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torch-mlir/lib/Dialect/ATen/CMakeLists.txt

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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
add_npcomp_dialect_library(NPCOMPATenDialect
Add ATen Dialect (#16) This patch adds a dialect intended to be used as a frontend dialect to facilitate lowering from "A Tensor Library" in torch/pytorch. This patch includes several passes that are useful in conjuction with the dialect: --aten-layer-name: Generates layer names for each operation, which are not present in the original pytorch. --aten-to-std: Lower the ATen dialect into standard dialect function calls. --return-elimination-pass: convert functions (primarily the toplevel function) to pass return values by reference. This simplifies pytorch integration. --aten-op-report: generate a textual report about the model --liveness-report Future patches will implement actual integration with the pytorch jit to intercept and generates MLIR in this dialect, then lower the resulting MLIR into function calls through aten-layer-name -> aten-to-std -> return-elimination -> std-to-llvm. The result would then jitted using the LLVM jit, linked against a runtime library which makes calls back into pytorch to implement all the layers. Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com> Co-authored-by: Jeff Fifield <jeff.fifield@xilinx.com>
2020-08-13 10:28:04 +08:00
ATenDialect.cpp
ATenDialectOpStats.cpp
ATenPasses.cpp
ATenLayerNamePass.cpp
ATenLoweringPass.cpp
ATenOpReport.cpp
ATenToStd.cpp
LivenessReport.cpp
ReturnEliminationPass.cpp
ADDITIONAL_HEADER_DIRS
${PROJECT_SOURCE_DIR}/dialect/include
${PROJECT_BINARY_DIR}/dialect/include
DEPENDS
MLIRATenIncGen
MLIRATenEnumsIncGen
MLIRATenOpInterfacesIncGen
MLIRATenToStdIncGen
LINK_LIBS PUBLIC
MLIRPass
MLIRTransformUtils
)