* Detect llvm-project commit change in utils/clone-mlir.sh and rebuild llvm-project
for zLinux Jenkins build bot
* Since many headers are generated and included indirectly through
other headers, there are often missing dependencies that break
parallel build. So we add header targets for KrnlOps, ONNXOps, and
MLONNXOps, and add explicit dependencies for all the relevant headers.
* fix copy-and-paste bug
Co-authored-by: Tian Jin <tjingrant@gmail.com>
* Call llc, ld from within onnx-mlir.
* Rename EmitLLVMBC -> EmitLib., reorder header files
* Edit comment.
* Checkpoint, debug.py works.
* Automatically generate inputs in debug.py.
* Use float.
* initial support for rapidcheck tests.
* Convolution test case works.
* Format code.
* Link library with MainUtils.
* Fix CMake script error.
* Fast implementation of array assertion, more detailed error analysis.
* More utility for DynMemRef.
* Fix linking issue.
* Uncomment unit test.
* Refactor to separate C++/Python ExecutionSession, enable unit test.
* format code.
* Verbose build.
* Enable PIC option for ExecusionSession.
* Fix cmake error.
* Build all targets.
* Fix doc to build all targets.
* Clean up.
* Clean up, debug.
* Use type alias consistently.
* Move definitions to DynMemRef.cpp.
* include algorithm.
* pyruntime -> PyRuntime
* Format code.
* Free memory.
* Add comments.
* Copyright notice.
* Improve stylistic consistency.
* Add comment.
* Revert irrelevant changes.
* Disambiguate.
* Refator test case generator out from test case implementation, implement example exhaustive test driver.
* Add documentation for testing.
* Add type inference for CastOp
* Share type translation between op builder and onnx importer
* clang-format
* Format emitted code
* Remove unnecessary dependencies
* fix type inference for ConstantOp and MaxPoolSingleOut
* modify interface
* use OpInterface
* change name to OpInterface
* Builder dependence
* Update CMakeLists.txt
* Update CMakeLists.txt
Co-authored-by: Tian Jin <tjingrant@gmail.com>
* Reorganize main function.
* Follow review comments.
* Emit constants are globals in Krnl and LLVM dialects.
* Output of non-value constants. Write full source to file.
* Fix e2e tests.
* Output constant free and full code in separate files.
* Emit separate files.
* Move file output management to utils.
* Elide the values of glotbal krnl constants.
* Add dual file output for Basic flag.
* Add tests.
* Add passes to cmake file.
* Specify each lib only once; allow llvm build in shared libs mode.
* Remove debug code.
* For library targets, retain dependency information using add_dependencies, but do not link using taget_link_libraries.
* Do not set LD_PRELOAD by default.
Co-authored-by: Gong Su <gongsu@us.ibm.com>
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
* 1.Break down CMake scripts to smaller libraries per-directory.
2. Move some transformations and interfaces to the right folder.
3. Fix minor merge failure of the patch renaming files to use LLVM convention.
* Link OMBuilder with OMONNXOps.
* 1. Update the src location of generated ONNX dialect definition.
2. Link OMONNXRewrite with OMONNXOps.
* Fix path to tablegen for add_onnx_mlir_dialect_doc.
* Update build script for onnx_mlir_transform.
* 1. Remove comment code.
2. onnx_mlir_attribute_promotion -> OMAttributePromotion.
* Name tablegen generated files with LLVM convention.
* Nit: reorder libraries to link against.
* Nit: Link against MLIR first.
* Support attribute promotion.
* Simplify op interface name.
* 1. Add more comments to Attribute Promotion Pass.
2. Move Promotable Const Operand Interface to src/interface, and link against it.
* Complete NFC change onnx -> onnx-mlir.
* Move attribute_promotion pass to src/transform.
* Nit: reword comment.
* Support Attribute Promotion in gen_doc.py.
* Add test.
* Update ONNX doc.
* Add negative test.
* Rename onnxop.inc -> onnx_ops.td.inc.
* Include onnx_ops.td.inc.
* Nit: better comments.
* Prettify CMake.
