Commit Graph

60 Commits

Author SHA1 Message Date
River Riddle ee1d447e5f [mlir][NFC] Move Translation.h to a Tools/mlir-translate directory
Translation.h is currently awkwardly shoved into the top-level mlir, even though it is
specific to the mlir-translate tool. This commit moves it to a new Tools/mlir-translate
directory, which is intended for libraries used to implement tools. It also splits the
translate registry from the main entry point, to more closely mirror what mlir-opt
does.

Differential Revision: https://reviews.llvm.org/D121026
2022-03-07 01:05:38 -08:00
Stephen Neuendorffer b0dce6b37f Revert "[RFC] Factor out repetitive cmake patterns for llvm-style projects"
This reverts commit e9b87f43bd.

There are issues with macros generating macros without an obvious simple fix
so I'm going to revert this and try something different.
2020-10-04 15:17:34 -07:00
Stephen Neuendorffer e9b87f43bd [RFC] Factor out repetitive cmake patterns for llvm-style projects
New projects (particularly out of tree) have a tendency to hijack the existing
llvm configuration options and build targets (add_llvm_library,
add_llvm_tool).  This can lead to some confusion.

1) When querying a configuration variable, do we care about how LLVM was
configured, or how these options were configured for the out of tree project?
2) LLVM has lots of defaults, which are easy to miss
(e.g. LLVM_BUILD_TOOLS=ON).  These options all need to be duplicated in the
CMakeLists.txt for the project.

In addition, with LLVM Incubators coming online, we need better ways for these
incubators to do things the "LLVM way" without alot of futzing.  Ideally, this
would happen in a way that eases importing into the LLVM monorepo when
projects mature.

This patch creates some generic infrastructure in llvm/cmake/modules and
refactors MLIR to use this infrastructure.  This should expand to include
add_xxx_library, which is by far the most complicated bit of building a
project correctly, since it has to deal with lots of shared library
configuration bits.  (MLIR currently hijacks the LLVM infrastructure for
building libMLIR.so, so this needs to get refactored anyway.)

Differential Revision: https://reviews.llvm.org/D85140
2020-10-03 17:12:35 -07:00
Marius Brehler c633842f13 [mlir] Fix includes in mlir-translate
Drops the include on InitAllDialects.h, as dialects are now initialized in the translation passes.

Differential Revision: https://reviews.llvm.org/D87129
2020-09-04 15:22:38 +02:00
Mehdi Amini f164534ca8 Add a `dialect_registration` callback for "translations" registered with mlir-translate
This will allow out-of-tree translation to register the dialects they expect
to see in their input, on the model of getDependentDialects() for passes.

Differential Revision: https://reviews.llvm.org/D86409
2020-08-23 01:00:39 +00:00
Mehdi Amini 96cb8cdeb0 Refactor `mlir-translate` to extract the `main()` logic in a helper on the model of `MlirOptMain()` (NFC)
Differential Revision: https://reviews.llvm.org/D86408
2020-08-23 01:00:31 +00:00
Mehdi Amini f9dc2b7079 Separate the Registration from Loading dialects in the Context
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.

This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.

To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.

1) For passes, you need to override the method:

virtual void getDependentDialects(DialectRegistry &registry) const {}

and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.

2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.

3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:

  mlir::DialectRegistry registry;
  registry.insert<mlir::standalone::StandaloneDialect>();
  registry.insert<mlir::StandardOpsDialect>();

Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:

  mlir::registerAllDialects(registry);

4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()

Differential Revision: https://reviews.llvm.org/D85622
2020-08-19 01:19:03 +00:00
Mehdi Amini e75bc5c791 Revert "Separate the Registration from Loading dialects in the Context"
This reverts commit d14cf45735.
The build is broken with GCC-5.
2020-08-19 01:19:03 +00:00
Mehdi Amini d14cf45735 Separate the Registration from Loading dialects in the Context
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.

This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.

To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.

1) For passes, you need to override the method:

virtual void getDependentDialects(DialectRegistry &registry) const {}

and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.

2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.

3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:

  mlir::DialectRegistry registry;
  registry.insert<mlir::standalone::StandaloneDialect>();
  registry.insert<mlir::StandardOpsDialect>();

Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:

  mlir::registerAllDialects(registry);

4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()

Differential Revision: https://reviews.llvm.org/D85622
2020-08-18 23:23:56 +00:00
Mehdi Amini d84fe55e0d Revert "Separate the Registration from Loading dialects in the Context"
This reverts commit e1de2b7550.
Broke a build bot.
2020-08-18 22:16:34 +00:00
Mehdi Amini e1de2b7550 Separate the Registration from Loading dialects in the Context
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.

