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torch-mlir/CMakeLists.txt

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Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
cmake_minimum_required(VERSION 3.12)
if(POLICY CMP0068)
cmake_policy(SET CMP0068 NEW)
set(CMAKE_BUILD_WITH_INSTALL_NAME_DIR ON)
endif()
if(POLICY CMP0075)
cmake_policy(SET CMP0075 NEW)
endif()
if(POLICY CMP0077)
cmake_policy(SET CMP0077 NEW)
[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
endif()
Bump LLVM to 881ff4e4ebe8cc0cc045c7c167cffb01f94f27f8 (#539)
2022-01-26 14:16:30 +08:00
if(POLICY CMP0116)
cmake_policy(SET CMP0116 OLD)
endif()
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
#-------------------------------------------------------------------------------
# Project setup and globals
#-------------------------------------------------------------------------------
post-commit review cleanup for #356 see https://github.com/llvm/torch-mlir/pull/356
2021-10-09 02:28:40 +08:00
project(torch-mlir LANGUAGES CXX C)
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
set(CMAKE_C_STANDARD 11)
set(CMAKE_CXX_STANDARD 14)
Add TMTensor dialect to torch-mlir This is intended to explore support for non-structured ops that can't be modeled by Linalg dialect. `tm_tensor.scan` and `tm_tensor.scatter` are added as the first such ops. The dialect should aim to be upstreamed in the future.
2022-02-03 07:01:38 +08:00
macro(torch_mlir_add_llvm_external_project name identifier location)
message(STATUS "Adding LLVM external project ${name} (${identifier}) -> ${location}")
if(NOT EXISTS "${location}/CMakeLists.txt")
message(FATAL_ERROR "External project location ${location} is not valid")
endif()
list(APPEND LLVM_EXTERNAL_PROJECTS ${name})
list(REMOVE_DUPLICATES LLVM_EXTERNAL_PROJECTS)
set(LLVM_EXTERNAL_${identifier}_SOURCE_DIR ${location} CACHE STRING "" FORCE)
set(LLVM_EXTERNAL_PROJECTS ${LLVM_EXTERNAL_PROJECTS} CACHE STRING "" FORCE)
endmacro()
torch_mlir_add_llvm_external_project(
torch-mlir-dialects
TORCH_MLIR_DIALECTS
${CMAKE_CURRENT_SOURCE_DIR}/external/llvm-external-projects/torch-mlir-dialects)
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
# Out-of-tree build
#-------------------------------------------------------------------------------
# MLIR/LLVM Configuration
#-------------------------------------------------------------------------------
find_package(MLIR REQUIRED CONFIG)
message(STATUS "Using MLIRConfig.cmake in: ${MLIR_DIR}")
message(STATUS "Using LLVMConfig.cmake in: ${LLVM_DIR}")
set(LLVM_RUNTIME_OUTPUT_INTDIR ${CMAKE_BINARY_DIR}/bin)
set(LLVM_LIBRARY_OUTPUT_INTDIR ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
Bump llvm-project to 3d92722f74993969243d1400bc3257ca3d03902f. (#369) * Picks up Python configure changes (was pinned to a bad intermediate commit). * Uses the new mlir_configure_python_dev_packages() to ensure CMake python is found consistently. * Fixes the JIT importer to build as a MODULE vs SHARED (needed for linking to Python as a module, per config changes). * Adds some notes to the README to help folks build a smaller set focused just on this project.
