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torch-mlir/lib/CAPI/CMakeLists.txt

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CMake
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Start reworking towards a shared library build. * Need to have a dag of shared library deps in order to interop across python extensions (as presented in ODM). * Introduced add_npcomp_library and friends to mirror the MLIR setup. * Adds a libNPCOMP.so shared library. * Redirects tools and extensions to link against libNPCOMP.so (instead of static libs). * Moves all libraries to lib/, all binaries to bin/ and all python extensions to python/. The invariant is that the rpaths are setup to have a one level directory structure. * Reworks the _torch_mlir extension to build like the others (still need to come up with a consolidated rule to do this instead of open coded). * Includes an upstream version bump to pick up needed changes. Sizes with dynamic linking (stripped, release, asserts enabled): libNPCOMP.so: 43M (includes much of the underlying LLVM codegen deps) libMLIR.so: 31M _npcomp.so: 1.6M (python extension) _torch_mlir.so: 670K (python extension) npcomp-capi-ir-test: 6.3K npcomp-opt: 351K npcomp-run-mlir: 461K mnist-playground: 530K Still more can be done to normalize and optimize but this gets us structurally to the starting point.
2020-10-09 09:29:59 +08:00
set(LLVM_LINK_COMPONENTS
Core
Support
nativecodegen
)
add_npcomp_library(NPCOMPCAPI
InitLLVM.cpp
Add public API for constructing a module/function to capture PyTorch ops. * Uses the MLIR-C API since that will save us a lot of grief down the road (i.e. will give PyTorch and libMLIR/libNPCOMP the ability to skew version-wise). * Quite a few TODOs and not yet populating the function in any way.
2020-09-29 09:36:00 +08:00
Registration.cpp
Add capture function arguments. * Adds at::Tensor -> MlirValue tracking. * Adds conversions for tensor and scalar types to MLIR types. * Adds npcomp C APIs for constructing custom types. * Reworks pybind include so as to get Torch pybind helpers (needed to pass at::Tensor type from Python->C++).
2020-10-02 09:59:58 +08:00
Types.cpp
Add public API for constructing a module/function to capture PyTorch ops. * Uses the MLIR-C API since that will save us a lot of grief down the road (i.e. will give PyTorch and libMLIR/libNPCOMP the ability to skew version-wise). * Quite a few TODOs and not yet populating the function in any way.
2020-09-29 09:36:00 +08:00
LINK_LIBS PUBLIC
Start reworking towards a shared library build. * Need to have a dag of shared library deps in order to interop across python extensions (as presented in ODM). * Introduced add_npcomp_library and friends to mirror the MLIR setup. * Adds a libNPCOMP.so shared library. * Redirects tools and extensions to link against libNPCOMP.so (instead of static libs). * Moves all libraries to lib/, all binaries to bin/ and all python extensions to python/. The invariant is that the rpaths are setup to have a one level directory structure. * Reworks the _torch_mlir extension to build like the others (still need to come up with a consolidated rule to do this instead of open coded). * Includes an upstream version bump to pick up needed changes. Sizes with dynamic linking (stripped, release, asserts enabled): libNPCOMP.so: 43M (includes much of the underlying LLVM codegen deps) libMLIR.so: 31M _npcomp.so: 1.6M (python extension) _torch_mlir.so: 670K (python extension) npcomp-capi-ir-test: 6.3K npcomp-opt: 351K npcomp-run-mlir: 461K mnist-playground: 530K Still more can be done to normalize and optimize but this gets us structurally to the starting point.
2020-10-09 09:29:59 +08:00
MLIRExecutionEngine
MLIRLLVMIR
Bump llvm-project to e31c77b1827fa4dd3511f21af11cfab18ecf6d38 Signed-off-by: Bairen Yi <yibairen.byron@bytedance.com>
2021-03-09 21:58:03 +08:00
MLIRTargetLLVMIRExport
Add public API for constructing a module/function to capture PyTorch ops. * Uses the MLIR-C API since that will save us a lot of grief down the road (i.e. will give PyTorch and libMLIR/libNPCOMP the ability to skew version-wise). * Quite a few TODOs and not yet populating the function in any way.
2020-09-29 09:36:00 +08:00
NPCOMPInitAll
Add capture function arguments. * Adds at::Tensor -> MlirValue tracking. * Adds conversions for tensor and scalar types to MLIR types. * Adds npcomp C APIs for constructing custom types. * Reworks pybind include so as to get Torch pybind helpers (needed to pass at::Tensor type from Python->C++).
2020-10-02 09:59:58 +08:00
NPCOMPBasicpyDialect
NPCOMPNumpyDialect
Add initial TorchScript module importer It turns out that this was easiest to structure as a general IValue importer, since torch module are just one of the possible IValue's. We import the IValue object graph in a braindead fashion into basicpy ops and a new `torch.nn_module` op that is used to model the attributes/methods of a torch::jit::Module IValue. See `Torch/ops.mlir` for an example, and also check out the .py import tests in `frontends/pytorch/test/module_import`. As part of this change, a few housekeeping tasks: - extract some helpers from graph_importer.cpp - more helpers around the C API - misc touchups
2021-01-28 08:35:44 +08:00
NPCOMPTorchDialect
Add public API for constructing a module/function to capture PyTorch ops. * Uses the MLIR-C API since that will save us a lot of grief down the road (i.e. will give PyTorch and libMLIR/libNPCOMP the ability to skew version-wise). * Quite a few TODOs and not yet populating the function in any way.
2020-09-29 09:36:00 +08:00
)