This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.

To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.

1) For passes, you need to override the method:

virtual void getDependentDialects(DialectRegistry &registry) const {}

and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.

2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.

3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:

  mlir::DialectRegistry registry;
  mlir::registerDialect<mlir::standalone::StandaloneDialect>();
  mlir::registerDialect<mlir::StandardOpsDialect>();

Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:

  mlir::registerAllDialects(registry);

4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
2020-08-18 21:14:39 +00:00
Mehdi Amini 25ee851746 Revert "Separate the Registration from Loading dialects in the Context"
This reverts commit 2056393387.

Build is broken on a few bots
2020-08-15 09:21:47 +00:00
Mehdi Amini 2056393387 Separate the Registration from Loading dialects in the Context
This changes the behavior of constructing MLIRContext to no longer load globally registered dialects on construction. Instead Dialects are only loaded explicitly on demand:
- the Parser is lazily loading Dialects in the context as it encounters them during parsing. This is the only purpose for registering dialects and not load them in the context.
- Passes are expected to declare the dialects they will create entity from (Operations, Attributes, or Types), and the PassManager is loading Dialects into the Context when starting a pipeline.

This changes simplifies the configuration of the registration: a compiler only need to load the dialect for the IR it will emit, and the optimizer is self-contained and load the required Dialects. For example in the Toy tutorial, the compiler only needs to load the Toy dialect in the Context, all the others (linalg, affine, std, LLVM, ...) are automatically loaded depending on the optimization pipeline enabled.

Differential Revision: https://reviews.llvm.org/D85622
2020-08-15 08:07:31 +00:00
Mehdi Amini ba92dadf05 Revert "Separate the Registration from Loading dialects in the Context"
This was landed by accident, will reland with the right comments
addressed from the reviews.
Also revert dependent build fixes.
2020-08-15 07:35:10 +00:00
Mehdi Amini ebf521e784 Separate the Registration from Loading dialects in the Context
This changes the behavior of constructing MLIRContext to no longer load globally registered dialects on construction. Instead Dialects are only loaded explicitly on demand:
- the Parser is lazily loading Dialects in the context as it encounters them during parsing. This is the only purpose for registering dialects and not load them in the context.
- Passes are expected to declare the dialects they will create entity from (Operations, Attributes, or Types), and the PassManager is loading Dialects into the Context when starting a pipeline.

This changes simplifies the configuration of the registration: a compiler only need to load the dialect for the IR it will emit, and the optimizer is self-contained and load the required Dialects. For example in the Toy tutorial, the compiler only needs to load the Toy dialect in the Context, all the others (linalg, affine, std, LLVM, ...) are automatically loaded depending on the optimization pipeline enabled.
2020-08-14 09:40:27 +00:00
Alex Zinenko b2ab375d1f [mlir] use the new stateful LLVM type translator by default
Previous type model in the LLVM dialect did not support identified structure
types properly and therefore could use stateless translations implemented as
free functions. The new model supports identified structs and must keep track
of the identified structure types present in the target context (LLVMContext or
MLIRContext) to avoid creating duplicate structs due to LLVM's type
auto-renaming. Expose the stateful type translation classes and use them during
translation, storing the state as part of ModuleTranslation.

Drop the test type translation mechanism that is no longer necessary and update
the tests to exercise type translation as part of the main translation flow.

Update the code in vector-to-LLVM dialect conversion that relied on stateless
translation to use the new class in a stateless manner.

Reviewed By: rriddle

Differential Revision: https://reviews.llvm.org/D85297
2020-08-06 00:36:33 +02:00
Alex Zinenko 4e491570b5 [mlir] Remove LLVMTypeTestDialect
This dialect was introduced during the bring-up of the new LLVM dialect type
system for testing purposes. The main LLVM dialect now uses the new type system
and the test dialect is no longer necessary, so remove it.

Reviewed By: rriddle

Differential Revision: https://reviews.llvm.org/D85224
2020-08-05 14:39:36 +02:00
Alex Zinenko d4fbbab2e4 [mlir] translate types between MLIR LLVM dialect and LLVM IR
With new LLVM dialect type modeling, the dialect types no longer wrap LLVM IR
types. Therefore, they need to be translated to and from LLVM IR during export
and import. Introduce the relevant functionality for translating types. It is
currently exercised by an ad-hoc type translation roundtripping test that will
be subsumed by the actual translation test when the type system transition is
complete.