2021-10-22 12:09:00 +08:00
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
# Define the default arguments to use with 'lit', and an option for the user to
# override.
set(LIT_ARGS_DEFAULT "-sv")
if (MSVC_IDE OR XCODE)
set(LIT_ARGS_DEFAULT "${LIT_ARGS_DEFAULT} --no-progress-bar")
endif()
set(LLVM_LIT_ARGS "${LIT_ARGS_DEFAULT}" CACHE STRING "Default options for lit")
list(APPEND CMAKE_MODULE_PATH "${MLIR_CMAKE_DIR}")
list(APPEND CMAKE_MODULE_PATH "${LLVM_CMAKE_DIR}")
include(TableGen)
include(AddLLVM)
include(AddMLIR)
include(HandleLLVMOptions)
# Don't try to compile the python extensions at the moment. We need
# to import lots of dependencies from AddMLIRPython to make this work.
Enable python extensions when building out of tree (#363)
2021-10-28 08:04:12 +08:00
set(MLIR_ENABLE_BINDINGS_PYTHON 1)
option(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER "Enables JIT IR Importer" ON)
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
post-commit review cleanup for #356 see https://github.com/llvm/torch-mlir/pull/356
2021-10-09 02:28:40 +08:00
set(TORCH-MLIR_BUILT_STANDALONE 1)
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
set(BACKEND_PACKAGE_STRING "LLVM ${LLVM_PACKAGE_VERSION}")
Ensure that torch-mlir-dialects is built when we're out of tree Its unclear to me what the right layering is here: Are you expecting torch-mlir-dialects to always get built with LLVM? This is pretty breaking for us, if so.
2022-02-26 06:45:28 +08:00
add_subdirectory(external/llvm-external-projects/torch-mlir-dialects)
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
else()
# In-tree build with LLVM_EXTERNAL_PROJECTS=torch-mlir
Don't override MLIR_TABLEGEN_EXE (#622) This should be set elsewhere depending on the build configuration. In particular, we need to be careful when cross-compiling to pick up the host mlir-tblgen.
2022-02-26 06:41:09 +08:00
# FIXME: This should really be inherited from the LLVM tree. In particular,
# it's going to change when cross-compiling.
set(MLIR_TABLEGEN_EXE mlir-tblgen)
Bump llvm-project to 3d92722f74993969243d1400bc3257ca3d03902f. (#369) * Picks up Python configure changes (was pinned to a bad intermediate commit). * Uses the new mlir_configure_python_dev_packages() to ensure CMake python is found consistently. * Fixes the JIT importer to build as a MODULE vs SHARED (needed for linking to Python as a module, per config changes). * Adds some notes to the README to help folks build a smaller set focused just on this project.
2021-10-22 12:09:00 +08:00
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
option(MLIR_ENABLE_BINDINGS_PYTHON "Enables MLIR Python Bindings" OFF)
option(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER "Enables JIT IR Importer" ON)
# TODO: Fix this upstream so that global include directories are not needed.
set(MLIR_MAIN_SRC_DIR ${LLVM_MAIN_SRC_DIR}/../mlir)
set(MLIR_INCLUDE_DIR ${LLVM_MAIN_SRC_DIR}/../mlir/include)
set(MLIR_GENERATED_INCLUDE_DIR ${LLVM_BINARY_DIR}/tools/mlir/include)
set(MLIR_INCLUDE_DIRS "${MLIR_INCLUDE_DIR};${MLIR_GENERATED_INCLUDE_DIR}")
post-commit review cleanup for #356 see https://github.com/llvm/torch-mlir/pull/356
2021-10-09 02:28:40 +08:00
endif()
[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
set(TORCH_MLIR_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}")
set(TORCH_MLIR_BINARY_DIR "${CMAKE_CURRENT_BINARY_DIR}")
message(STATUS "Building torch-mlir project at ${TORCH_MLIR_SOURCE_DIR} (into ${TORCH_MLIR_BINARY_DIR})")
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
include_directories(${LLVM_INCLUDE_DIRS})
include_directories(${MLIR_INCLUDE_DIRS})
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/include)
include_directories(${CMAKE_CURRENT_BINARY_DIR}/include)
[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
function(torch_mlir_target_includes target)
set(_dirs
$<BUILD_INTERFACE:${MLIR_INCLUDE_DIR}>
$<BUILD_INTERFACE:${MLIR_GENERATED_INCLUDE_DIR}>
$<BUILD_INTERFACE:${TORCH_MLIR_SOURCE_DIR}/include>
$<BUILD_INTERFACE:${TORCH_MLIR_BINARY_DIR}/include>
)
