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cmake_minimum_required ( VERSION 3.13.4 )
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# CMP0116: Ninja generators transform `DEPFILE`s from `add_custom_command()`
# New in CMake 3.20. https://cmake.org/cmake/help/latest/policy/CMP0116.html
if ( POLICY CMP0116 )
cmake_policy ( SET CMP0116 OLD )
endif ( )
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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 )
endif ( )
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#-------------------------------------------------------------------------------
# Options and settings
#-------------------------------------------------------------------------------
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set ( NPCOMP_MINIMUM_PYTHON_VERSION 3.6 )
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option ( NPCOMP_ENABLE_IREE "Enables the IREE backend (must configure location via IREE_DIR)." OFF )
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option ( NPCOMP_ENABLE_REFJIT "Enables the reference JIT backend." ON )
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set ( NPCOMP_IREE_BUILDDIR "../iree-build" CACHE STRING "If building IREE, then setting this elects to build from a source directory (versus installed package)" )
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option ( NPCOMP_ENABLE_PYTORCH "Enables PyTorch integration." OFF )
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# Turn on -gsplit-dwarf if requested in debug builds.
if ( NPCOMP_USE_SPLIT_DWARF AND
( ( C M A K E _ B U I L D _ T Y P E S T R E Q U A L " D e b u g " ) O R
( C M A K E _ B U I L D _ T Y P E S T R E Q U A L " R e l W i t h D e b I n f o " ) ) )
# Limit to clang and gcc so far. Add compilers supporting this option.
if ( CMAKE_CXX_COMPILER_ID MATCHES "Clang" OR
C M A K E _ C X X _ C O M P I L E R _ I D S T R E Q U A L " G N U " )
add_compile_options ( -gsplit-dwarf )
endif ( )
endif ( )
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#-------------------------------------------------------------------------------
# MSVC defaults
#-------------------------------------------------------------------------------
if ( MSVC )
add_compile_options (
$ < $ < C O N F I G : > : / M D >
$ < $ < C O N F I G : D e b u g > : / M D >
$ < $ < C O N F I G : R e l e a s e > : / M D >
)
endif ( )
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if ( CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR )
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# If we are not building as a part of LLVM, build NPCOMP as a standalone
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# project, including LLVM as a subdirectory. This gives us the most control
# and is used for standalone releases.
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#-------------------------------------------------------------------------------
# Project setup and globals
#-------------------------------------------------------------------------------
project ( npcomp LANGUAGES CXX C )
set ( CMAKE_C_STANDARD 11 )
set ( CMAKE_CXX_STANDARD 14 )
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#-------------------------------------------------------------------------------
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# Default and required options.
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#-------------------------------------------------------------------------------
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# CMake library generation settings.
set ( BUILD_SHARED_LIBS OFF CACHE BOOL "We are actually building a static mondo-lib" )
set ( CMAKE_PLATFORM_NO_VERSIONED_SONAME ON CACHE BOOL "Python soname linked libraries are bad" )
set ( CMAKE_VISIBILITY_INLINES_HIDDEN ON CACHE BOOL "Hide inlines" )
set ( CMAKE_CXX_VISIBILITY_PRESET hidden )
# Improved LLVM defaults for a standalone build.
set ( LLVM_ENABLE_PROJECTS mlir CACHE STRING "LLVM projects" )
set ( LLVM_ENABLE_Z3_SOLVER OFF CACHE BOOL "Disable Z3" )
set ( LLVM_ENABLE_ZLIB OFF CACHE BOOL "Disable ZLIB" )
set ( LLVM_TARGETS_TO_BUILD "host" CACHE STRING "Only build for the host" )
set ( LLVM_INCLUDE_EXAMPLES OFF CACHE BOOL "Disable examples" )
# TODO: MLIR is a "tool"
set ( LLVM_INCLUDE_TOOLS ON CACHE BOOL "Disable tools" )
set ( LLVM_INCLUDE_TESTS ON CACHE BOOL "Disable tests" )
set ( MLIR_BINDINGS_PYTHON_LOCK_VERSION ON CACHE BOOL "Link against libpython for development (should be disabled for production)" )
# Required LLVM settings.
set ( MLIR_ENABLE_BINDINGS_PYTHON ON CACHE BOOL "Enable MLIR python bindings" FORCE )