Depends On D84339

Reviewed By: herhut

Differential Revision: https://reviews.llvm.org/D85019
2020-08-04 13:42:43 +02:00
Stephen Neuendorffer 5469f434bb [MLIR] Reapply: Adjust libMLIR building to more closely follow libClang
This reverts commit ab1ca6e60f.
2020-05-04 20:47:57 -07:00
Stephen Neuendorffer ab1ca6e60f Revert "[MLIR] Adjust libMLIR building to more closely follow libClang"
This reverts commit 4f0f436749.

This seems to show some compile dependence problems, and also breaks flang.
2020-05-04 12:40:12 -07:00
Valentin Churavy 4f0f436749 [MLIR] Adjust libMLIR building to more closely follow libClang
- Exports MLIR targets to be used out-of-tree.
- mimicks `add_clang_library` and `add_flang_library`.
- Fixes libMLIR.so

After https://reviews.llvm.org/D77515 libMLIR.so was no longer containing
any object files. We originally had a cludge there that made it work with
the static initalizers and when switchting away from that to the way the
clang shlib does it, I noticed that MLIR doesn't create a `obj.{name}` target,
and doesn't export it's targets to `lib/cmake/mlir`.

This is due to MLIR using `add_llvm_library` under the hood, which adds
the target to `llvmexports`.

Differential Revision: https://reviews.llvm.org/D78773

[MLIR] Fix libMLIR.so and LLVM_LINK_LLVM_DYLIB

Primarily, this patch moves all mlir references to LLVM libraries into
either LLVM_LINK_COMPONENTS or LINK_COMPONENTS.  This enables magic in
the llvm cmake files to automatically replace reference to LLVM components
with references to libLLVM.so when necessary.  Among other things, this
completes fixing libMLIR.so, which has been broken for some configurations
since D77515.

Unlike previously, the pattern is now that mlir libraries should almost
always use add_mlir_library.  Previously, some libraries still used
add_llvm_library.  However, this confuses the export of targets for use
out of tree because libraries specified with add_llvm_library are exported
by LLVM.  Instead users which don't need/can't be linked into libMLIR.so
can specify EXCLUDE_FROM_LIBMLIR

A common error mode is linking with LLVM libraries outside of LINK_COMPONENTS.
This almost always results in symbol confusion or multiply defined options
in LLVM when the same object file is included as a static library and
as part of libLLVM.so.  To catch these errors more directly, there's now
mlir_check_all_link_libraries.

To simplify usage of add_mlir_library, we assume that all mlir
libraries depend on LLVMSupport, so it's not necessary to separately specify
it.

tested with:
BUILD_SHARED_LIBS=on,
BUILD_SHARED_LIBS=off + LLVM_BUILD_LLVM_DYLIB,
BUILD_SHARED_LIBS=off + LLVM_BUILD_LLVM_DYLIB + LLVM_LINK_LLVM_DYLIB.

By: Stephen Neuendorffer <stephen.neuendorffer@xilinx.com>
Differential Revision: https://reviews.llvm.org/D79067

[MLIR] Move from using target_link_libraries to LINK_LIBS

This allows us to correctly generate dependencies for derived targets,
such as targets which are created for object libraries.

By: Stephen Neuendorffer <stephen.neuendorffer@xilinx.com>
Differential Revision: https://reviews.llvm.org/D79243

Three commits have been squashed to avoid intermediate build breakage.
2020-05-04 11:40:46 -07:00
Denis Khalikov 29b955f97c [mlir][spirv] Handle debug information during (de)serialization.
Summary:
This is an initial version, currently supports OpString and OpLine
for autogenerated operations during (de)serialization.

Differential Revision: https://reviews.llvm.org/D79091
2020-05-01 14:11:54 +03:00
River Riddle 8938dea44a [mlir][IR] Manually register command line options for MLIRContext and AsmPrinter
Summary: This revision makes the registration of command line options for these two files manual with `registerMLIRContextCLOptions` and `registerAsmPrinterCLOptions` methods. This removes the last remaining static constructors within lib/.

Differential Revision: https://reviews.llvm.org/D77960
2020-04-11 23:13:00 -07:00
Stephen Neuendorffer 4c18e1d3af [MLIR] add cmake abstraction for translation libraries
Differential Revision: https://reviews.llvm.org/D77926
2020-04-11 22:02:16 -07:00
Jonathan Roelofs 223154d267 [mlir] Remove need for static global ctors from mlir-translate
Summary: https://bugs.llvm.org/show_bug.cgi?id=45436

Reviewers: mehdi_amini, mravishankar, antiagainst, rriddle, stephenneuendorffer

Reviewed By: mehdi_amini, rriddle, stephenneuendorffer

Subscribers: frgossen, stephenneuendorffer, jholewinski, mgorny, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, bader, grosul1, llvm-commits

Tags: #llvm

Differential Revision: https://reviews.llvm.org/D77515
2020-04-08 16:52:33 -06:00
River Riddle 74d44c43e8 [mlir] Refactor and cleanup the translation facilities.
Summary:
This revision performs several cleanups on the translation infra:
* Removes the TranslateCLParser library and consolidates into Translation
  - This was a weird library that existed in Support, and didn't really justify being a standalone library.
* Cleans up the internal registration and consolidates all of the translation functions within one registry.