# In LLVM parlance, the actual target may just be an interface and may not
# be responsible for actually compiling anything. The corresponding obj.
# target, when present, is just used for compilation and does not
# contribute to the interface properties.
# TODO: Normalize this upstream.
target_include_directories(${target} PUBLIC ${_dirs})
if(TARGET obj.${target})
target_include_directories(obj.${target} PRIVATE ${_dirs})
endif()
endfunction()
Don't override MLIR_TABLEGEN_EXE (#622) This should be set elsewhere depending on the build configuration. In particular, we need to be careful when cross-compiling to pick up the host mlir-tblgen.
2022-02-26 06:41:09 +08:00
# Configure CMake.
[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
list(APPEND CMAKE_MODULE_PATH ${MLIR_MAIN_SRC_DIR}/cmake/modules)
list(APPEND CMAKE_MODULE_PATH ${LLVM_MAIN_SRC_DIR}/cmake)
include(TableGen)
include(AddLLVM)
include(AddMLIR)
################################################################################
# Setup python.
################################################################################
if(MLIR_ENABLE_BINDINGS_PYTHON)
include(MLIRDetectPythonEnv)
Bump llvm-project to 3d92722f74993969243d1400bc3257ca3d03902f. (#369) * Picks up Python configure changes (was pinned to a bad intermediate commit). * Uses the new mlir_configure_python_dev_packages() to ensure CMake python is found consistently. * Fixes the JIT importer to build as a MODULE vs SHARED (needed for linking to Python as a module, per config changes). * Adds some notes to the README to help folks build a smaller set focused just on this project.
2021-10-22 12:09:00 +08:00
mlir_configure_python_dev_packages()
[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
endif()
add_subdirectory(include)
add_subdirectory(lib)
add_subdirectory(tools)
Port the bulk of the remaining code to torch-mlir This leaves no real code outside torch-mlir. This also renames the "npcomp backend contract" to "linalg on tensors backend contract" as the name of the abstraction layer that RefBackend (IREE too) accepts.
2021-09-28 02:36:44 +08:00
add_custom_target(check-torch-mlir-all)
add_dependencies(check-torch-mlir-all
check-torch-mlir
Add TMTensor dialect to torch-mlir This is intended to explore support for non-structured ops that can't be modeled by Linalg dialect. `tm_tensor.scan` and `tm_tensor.scatter` are added as the first such ops. The dialect should aim to be upstreamed in the future.
2022-02-03 07:01:38 +08:00
check-torch-mlir-dialects
Port the bulk of the remaining code to torch-mlir This leaves no real code outside torch-mlir. This also renames the "npcomp backend contract" to "linalg on tensors backend contract" as the name of the abstraction layer that RefBackend (IREE too) accepts.
2021-09-28 02:36:44 +08:00
)
[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
if(MLIR_ENABLE_BINDINGS_PYTHON)
Implement Python relayout from #311 Fixes https://github.com/llvm/mlir-npcomp/issues/311 The key change is that TorchPlugin is folded into `torch_mlir.dialects.torch.importer.jit_ir` (it imports the PyTorch JIT's IR, so that's a good, scoped name for it). The CMake option `-DTORCH_MLIR_ENABLE_JIT_IR_IMPORTER=OFF` disables it, which allows building without a PyTorch native dependency.