#-------------------------------------------------------------------------------
# MLIR/LLVM Build Setup
# TODO: It would be nice to have a better setup than this for sub including
# MLIR.
#-------------------------------------------------------------------------------
if ( NOT LLVM_MAIN_SRC_DIR )
set ( LLVM_MAIN_SRC_DIR "${CMAKE_CURRENT_SOURCE_DIR}/external/llvm-project/llvm" )
endif ( )
if ( NOT MLIR_MAIN_SRC_DIR )
set ( MLIR_MAIN_SRC_DIR "${LLVM_MAIN_SRC_DIR}/../mlir" )
endif ( )
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set ( LLVM_MAIN_BINARY_DIR "${CMAKE_CURRENT_BINARY_DIR}/llvm" )
set ( MLIR_MAIN_BINARY_DIR "${LLVM_MAIN_BINARY_DIR}/tools/mlir" )
set ( LLVM_INCLUDE_DIR "${LLVM_MAIN_SRC_DIR}/include" )
set ( LLVM_GENERATED_INCLUDE_DIR "${LLVM_MAIN_BINARY_DIR}/include" )
set ( MLIR_INCLUDE_DIR "${MLIR_MAIN_SRC_DIR}/include" )
set ( MLIR_GENERATED_INCLUDE_DIR "${MLIR_MAIN_BINARY_DIR}/include" )
set ( MLIR_TABLEGEN_EXE "$<TARGET_FILE:mlir-tblgen>" )
include_directories ( SYSTEM "${LLVM_INCLUDE_DIR}" )
include_directories ( SYSTEM "${LLVM_GENERATED_INCLUDE_DIR}" )
include_directories ( SYSTEM "${MLIR_INCLUDE_DIR}" )
include_directories ( SYSTEM "${MLIR_GENERATED_INCLUDE_DIR}" )
list ( APPEND CMAKE_MODULE_PATH "${MLIR_MAIN_SRC_DIR}/cmake/modules" )
list ( APPEND CMAKE_MODULE_PATH "${LLVM_MAIN_SRC_DIR}/cmake/modules" )
# Pre-configure the Python environment using the MLIR macros so that they
# are in scope and subsequent include of LLVM will match them.
include ( MLIRDetectPythonEnv )
find_package ( Python3 ${ NPCOMP_MINIMUM_PYTHON_VERSION }
C O M P O N E N T S I n t e r p r e t e r D e v e l o p m e n t N u m P y R E Q U I R E D )
message ( STATUS "Found python include dirs: ${Python3_INCLUDE_DIRS}" )
message ( STATUS "Found python libraries: ${Python3_LIBRARIES}" )
mlir_detect_pybind11_install ( )
find_package ( pybind11 2.6 CONFIG REQUIRED )
message ( STATUS "Found pybind11 v${pybind11_VERSION}: ${pybind11_INCLUDE_DIR}" )
message ( STATUS "Python prefix = '${PYTHON_MODULE_PREFIX}', "
" s u f f i x = ' $ { P Y T H O N _ M O D U L E _ S U F F I X } ' , "
" e x t e n s i o n = ' $ { P Y T H O N _ M O D U L E _ E X T E N S I O N } " )
[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
# Include LLVM_EXTERNAL_PROJECTS.
set ( LLVM_EXTERNAL_PROJECTS "iree-dialects;torch-mlir" )
Add TorchToIREE and factor out TorchConversion dialect.
This converts a basic list op (torch.prim.ListConstruct) to the IREE
dialect.
```
def forward(self, x: float):
return [x, x]
```
turns into:
```
builtin.func @forward(%arg0: !torch.float) -> !torch.list<!torch.float> {
%0 = torch.prim.ListConstruct %arg0, %arg0 : (!torch.float, !torch.float) -> !torch.list<!torch.float>
return %0 : !torch.list<!torch.float>
}
```
which turns into:
```
builtin.func @forward(%arg0: f64) -> !iree.list<f64> {
%c1 = constant 1 : index
%c0 = constant 0 : index
%c2 = constant 2 : index
%0 = iree.list.create %c2 : !iree.list<f64>
iree.list.set %0[%c0], %arg0 : !iree.list<f64>, f64
iree.list.set %0[%c1], %arg0 : !iree.list<f64>, f64
return %0 : !iree.list<f64>
}
```
As part of doing this, I realized that it was time to formalize the IR
form that we reach right before running TorchTo{Linalg,Std,...}. We now
call it the "Torch backend contract". We then lower the "Torch backend
contract" to the "npcomp backend contract", which involves the new
TorchConversion (`torch_c`) dialect, which holds ops that need to
operate on both the npcomp backend types (e.g. builtin tensors, i1, IREE
list, etc.) and the `!torch` types.
This made more sense, as I realized that if I didn't factor out
`torch_c` then the Torch dialect would have a dependency on IREE
dialect (we previously didn't notice this was an issue because we only
depended on `builtin` types), which seemed wrong to me.
