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torch-mlir/tools/torch-mlir-lsp-server/CMakeLists.txt

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npcomp-lsp-server -> torch-mlir-lsp-server
2021-09-24 10:30:35 +08:00
# torch-mlir-lsp-server is always linked dynamically as we want to distribute the
Add npcomp-lsp-server. To use, do `ninja npcomp-lsp-server`, copy `build/bin/npcomp-lsp-server` into your PATH somewhere, and then add ``` "mlir.server_path": "npcomp-lsp-server", ``` to your settings.json. Also bump llvm-project to 2d9759c7902c5cbc9a7e3ab623321d5578d51687 to bring in latest `mlir-lsp-server` changes.
2021-08-04 07:47:38 +08:00
# binaries with the python packages for hacking/debugging.
Install torch-mlir binaries (#421) In addition, use add_llvm_executable so that the relative rpath of the installed binaries is set properly.
2022-01-21 00:20:54 +08:00
add_llvm_executable(torch-mlir-lsp-server torch-mlir-lsp-server.cpp)
install(TARGETS torch-mlir-lsp-server
EXPORT TorchMLIRTargets
RUNTIME DESTINATION ${LLVM_TOOLS_INSTALL_DIR}
COMPONENT torch-mlir-lsp-server)
Add npcomp-lsp-server. To use, do `ninja npcomp-lsp-server`, copy `build/bin/npcomp-lsp-server` into your PATH somewhere, and then add ``` "mlir.server_path": "npcomp-lsp-server", ``` to your settings.json. Also bump llvm-project to 2d9759c7902c5cbc9a7e3ab623321d5578d51687 to bring in latest `mlir-lsp-server` changes.
2021-08-04 07:47:38 +08:00
Re-organize project structure to separate PyTorch dependencies from core project. (#2542) This is a first step towards the structure we discussed here: https://gist.github.com/stellaraccident/931b068aaf7fa56f34069426740ebf20 There are two primary goals: 1. Separate the core project (C++ dialects and conversions) from the hard PyTorch dependencies. We move all such things into projects/pt1 as a starting point since they are presently entangled with PT1-era APIs. Additional work can be done to disentangle components from that (specifically LTC is identified as likely ultimately living in a `projects/ltc`). 2. Create space for native PyTorch2 Dynamo-based infra to be upstreamed without needing to co-exist with the original TorchScript path. Very little changes in this path with respect to build layering or options. These can be updated in a followup without commingling directory structure changes. This also takes steps toward a couple of other layering enhancements: * Removes the llvm-external-projects/torch-mlir-dialects sub-project, collapsing it into the main tree. * Audits and fixes up the core C++ build to account for issues found while moving things. This is just an opportunistic pass through but roughly ~halves the number of build actions for the project from the high 4000's to the low 2000's. It deviates from the discussed plan by having a `projects/` tree instead of `compat/`. As I was thinking about it, this will better accommodate the follow-on code movement. Once things are roughly in place and the CI passing, followups will focus on more in-situ fixes and cleanups.
2023-11-03 10:45:55 +08:00
# get_property(dialect_libs GLOBAL PROPERTY MLIR_DIALECT_LIBS)
# get_property(conversion_libs GLOBAL PROPERTY MLIR_CONVERSION_LIBS)
# get_property(extension_libs GLOBAL PROPERTY MLIR_EXTENSION_LIBS)
Add npcomp-lsp-server. To use, do `ninja npcomp-lsp-server`, copy `build/bin/npcomp-lsp-server` into your PATH somewhere, and then add ``` "mlir.server_path": "npcomp-lsp-server", ``` to your settings.json. Also bump llvm-project to 2d9759c7902c5cbc9a7e3ab623321d5578d51687 to bring in latest `mlir-lsp-server` changes.
2021-08-04 07:47:38 +08:00
npcomp-lsp-server -> torch-mlir-lsp-server
2021-09-24 10:30:35 +08:00
target_link_libraries(torch-mlir-lsp-server PRIVATE
Add npcomp-lsp-server. To use, do `ninja npcomp-lsp-server`, copy `build/bin/npcomp-lsp-server` into your PATH somewhere, and then add ``` "mlir.server_path": "npcomp-lsp-server", ``` to your settings.json. Also bump llvm-project to 2d9759c7902c5cbc9a7e3ab623321d5578d51687 to bring in latest `mlir-lsp-server` changes.
