{ getParallelIteratorTypeName(), getParallelIteratorTypeName(), getParallelIteratorTypeName(), getReductionIteratorTypeName() }; } llvm::Optional<SmallVector<AffineMap, 8>> batch_matmul::referenceIndexingMaps() { MLIRContext *context = getContext(); AffineExpr d0, d1, d2, d3; bindDims(context, d0, d1, d2, d3); return SmallVector<AffineMap, 8>{ AffineMap::get(4, 0, {d0, d1, d3}), AffineMap::get(4, 0, {d3, d2}), AffineMap::get(4, 0, {d0, d1, d2}) }; } void batch_matmul::regionBuilder(ArrayRef<BlockArgument> args) { using namespace edsc; using namespace intrinsics; ValueHandle _0(args[0]), _1(args[1]), _2(args[2]); ValueHandle _4 = std_mulf(_0, _1); ValueHandle _5 = std_addf(_2, _4); (linalg_yield(ValueRange{ _5 })); } ``` Differential Revision: https://reviews.llvm.org/D77067
2020-04-11 01:54:08 +08:00
mlir-linalg-ods-gen
Add build files and update README. * Add initial version of build files; * Update README with instructions to download and build MLIR from github; -- PiperOrigin-RevId: 241102092
2019-03-30 13:10:12 +08:00
mlir-opt
Move SDBM infrastructure into a new SDBM dialect We now have sufficient extensibility in dialects to move attribute components such as SDBM out of the core IR into a dedicated dialect and make them optional. Introduce an SDBM dialect and move the code. This is a mostly non-functional change. -- PiperOrigin-RevId: 249244802
2019-05-21 22:22:35 +08:00
mlir-sdbm-api-test
Add build files and update README. * Add initial version of build files; * Update README with instructions to download and build MLIR from github; -- PiperOrigin-RevId: 241102092
2019-03-30 13:10:12 +08:00
mlir-tblgen
mlir-translate
[mlir][test] NFC - Rename cblas to mlir_test_cblas The "cblas" lib under mlir/test is meant as a simple integration demonstration. However it is installed and ends up conflicting with external projects who want to define the real cblas. Rename to avoid conflicts. Differential revision: https://reviews.llvm.org/D76615
2020-04-10 03:29:06 +08:00
mlir_test_cblas
mlir_test_cblas_interface
[mlir] Hotfix - Rename MLIRRuntimeUtils to mlir_runtime_utils
2020-02-28 01:58:41 +08:00
mlir_runner_utils
[mlir] NFC - Split out RunnerUtils that don't require a C++ runtime Summary: This revision split out a new CRunnerUtils library that supports MLIR execution on targets without a C++ runtime. Differential Revision: https://reviews.llvm.org/D75257
2020-02-28 02:45:43 +08:00
mlir_c_runner_utils
Add build files and update README. * Add initial version of build files; * Update README with instructions to download and build MLIR from github; -- PiperOrigin-RevId: 241102092
2019-03-30 13:10:12 +08:00
)
Initial version for chapter 1 of the Toy tutorial -- PiperOrigin-RevId: 241549247
2019-04-03 01:02:07 +08:00
if(LLVM_BUILD_EXAMPLES)
list(APPEND MLIR_TEST_DEPENDS
toyc-ch1
Chapter 2 of the Toy tutorial This introduces a basic MLIRGen through straight AST traversal, without dialect registration at this point. -- PiperOrigin-RevId: 241588354
2019-04-03 04:11:20 +08:00
toyc-ch2
Fix Toy Ch3 testing with CMake Mainly a missing dependency caused the tests to pass if one already built the repo, but not from a clean (or incremental) build. -- PiperOrigin-RevId: 241852313
2019-04-04 10:16:32 +08:00
toyc-ch3
Add Chapter 4 for the Toy tutorial: shape inference, function specialization, and basic combines -- PiperOrigin-RevId: 242050514
2019-04-05 09:31:31 +08:00
toyc-ch4
Toy tutorial Chapter 5: Lowering to Linalg and LLVM -- PiperOrigin-RevId: 242606796