Recommended review order:
- TorchToIREE.cpp / `TorchToIREE/basic.mlir`
- Look at the new structure of createTorchScriptToNpcompBackendPipeline.
It now lives in TorchConversion/Transforms/Passes.cpp and cleanly
calls into `Torch::createTorchScriptToTorchBackendPipeline` for the
frontend lowering to the Torch backend contract.
- Mechanical change extracting
`torch_c.{to,from}_{i1,i64,f64,builtin_tensor,iree_list}` into a new
TorchConversion dialect, and a few passes specific to the lowering
from the Torch backend contract to the npcomp backend contract.
- Minor fixes to TorchToLinalg.cpp to use unconverted operands (now that
we convert lists as part of operand materialization, we need to use
the original operands). Also added test for AtenMaxPool2dOp and fixed
m_TorchConstantIntList.
- TmpDeleteDeadIREELists pass. Temporary pass for deleting dead IREE lists that
are created as part of operand materialization for conv/max pool/avg pool ops
in TorchToLinalg.
2021-08-12 05:40:08 +08:00
set ( LLVM_EXTERNAL_IREE_DIALECTS_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}/external/iree-dialects" )
[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 ( LLVM_EXTERNAL_TORCH_MLIR_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}/external/torch-mlir" )
Add TorchToIREE and factor out TorchConversion dialect.
This converts a basic list op (torch.prim.ListConstruct) to the IREE
dialect.
```
def forward(self, x: float):
return [x, x]
```
turns into:
```
builtin.func @forward(%arg0: !torch.float) -> !torch.list<!torch.float> {
%0 = torch.prim.ListConstruct %arg0, %arg0 : (!torch.float, !torch.float) -> !torch.list<!torch.float>
return %0 : !torch.list<!torch.float>
}
```
which turns into:
```
builtin.func @forward(%arg0: f64) -> !iree.list<f64> {
%c1 = constant 1 : index
%c0 = constant 0 : index
%c2 = constant 2 : index
%0 = iree.list.create %c2 : !iree.list<f64>
iree.list.set %0[%c0], %arg0 : !iree.list<f64>, f64
iree.list.set %0[%c1], %arg0 : !iree.list<f64>, f64
return %0 : !iree.list<f64>
}
```
As part of doing this, I realized that it was time to formalize the IR
form that we reach right before running TorchTo{Linalg,Std,...}. We now
call it the "Torch backend contract". We then lower the "Torch backend
contract" to the "npcomp backend contract", which involves the new
TorchConversion (`torch_c`) dialect, which holds ops that need to
operate on both the npcomp backend types (e.g. builtin tensors, i1, IREE
list, etc.) and the `!torch` types.
This made more sense, as I realized that if I didn't factor out
`torch_c` then the Torch dialect would have a dependency on IREE
dialect (we previously didn't notice this was an issue because we only
depended on `builtin` types), which seemed wrong to me.
Recommended review order:
- TorchToIREE.cpp / `TorchToIREE/basic.mlir`
- Look at the new structure of createTorchScriptToNpcompBackendPipeline.
It now lives in TorchConversion/Transforms/Passes.cpp and cleanly
calls into `Torch::createTorchScriptToTorchBackendPipeline` for the
frontend lowering to the Torch backend contract.
- Mechanical change extracting
`torch_c.{to,from}_{i1,i64,f64,builtin_tensor,iree_list}` into a new
TorchConversion dialect, and a few passes specific to the lowering
from the Torch backend contract to the npcomp backend contract.
- Minor fixes to TorchToLinalg.cpp to use unconverted operands (now that
we convert lists as part of operand materialization, we need to use
the original operands). Also added test for AtenMaxPool2dOp and fixed
m_TorchConstantIntList.
- TmpDeleteDeadIREELists pass. Temporary pass for deleting dead IREE lists that
are created as part of operand materialization for conv/max pool/avg pool ops
in TorchToLinalg.