2021-08-04 07:47:38 +08:00
MLIRLspServerLib
[torch-mlir earthmoving (1/N)] C/C++ code movement. This creates the `external/torch-mlir` directory as an LLVM_EXTERNAL_PROJECTS-compatible project (analogous to `iree-dialects`) and completes movement/rename of all pure MLIR C/C++ compiler code into there. The next step will be to move all the Python code / code that links/includes PyTorch C++ code (which currently lives in `frontends/pytorch`) into a subdirectory here. I call this "earthmoving" because it is mostly mechanical changes and renames. As a quick summary (we can change this down the road easily) - C++ `mlir::NPCOMP::Torch -> mlir::torch::Torch` - CAPI `npcompTorchListTypeGet -> torchMlirTorchListTypeGet` - preprocessor `#ifndef NPCOMP_ -> #ifndef TORCHMLIR_` - CMake `NPCOMPFoo -> TorchMLIRFoo` The goal of this is to create a standalone project creating a center of mass for entry into the MLIR ecosystem from PyTorch, suitable in scope for eventual inclusion/ownership in PyTorch. The idea is that `external/torch-mlir` will some day be pulled out into its own repository, and then npcomp will simply pull it in as a submodule. Layering-wise, what lives in `torch-mlir` lowers code from PyTorch (currently TorchScript, but TorchFX or pytorch/xla-style tracing are possible extensions) down to what we have been calling the "Torch backend contract" which is cleaned up IR (inlining, simplifcation, conversion to value tensors, ...) entirely in the `torch` dialect. This is the branching off point for further lowering, of which npcomp takes one opinion (outside `torch-mlir` of course!), namely the `TorchConversion` dialect/transforms which lower to IR suitable for IREE and other linalg-on-tensors based lower-level compilers. Summary of changes: - move `{include,lib,test}/Dialect/Torch` into `torch-mlir` - move relevant parts of CAPI into `torch-mlir`. - leave a few things related to the `torch-mlir` Python build commented out, which should be resolved in a subsequent change.
2021-09-10 03:24:10 +08:00
TorchMLIRInitAll
Add npcomp-lsp-server. To use, do `ninja npcomp-lsp-server`, copy `build/bin/npcomp-lsp-server` into your PATH somewhere, and then add ``` "mlir.server_path": "npcomp-lsp-server", ``` to your settings.json. Also bump llvm-project to 2d9759c7902c5cbc9a7e3ab623321d5578d51687 to bring in latest `mlir-lsp-server` changes.
2021-08-04 07:47:38 +08:00
Re-organize project structure to separate PyTorch dependencies from core project. (#2542) This is a first step towards the structure we discussed here: https://gist.github.com/stellaraccident/931b068aaf7fa56f34069426740ebf20 There are two primary goals: 1. Separate the core project (C++ dialects and conversions) from the hard PyTorch dependencies. We move all such things into projects/pt1 as a starting point since they are presently entangled with PT1-era APIs. Additional work can be done to disentangle components from that (specifically LTC is identified as likely ultimately living in a `projects/ltc`). 2. Create space for native PyTorch2 Dynamo-based infra to be upstreamed without needing to co-exist with the original TorchScript path. Very little changes in this path with respect to build layering or options. These can be updated in a followup without commingling directory structure changes. This also takes steps toward a couple of other layering enhancements: * Removes the llvm-external-projects/torch-mlir-dialects sub-project, collapsing it into the main tree. * Audits and fixes up the core C++ build to account for issues found while moving things. This is just an opportunistic pass through but roughly ~halves the number of build actions for the project from the high 4000's to the low 2000's. It deviates from the discussed plan by having a `projects/` tree instead of `compat/`. As I was thinking about it, this will better accommodate the follow-on code movement. Once things are roughly in place and the CI passing, followups will focus on more in-situ fixes and cleanups.
2023-11-03 10:45:55 +08:00
# # TODO: Remove these in favor of interface deps.
# ${dialect_libs}
# ${conversion_libs}
# ${extension_libs}
Add npcomp-lsp-server. To use, do `ninja npcomp-lsp-server`, copy `build/bin/npcomp-lsp-server` into your PATH somewhere, and then add ``` "mlir.server_path": "npcomp-lsp-server", ``` to your settings.json. Also bump llvm-project to 2d9759c7902c5cbc9a7e3ab623321d5578d51687 to bring in latest `mlir-lsp-server` changes.
2021-08-04 07:47:38 +08:00
)
npcomp-lsp-server -> torch-mlir-lsp-server
2021-09-24 10:30:35 +08:00
mlir_check_all_link_libraries(torch-mlir-lsp-server)