2021-09-21 04:55:36 +08:00
# If parent projects want to configure where to place the python packages,
# respect that.
[torch-mlir earthmoving (2/N)] Python code movement. This moves the bulk of the Python code (including the Torch interop) from `frontends/pytorch` into `torch-mlir/TorchPlugin`. This also required reconciling a bunch of other Python-related stuff, like the `torch` dialects. As I did this, it was simpler to just remove all the old numpy/basicpy stuff because we were going to delete it anyway and it was faster than debugging an intermediate state that would only last O(days) anyway. torch-mlir has two top-level python packages (built into the `python_packages` directory): - `torch_mlir_dialects`: `torch` dialect Python bindings (does not depend on PyTorch). This also involves building the aggregate CAPI for `torch-mlir`. - `torch_mlir`: bindings to the part of the code that links against PyTorch (or C++ code that transitively does). Additionally, there remain two more Python packages in npcomp (but outside `torch-mlir`): - `npcomp_torch`: Contains the e2e test framework and testing configs that plug into RefBackend and IREE. - `npcomp_core`: Contains the low-level interfaces to RefBackend and IREE that `npcomp_torch` uses, along with its own `MLIR_PYTHON_PACKAGE_PREFIX=npcomp.` aggregation of the core MLIR python bindings. (all other functionality has been stripped out) After all the basicpy/numpy deletions, the `npcomp` C++ code is now very tiny. It basically just contains RefBackend and the `TorchConversion` dialect/passes (e.g. `TorchToLinalg.cpp`). Correspondingly, there are now 4 main testing targets paralleling the Python layering (which is reflective of the deeper underlying dependency structure) - `check-torch-mlir`: checks the `torch-mlir` pure MLIR C++ code. - `check-torch-mlir-plugin`: checks the code in `TorchPlugin` (e.g. TorchScript import) - `check-frontends-pytorch`: Checks the little code we have in `frontends/pytorch` -- mainly things related to the e2e framework itself. - `check-npcomp`: Checks the pure MLIR C++ code inside npcomp. There is a target `check-npcomp-all` that runs all of them. The `torch-mlir/build_standalone.sh` script does a standalone build of `torch-mlir`. The e2e tests (`tools/torchscript_e2e_test.sh`) are working too. The update_torch_ods script now lives in `torch-mlir/build_tools/update_torch_ods.sh` and expects a standalone build. This change also required a fix upstream related to cross-shlib Python dependencies, so we also update llvm-project to 8dca953dd39c0cd8c80decbeb38753f58a4de580 to get https://reviews.llvm.org/D109776 (no other fixes were needed for the integrate, thankfully). This completes most of the large source code changes. Next will be bringing the CI/packaging/examples back to life.
2021-09-11 02:44:38 +08:00
if(NOT TORCH_MLIR_PYTHON_PACKAGES_DIR)
set(TORCH_MLIR_PYTHON_PACKAGES_DIR "${CMAKE_CURRENT_BINARY_DIR}/python_packages")
endif()
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
add_dependencies(check-torch-mlir-all
check-torch-mlir-python
)
[torch-mlir earthmoving (2/N)] Python code movement. This moves the bulk of the Python code (including the Torch interop) from `frontends/pytorch` into `torch-mlir/TorchPlugin`. This also required reconciling a bunch of other Python-related stuff, like the `torch` dialects. As I did this, it was simpler to just remove all the old numpy/basicpy stuff because we were going to delete it anyway and it was faster than debugging an intermediate state that would only last O(days) anyway. torch-mlir has two top-level python packages (built into the `python_packages` directory): - `torch_mlir_dialects`: `torch` dialect Python bindings (does not depend on PyTorch). This also involves building the aggregate CAPI for `torch-mlir`. - `torch_mlir`: bindings to the part of the code that links against PyTorch (or C++ code that transitively does). Additionally, there remain two more Python packages in npcomp (but outside `torch-mlir`): - `npcomp_torch`: Contains the e2e test framework and testing configs that plug into RefBackend and IREE. - `npcomp_core`: Contains the low-level interfaces to RefBackend and IREE that `npcomp_torch` uses, along with its own `MLIR_PYTHON_PACKAGE_PREFIX=npcomp.` aggregation of the core MLIR python bindings. (all other functionality has been stripped out) After all the basicpy/numpy deletions, the `npcomp` C++ code is now very tiny. It basically just contains RefBackend and the `TorchConversion` dialect/passes (e.g. `TorchToLinalg.cpp`). Correspondingly, there are now 4 main testing targets paralleling the Python layering (which is reflective of the deeper underlying dependency structure) - `check-torch-mlir`: checks the `torch-mlir` pure MLIR C++ code. - `check-torch-mlir-plugin`: checks the code in `TorchPlugin` (e.g. TorchScript import) - `check-frontends-pytorch`: Checks the little code we have in `frontends/pytorch` -- mainly things related to the e2e framework itself. - `check-npcomp`: Checks the pure MLIR C++ code inside npcomp. There is a target `check-npcomp-all` that runs all of them. The `torch-mlir/build_standalone.sh` script does a standalone build of `torch-mlir`. The e2e tests (`tools/torchscript_e2e_test.sh`) are working too. The update_torch_ods script now lives in `torch-mlir/build_tools/update_torch_ods.sh` and expects a standalone build. This change also required a fix upstream related to cross-shlib Python dependencies, so we also update llvm-project to 8dca953dd39c0cd8c80decbeb38753f58a4de580 to get https://reviews.llvm.org/D109776 (no other fixes were needed for the integrate, thankfully). This completes most of the large source code changes. Next will be bringing the CI/packaging/examples back to life.