Differential Revision: https://reviews.llvm.org/D77514
2020-04-05 16:21:21 -07:00
River Riddle 79afdfab9a [mlir] Change the default of `mlir-print-op-on-diagnostic` to true
Summary: It is a very common user trap to think that the location printed along with the diagnostic is the same as the current operation that caused the error. This revision changes the behavior to always print the current operation, except for when diagnostics are being verified. This is achieved by moving the command line flags in IR/ to be options on the MLIRContext.

Differential Revision: https://reviews.llvm.org/D77095
2020-04-03 19:02:51 -07:00
Mehdi Amini bab5bcf8fd Add a flag on the context to protect against creation of operations in unregistered dialects
Differential Revision: https://reviews.llvm.org/D76903
2020-03-30 19:37:31 +00:00
Nicolas Vasilache 462db62053 [mlir][AVX512] Start a primitive AVX512 dialect
The Vector Dialect [document](https://mlir.llvm.org/docs/Dialects/Vector/) discusses the vector abstractions that MLIR supports and the various tradeoffs involved.

One of the layer that is missing in OSS atm is the Hardware Vector Ops (HWV) level.

This revision proposes an AVX512-specific to add a new Dialect/Targets/AVX512 Dialect that would directly target AVX512-specific intrinsics.

Atm, we rely too much on LLVM’s peephole optimizer to do a good job from small insertelement/extractelement/shufflevector. In the future, when possible, generic abstractions such as VP intrinsics should be preferred.

The revision will allow trading off HW-specific vs generic abstractions in MLIR.

Differential Revision: https://reviews.llvm.org/D75987
2020-03-20 14:11:57 -04:00
Stephen Neuendorffer 5869552821 [MLIR] Refactor handling of dialect libraries
Instead of creating extra libraries we don't really need, collect a
list of all dialects and use that instead.

Differential Revision: https://reviews.llvm.org/D75221
2020-02-28 11:35:16 -08:00
Mehdi Amini c64770506b Remove static registration for dialects, and the "alwayslink" hack for passes
In the previous state, we were relying on forcing the linker to include
all libraries in the final binary and the global initializer to self-register
every piece of the system. This change help moving away from this model, and
allow users to compose pieces more freely. The current change is only "fixing"
the dialect registration and avoiding relying on "whole link" for the passes.
The translation is still relying on the global registry, and some refactoring
is needed to make this all more convenient.

Differential Revision: https://reviews.llvm.org/D74461
2020-02-12 09:13:02 +00:00
Kern Handa b8004b7308 [mlir] Mark the MLIR tools for installation in CMake
This binplaces `mlir-translate`, `mlir-cuda-runner`, and `mlir-cpu-runner` when building the CMake install target.

Differential Revision: https://reviews.llvm.org/D73986
2020-02-05 03:42:57 +00:00
Mehdi Amini 308571074c Mass update the MLIR license header to mention "Part of the LLVM project"
This is an artifact from merging MLIR into LLVM, the file headers are
now aligned with the rest of the project.
2020-01-26 03:58:30 +00:00
Mehdi Amini 56222a0694 Adjust License.txt file to use the LLVM license
PiperOrigin-RevId: 286906740
2019-12-23 15:33:37 -08:00
Uday Bondhugula 613ace94f2 Drop unnecessary dependences from mlir-translate
Closes tensorflow/mlir#243

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/243 from bondhugula:patch-2 fb682996efde001189414a4c7aa59ce42ace7831
PiperOrigin-RevId: 281167834
2019-11-18 16:44:43 -08:00
Alex Zinenko 09e8e7107a mlir-translate: support -verify-diagnostics
MLIR translation tools can emit diagnostics and we want to be able to check if
it is indeed the case in tests. Reuse the source manager error handlers
provided for mlir-opt to support the verification in mlir-translate. This
requires us to change the signature of the functions that are registered to
translate sources to MLIR: it now takes a source manager instead of a memory
buffer.