2021-08-12 05:40:08 +08:00
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# LLVM configuration.
message ( STATUS "*** ADDING LLVM ***" )
add_subdirectory (
" $ { C M A K E _ C U R R E N T _ S O U R C E _ D I R } / e x t e r n a l / l l v m - p r o j e c t / l l v m "
" $ { L L V M _ M A I N _ B I N A R Y _ D I R } "
E X C L U D E _ F R O M _ A L L )
message ( STATUS "*** LLVM DONE ***" )
set ( LLVM_RUNTIME_OUTPUT_INTDIR ${ CMAKE_BINARY_DIR } /bin )
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set ( LLVM_LIBRARY_OUTPUT_INTDIR ${ CMAKE_BINARY_DIR } /lib )
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set ( LLVM_EXTERNAL_LIT "${LLVM_MAIN_BINARY_DIR}/bin/llvm-lit" )
set ( LLVM_TOOLS_DIR "${LLVM_MAIN_BINARY_DIR}/bin" )
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# Define the default arguments to use with 'lit', and an option for the user to
# override.
set ( LIT_ARGS_DEFAULT "-sv" )
if ( MSVC_IDE OR XCODE )
set ( LIT_ARGS_DEFAULT "${LIT_ARGS_DEFAULT} --no-progress-bar" )
endif ( )
set ( LLVM_LIT_ARGS "${LIT_ARGS_DEFAULT}" CACHE STRING "Default options for lit" )
include ( TableGen )
include ( AddLLVM )
include ( AddMLIR )
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include ( AddMLIRPython )
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include ( HandleLLVMOptions )
set ( NPCOMP_BUILT_STANDALONE 1 )
else ( )
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# TODO: RE-ENABLE EXTERNAL UNIFIED BUILD
message ( FATAL_ERROR "External project builds of npcomp are currently not available" )
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# Otherwise, we are building as a part of LLVM, and we need to set up some
# variables and includes.
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# set(MLIR_MAIN_SRC_DIR ${LLVM_MAIN_SRC_DIR}/../mlir/include ) # --src-root
# set(MLIR_INCLUDE_DIR ${LLVM_MAIN_SRC_DIR}/../mlir/include ) # --includedir
# set(MLIR_TABLEGEN_OUTPUT_DIR ${CMAKE_BINARY_DIR}/tools/mlir/include)
# set(MLIR_TABLEGEN_EXE $<TARGET_FILE:mlir-tblgen>)
# include_directories(SYSTEM ${MLIR_INCLUDE_DIR})
# include_directories(SYSTEM ${MLIR_TABLEGEN_OUTPUT_DIR})
# set(BACKEND_PACKAGE_STRING "${PACKAGE_STRING}")
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endif ( )
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list ( APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/modules" )
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include ( AddNPCOMP )
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include_directories ( ${ LLVM_INCLUDE_DIRS } )
include_directories ( ${ MLIR_INCLUDE_DIRS } )
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include_directories ( ${ CMAKE_CURRENT_SOURCE_DIR } /include )
include_directories ( ${ CMAKE_CURRENT_BINARY_DIR } /include )
Add TorchToIREE and factor out TorchConversion dialect.
This converts a basic list op (torch.prim.ListConstruct) to the IREE
dialect.
```
def forward(self, x: float):
return [x, x]
```
turns into:
```
builtin.func @forward(%arg0: !torch.float) -> !torch.list<!torch.float> {
%0 = torch.prim.ListConstruct %arg0, %arg0 : (!torch.float, !torch.float) -> !torch.list<!torch.float>
return %0 : !torch.list<!torch.float>
}
```
which turns into:
```
builtin.func @forward(%arg0: f64) -> !iree.list<f64> {
%c1 = constant 1 : index
%c0 = constant 0 : index
%c2 = constant 2 : index
%0 = iree.list.create %c2 : !iree.list<f64>
iree.list.set %0[%c0], %arg0 : !iree.list<f64>, f64
iree.list.set %0[%c1], %arg0 : !iree.list<f64>, f64
return %0 : !iree.list<f64>
}
```
As part of doing this, I realized that it was time to formalize the IR
form that we reach right before running TorchTo{Linalg,Std,...}. We now
call it the "Torch backend contract". We then lower the "Torch backend
contract" to the "npcomp backend contract", which involves the new
TorchConversion (`torch_c`) dialect, which holds ops that need to
operate on both the npcomp backend types (e.g. builtin tensors, i1, IREE
list, etc.) and the `!torch` types.
This made more sense, as I realized that if I didn't factor out
`torch_c` then the Torch dialect would have a dependency on IREE
dialect (we previously didn't notice this was an issue because we only
depended on `builtin` types), which seemed wrong to me.
Recommended review order:
- TorchToIREE.cpp / `TorchToIREE/basic.mlir`
- Look at the new structure of createTorchScriptToNpcompBackendPipeline.
It now lives in TorchConversion/Transforms/Passes.cpp and cleanly
calls into `Torch::createTorchScriptToTorchBackendPipeline` for the
frontend lowering to the Torch backend contract.
