It may be necessary for interface methods to process or return variables with
the interface class type, in particular for attribute and type interfaces that
can return modified attributes and types that implement the same interface.
However, the code generated by ODS in this case would not compile because the
signature (and the body if provided) appear in the definition of the Model
class and before the interface class, which derives from the Model. Change the ODS
interface method generator to emit only method declarations in the Model class
itself, and emit method definitions after the interface class. Mark as "inline"
since their definitions are still emitted in the header and are no longer
implicitly inline. Add a forward declaration of the interface class before the
Concept+Model classes to make the class name usable in declarations.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D91499
In ODS, attributes of an operation can be provided as a part of the "arguments"
field, together with operands. Such attributes are accepted by the op builder
and have accessors generated.
Implement similar functionality for ODS-generated op-specific Python bindings:
the `__init__` method now accepts arguments together with operands, in the same
order as in the ODS `arguments` field; the instance properties are introduced
to OpView classes to access the attributes.
This initial implementation accepts and returns instances of the corresponding
attribute class, and not the underlying values since the mapping scheme of the
value types between C++, C and Python is not yet clear. Default-valued
attributes are not supported as that would require Python to be able to parse
C++ literals.
Since attributes in ODS are tightely related to the actual C++ type system,
provide a separate Tablegen file with the mapping between ODS storage type for
attributes (typically, the underlying C++ attribute class), and the
corresponding class name. So far, this might look unnecessary since all names
match exactly, but this is not necessarily the cases for non-standard,
out-of-tree attributes, which may also be placed in non-default namespaces or
Python modules. This also allows out-of-tree users to generate Python bindings
without having to modify the bindings generator itself. Storage type was
preferred over the Tablegen "def" of the attribute class because ODS
essentially encodes attribute _constraints_ rather than classes, e.g. there may
be many Tablegen "def"s in the ODS that correspond to the same attribute type
with additional constraints
The presence of the explicit mapping requires the change in the .td file
structure: instead of just calling the bindings generator directly on the main
ODS file of the dialect, it becomes necessary to create a new file that
includes the main ODS file of the dialect and provides the mapping for
attribute types. Arguably, this approach offers better separability of the
Python bindings in the build system as the main dialect no longer needs to know
that it is being processed by the bindings generator.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D91542
These includes have been deprecated in favor of BuiltinDialect.h, which contains the definitions of ModuleOp and FuncOp.
Differential Revision: https://reviews.llvm.org/D91572
This replaces the old type decomposition logic that was previously mixed
into bufferization, and makes it easily accessible.
This also deletes TestFinalizingBufferize, because after we remove the type
decomposition, it doesn't do anything that is not already provided by
func-bufferize.
Differential Revision: https://reviews.llvm.org/D90899
The tokens are already handled by the lexer. This revision exposes them
through the parser interface.
This revision also adds missing functions for question mark parsing and
completes the list of valid punctuation tokens in the documentation.
Differential Revision: https://reviews.llvm.org/D90907
Add an ODS-backed generator of default builders. This currently does not
support operation with attribute arguments, for which the builder is
just ignored. Attribute support will be introduced separately for
builders and accessors.
Default builders are always generated with the same number of result and
operand groups as the ODS specification, i.e. one group per each operand
or result. Optional elements accept None but cannot be omitted. Variadic
groups accept iterable objects and cannot be replaced with a single
object.
For some operations, it is possible to infer the result type given the
traits, but most traits rely on inline pieces of C++ that we cannot
(yet) forward to Python bindings. Since the Ops where the inference is
possible (having the `SameOperandAndResultTypes` trait or
`TypeMatchesWith` without transform field) are a small minority, they
also require the result type to make the builder syntax more consistent.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D91190
I would like to use this for D90589 to switch std.alloc to assemblyFormat.
Hopefully it will be useful in other places as well.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D91068
This only exposes the ability to round-trip a textual pipeline at the
moment.
To exercise it, we also bind the libTransforms in a new Python extension. This
does not include any interesting bindings, but it includes all the
mechanism to add separate native extensions and load them dynamically.
As such passes in libTransforms are only registered after `import
mlir.transforms`.
To support this global registration, the TableGen backend is also
extended to bind to the C API the group registration for passes.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D90819
Introduce an ODS/Tablegen backend producing Op wrappers for Python bindings
based on the ODS operation definition. Usage:
mlir-tblgen -gen-python-op-bindings -Iinclude <path/to/Ops.td> \
-bind-dialect=<dialect-name>
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D90960
The pass combines patterns of ExpandAtomic, ExpandMemRefReshape,
StdExpandDivs passes. The pass is meant to legalize STD for conversion to LLVM.
Differential Revision: https://reviews.llvm.org/D91082
* Wires them in the same way that peer-dialect test passes are registered.
* Fixes the build for -DLLVM_INCLUDE_TESTS=OFF.
Differential Revision: https://reviews.llvm.org/D91022
We were discussing on discord regarding the need for extension-based systems like Python to dynamically link against MLIR (or else you can only have one extension that depends on it). Currently, when I set that up, I piggy-backed off of the flag that enables build libLLVM.so and libMLIR.so and depended on libMLIR.so from the python extension if shared library building was enabled. However, this is less than ideal.
In the current setup, libMLIR.so exports both all symbols from the C++ API and the C-API. The former is a kitchen sink and the latter is curated. We should be splitting them and for things that are properly factored to depend on the C-API, they should have the option to *only* depend on the C-API, and we should build that shared library no matter what. Its presence isn't just an optimization: it is a key part of the system.