PiperOrigin-RevId: 279132972
2019-11-07 11:42:46 -08:00
Deven Desai fee40fef5c [ROCm] Adding ROCDL Dialect.
This commit introduces the ROCDL Dialect (i.e. the ROCDL ops + the code to lower those ROCDL ops to LLWM intrinsics/functions). Think of ROCDL Dialect as analogous to the NVVM Dialect, but for AMD GPUs. This patch contains just the essentials needed to get a simple example up and running. We expect to make further additions to the ROCDL Dialect.

This is the first of 3 commits, the follow-up will be:
 * add a pass that lowers GPU Dialect to ROCDL Dialect
 * add a "mlir-rocm-runner" utility

Closes tensorflow/mlir#146

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/146 from deven-amd:deven-rocdl-dialect e78e8005c75a78912631116c78dc844fcc4b0de9
PiperOrigin-RevId: 271511259
2019-09-27 00:22:32 -07:00
Lei Zhang 0e7edcfe7e Let mlir-translate support -split-input-file
Similar to mlir-opt, having a -split-input-file mode is quite useful
in mlir-translate. It allows to put logically related tests in the
same test file for better organization.

PiperOrigin-RevId: 270805467
2019-09-23 18:18:23 -07:00
Lei Zhang b00a522b80 Change MLIR translation functions signature
This CL changes translation functions to take MemoryBuffer
as input and raw_ostream as output. It is generally better to
avoid handling files directly in a library (unless the library
is specifically for file manipulation) and we can unify all
file handling to the mlir-translate binary itself.

PiperOrigin-RevId: 269625911
2019-09-17 12:16:45 -07:00
Jacques Pienaar 33a8642f53 InitLLVM already initializes PrettyStackTraceProgram
Remove extra PrettyStackTraceProgram and use InitLLVM consistently.

PiperOrigin-RevId: 264041205
2019-08-18 11:32:52 -07:00
Jacques Pienaar d4cf54f2c1 Split out TranslateClParser and add new parse method that reuses SourceMgr.
Split out class to command line parser for translate methods into standalone
class. Similar to splitting up mlir-opt to reuse functionality with different
initialization.

PiperOrigin-RevId: 255225790
2019-06-26 11:14:45 -07:00
Lei Zhang 8f77d2afed [spirv] Basic serializer and deserializer
This CL adds the basic SPIR-V serializer and deserializer for converting
SPIR-V module into the binary format and back. Right now only an empty
module with addressing model and memory model is supported; (de)serialize
other components will be added gradually with subsequent CLs.

The purpose of this library is to enable importing SPIR-V binary modules
to run transformations on them and exporting SPIR-V modules to be consumed
by execution environments. The focus is transformations, which inevitably
means changes to the binary module; so it is not designed to be a general
tool for investigating the SPIR-V binary module and does not guarantee
roundtrip equivalence (at least for now).

PiperOrigin-RevId: 254473019
2019-06-22 09:17:21 -07:00
Jacques Pienaar c59538977e Add keywords in target_link_libraries post add_llvm_executable.
--

PiperOrigin-RevId: 250704528
2019-06-01 20:10:42 -07:00
River Riddle 11e485ca19 Replace usages of 'add_executable' with 'add_llvm_executable'.
--

PiperOrigin-RevId: 250691487
2019-06-01 20:10:32 -07:00
Jacques Pienaar f0ee052d9e Use SourceMgrDiagnosticHandler in mlir-translate for translations from MLIR input.
Report errors using the file and line location using SourceMgr's diagnostic reporting. Reduce some horizontal white spacing too.

--

PiperOrigin-RevId: 250193646
2019-06-01 20:04:32 -07:00
Smit Hinsu 0bd0571e72 Reserve the required capacity to avoid pointer invalidations for translation functions
--

PiperOrigin-RevId: 245992152
2019-05-06 08:23:04 -07:00
Stephan Herhut 5d7231d812 Add transformation of the NVVM dialect to an LLVM module. Only handles
the generation of intrinsics out of NVVM index ops for now.

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PiperOrigin-RevId: 245933152
2019-05-06 08:22:14 -07:00
River Riddle 0be6369176 Update the Function and Module verifiers to return LogicalResult instead of bool.
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PiperOrigin-RevId: 241553930
2019-04-02 13:40:20 -07:00
Mehdi Amini b3a407fa68 Fix MacOS build
This is making up for some differences in standard library and linker flags.
    It also get rid of the requirement to build with RTTI.

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PiperOrigin-RevId: 241348845
2019-04-01 11:00:30 -07:00
Jacques Pienaar 1273af232c Add build files and update README.
* Add initial version of build files;
    * Update README with instructions to download and build MLIR from github;

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PiperOrigin-RevId: 241102092
2019-03-30 11:23:22 -07:00