* Remove original attribute_promotion code, improve comments.
* Append '_op_interface' to op interface decl/defs.
* Namespace cmake targets using onnx_mlir_ prefix.
* Use updated header name.
* Use new body file name.
* Fix dependency.
* Use new CMake target name.
* Make attribute promotion self-contained by removing redundant constant operaions inside the pass execution.
* Remove canonicalization pass.
* Increase comments.
* Use stricter checks.
* Add one more test case.
* Remove %arg1 as it's never used.
* Lower MaxPoolSingleOutOp to Krnl dialect
* Edit comments
* Update changes according to the new folder structure
* Add MLIR tests
* Support ceil_mode
* Merge the first two krnl loops into one krnl loop; remove attribute checks
* Dynamically allocate memory for the result if the result has unknown dimensions
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
* Add result type inference to op definition
* Edit MLIR tests
* Fix result type for Mul
* Format comments
* Return UnrankedTensorType as result type
* Just for testing -split-input-file
* Undo: Just for testing -split-input-file
* Extract a function, get_operand_ins, that gets operand types; rewrite gen_attr_ins function
* Generate custom builders
* Call existing build methods
* Add comments
* Minor changes
* Generate build methods with attributes
* Add support of variadic type
* Do not generate custom build methods for ops having only attributes
Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
* Create two categories: elementwise and tensor
* typos
* Create directories for categories
* Edit comments
* Extract a function that creates a KrnlIterateOp
* Add comments
* Extract some common parts
* Revise softmax
* Add reduction.inc
* Move lower-frontend to lib/conversion
* Move directory to directory
* Change file/directory names
* Comment format
* Add matmul.inc
* Add dialect documentation.
* Add a step in our CI to ensure documentation is up-to-date.
* Add dialect documentation.
* Fix config file mistake, using multi-line commands.
* Fix a bug in DocCheck.
* Rewrite ReduceSumSquare
* Edit gen_doc.py
* Revise the code
* Do shape inference after canonicalization so that there is no need to implement shape inference of rewritten ops
* Rewrite ReduceL2
* Add onnx_rewrite.cpp for all rewriting for ONNX ops
* Rewrite ReduceL1, ReduceLogSum, ReduceLogSumExp
* Edit comments
* Change the use of -> to .
* Checkout gen_doc.py from the master branch
* Use emplace_back instead of push_back
* Revise the code
* Edit comments
Co-authored-by: Tian Jin <tjingrant@gmail.com>
* Store bounds as affine map attributes & check in test cases with generic printer
* Upgrading MLIR
MLIR is outdated on Buildbot, rebuilding a newer version.
* work with new version of mlir
* check-in parser tests
* custom printer
* nit
* bug fix
* enable custom asm printer test
* enable custom asm printer test
* more consistent variable naming
* test max/min
* variable naming scheme change to MLIR style
* can lower krnl to llvm
* kernel -> llvm
* comments
* bug fix
* try fixing ci
* fix ci
* deactivate model test
* fix lit test
* nit
* fix z buildbot
* a complete, roud-trippable Krnl dialect operation definition
* remove old dialect definition files, edit build files
* register dialect
* check in src for onnf_opt and dimension handler types
* re-trigger jenkins
* fix build
* clarify operation semantics
* add verifier for krnl.iterate
* refactor to make things clear
* do not hard code types
* nit and add comments
* fix rebase
* update op implementation
* fix merge
* update kernel dialect definition
* more comment on how to use the builder for krnl.iterate operation
* ammend the comment
* can parse krnl.iterate
* can parse and print if bounds are not SSA values
* address comments
* better error handling
* Update CMakeLists.txt
* update comment
* reflow comments
* Create and register ONNX Dialect with one Add operation.
* Fix file formatting.
* Change name from ONNX to SGIR.
* Use ONNX dialect. Change SGIR to frontend placeholder dialect.
* Add comments.
* Type clean-up.
gongsu832
Tian Jin
Tung D. Le
chentong319
Gheorghe-Teodor Bercea
Gheorghe-Teodor Bercea
Tian Jin