- Mechanical change extracting
`torch_c.{to,from}_{i1,i64,f64,builtin_tensor,iree_list}` into a new
TorchConversion dialect, and a few passes specific to the lowering
from the Torch backend contract to the npcomp backend contract.
- Minor fixes to TorchToLinalg.cpp to use unconverted operands (now that
we convert lists as part of operand materialization, we need to use
the original operands). Also added test for AtenMaxPool2dOp and fixed
m_TorchConstantIntList.
- TmpDeleteDeadIREELists pass. Temporary pass for deleting dead IREE lists that
are created as part of operand materialization for conv/max pool/avg pool ops
in TorchToLinalg.
2021-08-12 05:40:08 +08:00
include_directories ( ${ CMAKE_CURRENT_SOURCE_DIR } /external/iree-dialects/include )
include_directories ( ${ CMAKE_CURRENT_BINARY_DIR } /llvm/tools/iree-dialects/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
include_directories ( ${ CMAKE_CURRENT_SOURCE_DIR } /external/torch-mlir/include )
include_directories ( ${ CMAKE_CURRENT_BINARY_DIR } /llvm/tools/torch-mlir/include )
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link_directories ( ${ LLVM_BUILD_LIBRARY_DIR } )
add_definitions ( ${ LLVM_DEFINITIONS } )
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set ( NPCOMP_TABLEGEN_ARGS "" )
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#-------------------------------------------------------------------------------
# Optional feature selection
#-------------------------------------------------------------------------------
if ( NPCOMP_ENABLE_REFJIT )
add_compile_definitions ( NPCOMP_ENABLE_REFJIT )
message ( STATUS "Reference JIT backend enabled" )
endif ( )
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#-------------------------------------------------------------------------------
# IREE configuration
#-------------------------------------------------------------------------------
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if ( NPCOMP_ENABLE_IREE )
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add_compile_definitions ( NPCOMP_ENABLE_IREE )
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string ( APPEND NPCOMP_TABLEGEN_ARGS "-DNPCOMP_ENABLE_IREE" )
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if ( NPCOMP_IREE_BUILDDIR )
message ( STATUS "Depending on IREE build: ${NPCOMP_IREE_BUILDDIR}" )
set ( IREE_DIR "${NPCOMP_IREE_BUILDDIR}" )
set ( IREE_FOUND 1 )
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else ( )
find_package ( IREE REQUIRED CONFIG )
endif ( )
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# This is temporary until IREE properly supports installation. We splice
# the various files into where we want them.
function ( symlink_iree src dst )
set ( full_src_path "${IREE_DIR}/${src}" )
get_filename_component ( full_src_path "${full_src_path}" ABSOLUTE )
set ( full_dst_path "${CMAKE_CURRENT_BINARY_DIR}/${dst}" )
get_filename_component ( dst_dir ${ full_dst_path } PATH )
file ( MAKE_DIRECTORY "${dst_dir}" )
execute_process (
C O M M A N D
$ { C M A K E _ C O M M A N D } - E c r e a t e _ s y m l i n k " $ { f u l l _ s r c _ p a t h } " " $ { f u l l _ d s t _ p a t h } "
R E S U L T _ V A R I A B L E r e s u l t
)
if ( NOT ${ result } EQUAL 0 )
message ( FATAL_ERROR "Could not symlink iree file: ${full_src_path} -> ${full_dst_path}" )
endif ( )
endfunction ( )
symlink_iree ( iree/tools/iree-translate python/npcomp/compiler/generic/backend/iree-translate )
symlink_iree ( bindings/python/pyiree/rt python/pyiree/rt )
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endif ( )
#-------------------------------------------------------------------------------
# Directory setup
#-------------------------------------------------------------------------------
set ( MLIR_NPCOMP_SOURCE_DIR ${ CMAKE_CURRENT_SOURCE_DIR } )
set ( MLIR_NPCOMP_BINARY_DIR ${ CMAKE_CURRENT_BINARY_DIR } )
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set ( MLIR_NPCOMP_PYTHON_PACKAGES_DIR ${ CMAKE_CURRENT_BINARY_DIR } /python_packages )
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add_custom_target ( check-npcomp )
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add_custom_target ( check-npcomp-all )
add_dependencies ( check-npcomp-all check-npcomp )
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add_subdirectory ( include/npcomp )
add_subdirectory ( lib )
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add_subdirectory ( python )
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add_subdirectory ( test )
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add_subdirectory ( tools )
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if ( NPCOMP_ENABLE_PYTORCH )
message ( STATUS "Adding PyTorch frontent support..." )
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add_subdirectory ( frontends/pytorch )
endif ( )