2021-09-11 02:44:38 +08:00
add_subdirectory(python)
Add support for out-of-tree building (#356) Currently I haven't attempted to get the python bits working. Instead the python bits are forcibly disabled.
2021-10-08 12:44:15 +08:00
else()
add_custom_target(TorchMLIRPythonModules)
[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
endif()
[torch-mlir earthmoving (2/N)] Python code movement. This moves the bulk of the Python code (including the Torch interop) from `frontends/pytorch` into `torch-mlir/TorchPlugin`. This also required reconciling a bunch of other Python-related stuff, like the `torch` dialects. As I did this, it was simpler to just remove all the old numpy/basicpy stuff because we were going to delete it anyway and it was faster than debugging an intermediate state that would only last O(days) anyway. torch-mlir has two top-level python packages (built into the `python_packages` directory): - `torch_mlir_dialects`: `torch` dialect Python bindings (does not depend on PyTorch). This also involves building the aggregate CAPI for `torch-mlir`. - `torch_mlir`: bindings to the part of the code that links against PyTorch (or C++ code that transitively does). Additionally, there remain two more Python packages in npcomp (but outside `torch-mlir`): - `npcomp_torch`: Contains the e2e test framework and testing configs that plug into RefBackend and IREE. - `npcomp_core`: Contains the low-level interfaces to RefBackend and IREE that `npcomp_torch` uses, along with its own `MLIR_PYTHON_PACKAGE_PREFIX=npcomp.` aggregation of the core MLIR python bindings. (all other functionality has been stripped out) After all the basicpy/numpy deletions, the `npcomp` C++ code is now very tiny. It basically just contains RefBackend and the `TorchConversion` dialect/passes (e.g. `TorchToLinalg.cpp`). Correspondingly, there are now 4 main testing targets paralleling the Python layering (which is reflective of the deeper underlying dependency structure) - `check-torch-mlir`: checks the `torch-mlir` pure MLIR C++ code. - `check-torch-mlir-plugin`: checks the code in `TorchPlugin` (e.g. TorchScript import) - `check-frontends-pytorch`: Checks the little code we have in `frontends/pytorch` -- mainly things related to the e2e framework itself. - `check-npcomp`: Checks the pure MLIR C++ code inside npcomp. There is a target `check-npcomp-all` that runs all of them. The `torch-mlir/build_standalone.sh` script does a standalone build of `torch-mlir`. The e2e tests (`tools/torchscript_e2e_test.sh`) are working too. The update_torch_ods script now lives in `torch-mlir/build_tools/update_torch_ods.sh` and expects a standalone build. This change also required a fix upstream related to cross-shlib Python dependencies, so we also update llvm-project to 8dca953dd39c0cd8c80decbeb38753f58a4de580 to get https://reviews.llvm.org/D109776 (no other fixes were needed for the integrate, thankfully). This completes most of the large source code changes. Next will be bringing the CI/packaging/examples back to life.
2021-09-11 02:44:38 +08:00
add_subdirectory(test)