2019-04-09 14:00:49 +08:00
toyc-ch5
Add Ch.6 of the Toy tutorial. This chapters introduces the notion of a full conversion, and adds support for lowering down to the LLVM dialect, LLVM IR, and thus code generation. PiperOrigin-RevId: 275337786
2019-10-18 05:21:44 +08:00
toyc-ch6
Add Ch-7 of the toy tutorial detailing how to define new types. This chapter adds a new composite type to Toy, and shows the process of adding a new type to the IR, adding and updating operations to use it, and constant folding operations producing it. PiperOrigin-RevId: 279107885
2019-11-08 01:53:27 +08:00
toyc-ch7
Initial version for chapter 1 of the Toy tutorial -- PiperOrigin-RevId: 241549247
2019-04-03 01:02:07 +08:00
)
endif()
Add an mlir-cuda-runner tool. This tool allows to execute MLIR IR snippets written in the GPU dialect on a CUDA capable GPU. For this to work, a working CUDA install is required and the build has to be configured with MLIR_CUDA_RUNNER_ENABLED set to 1. PiperOrigin-RevId: 256551415
2019-07-04 22:49:52 +08:00
if(MLIR_CUDA_RUNNER_ENABLED)
list(APPEND MLIR_TEST_DEPENDS
mlir-cuda-runner
)
endif()
[mlir][gpu] Introduce mlir-rocm-runner. Summary: `mlir-rocm-runner` is introduced in this commit to execute GPU modules on ROCm platform. A small wrapper to encapsulate ROCm's HIP runtime API is also inside the commit. Due to behavior of ROCm, raw pointers inside memrefs passed to `gpu.launch` must be modified on the host side to properly capture the pointer values addressable on the GPU. LLVM MC is used to assemble AMD GCN ISA coming out from `ConvertGPUKernelToBlobPass` to binary form, and LLD is used to produce a shared ELF object which could be loaded by ROCm HIP runtime. gfx900 is the default target be used right now, although it could be altered via an option in `mlir-rocm-runner`. Future revisions may consider using ROCm Agent Enumerator to detect the right target on the system. Notice AMDGPU Code Object V2 is used in this revision. Future enhancements may upgrade to AMDGPU Code Object V3. Bitcode libraries in ROCm-Device-Libs, which implements math routines exposed in `rocdl` dialect are not yet linked, and is left as a TODO in the logic. Reviewers: herhut Subscribers: mgorny, tpr, dexonsmith, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, csigg, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, llvm-commits Tags: #mlir, #llvm Differential Revision: https://reviews.llvm.org/D80676
2020-05-21 05:07:49 +08:00
if(MLIR_ROCM_RUNNER_ENABLED)
list(APPEND MLIR_TEST_DEPENDS
mlir-rocm-runner
)
endif()
[mlir][spirv] Add mlir-vulkan-runner Add an initial version of mlir-vulkan-runner execution driver. A command line utility that executes a MLIR file on the Vulkan by translating MLIR GPU module to SPIR-V and host part to LLVM IR before JIT-compiling and executing the latter. Differential Revision: https://reviews.llvm.org/D72696
2020-02-19 22:11:22 +08:00
if(MLIR_VULKAN_RUNNER_ENABLED)
list(APPEND MLIR_TEST_DEPENDS
mlir-vulkan-runner
)
endif()
Add build files and update README. * Add initial version of build files; * Update README with instructions to download and build MLIR from github; -- PiperOrigin-RevId: 241102092
2019-03-30 13:10:12 +08:00
add_lit_testsuite(check-mlir "Running the MLIR regression tests"
${CMAKE_CURRENT_BINARY_DIR}
DEPENDS ${MLIR_TEST_DEPENDS}
)
set_target_properties(check-mlir PROPERTIES FOLDER "Tests")
add_lit_testsuites(MLIR ${CMAKE_CURRENT_SOURCE_DIR}
DEPENDS ${MLIR_TEST_DEPS}
)