To do this right, I needed to:
* Introduce visibility macros into mlir-c/Support.h. These should work on both *nix and windows as-is.
* Create a new libMLIRPublicAPI.so with just the mlir-c object files.
* Compile the C-API with -fvisibility=hidden.
* Conditionally depend on the libMLIR.so from libMLIRPublicAPI.so if building libMLIR.so (otherwise, also links against the static libs and will produce a mondo libMLIRPublicAPI.so).
* Disable re-exporting of static library symbols that come in as transitive deps.
This gives us a dynamic linked C-API layer that is minimal and should work as-is on all platforms. Since we don't support libMLIR.so building on Windows yet (and it is not very DLL friendly), this will fall back to a mondo build of libMLIRPublicAPI.so, which has its uses (it is also the most size conscious way to go if you happen to know exactly what you need).
Sizes (release/stripped, Ubuntu 20.04):
Shared library build:
libMLIRPublicAPI.so: 121Kb
_mlir.cpython-38-x86_64-linux-gnu.so: 1.4Mb
mlir-capi-ir-test: 135Kb
libMLIR.so: 21Mb
Static build:
libMLIRPublicAPI.so: 5.5Mb (since this is a "static" build, this includes the MLIR implementation as non-exported code).
_mlir.cpython-38-x86_64-linux-gnu.so: 1.4Mb
mlir-capi-ir-test: 44Kb
Things like npcomp and circt which bring their own dialects/transforms/etc would still need the shared library build and code that links against libMLIR.so (since it is all C++ interop stuff), but hopefully things that only depend on the public C-API can just have the one narrow dep.
I spot checked everything with nm, and it looks good in terms of what is exporting/importing from each layer.
I'm not in a hurry to land this, but if it is controversial, I'll probably split off the Support.h and API visibility macro changes, since we should set that pattern regardless.
Reviewed By: mehdi_amini, benvanik
Differential Revision: https://reviews.llvm.org/D90824
This functionality is superceded by BufferResultsToOutParams pass (see
https://reviews.llvm.org/D90071) for users the require buffers to be
out-params. That pass should be run immediately after all tensors are gone from
the program (before buffer optimizations and deallocation insertion), such as
immediately after a "finalizing" bufferize pass.
The -test-finalizing-bufferize pass now defaults to what used to be the
`allowMemrefFunctionResults=true` flag. and the
finalizing-bufferize-allowed-memref-results.mlir file is moved
to test/Transforms/finalizing-bufferize.mlir.
Differential Revision: https://reviews.llvm.org/D90778
TestDialect has many operations and they all live in ::mlir namespace.
Sometimes it is not clear whether the ops used in the code for the test passes
belong to Standard or to Test dialects.
Also, with this change it is easier to understand what test passes registered
in mlir-opt are actually passes in mlir/test.
Differential Revision: https://reviews.llvm.org/D90794
The LinalgDependenceGraph and alias analysis provide the necessary analysis for the Linalg fusion on buffers case.
However this is not enough for linalg on tensors which require proper memory effects to play nicely with DCE and other transformations.
This revision adds side effects to Linalg ops that were previously missing and has 2 consequences:
1. one example in the copy removal pass now fails since the linalg.generic op has side effects and the pass does not perform alias analysis / distinguish between reads and writes.
2. a few examples in fusion-tensor.mlir need to return the resulting tensor otherwise DCE automatically kicks in as part of greedy pattern application.
Differential Revision: https://reviews.llvm.org/D90762
This is exposing the basic functionalities (create, nest, addPass, run) of
the PassManager through the C API in the new header: `include/mlir-c/Pass.h`.
In order to exercise it in the unit-test, a basic TableGen backend is
also provided to generate a simple C wrapper around the pass
constructor. It is used to expose the libTransforms passes to the C API.
Reviewed By: stellaraccident, ftynse
Differential Revision: https://reviews.llvm.org/D90667
BufferPlacement is no longer part of bufferization. However, this test
is an important test of "finalizing" bufferize passes.
A "finalizing" bufferize conversion is one that performs a "full"
conversion and expects all tensors to be gone from the program. This in
particular involves rewriting funcs (including block arguments of the
contained region), calls, and returns. The unique property of finalizing
bufferization passes is that they cannot be done via a local
transformation with suitable materializations to ensure composability
(as other bufferization passes do). For example, if a call is
rewritten, the callee needs to be rewritten otherwise the IR will end up
invalid. Thus, finalizing bufferization passes require an atomic change
to the entire program (e.g. the whole module).
This new designation makes it clear also that it shouldn't be testing
bufferization of linalg ops, so the tests have been updated to not use
linalg.generic ops. (linalg.copy is still used as the "copy" op for
copying into out-params)
Differential Revision: https://reviews.llvm.org/D89979
This commit adds a new library that merges/combines a number of spv
modules into a combined one. The library has a single entry point:
combine(...).
To combine a number of MLIR spv modules, we move all the module-level ops
from all the input modules into one big combined module. To that end, the
combination process can proceed in 2 phases:
(1) resolving conflicts between pairs of ops from different modules
(2) deduplicate equivalent ops/sub-ops in the merged module. (TODO)
This patch implements only the first phase.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D90477
This commit adds a new library that merges/combines a number of spv
modules into a combined one. The library has a single entry point:
combine(...).
To combine a number of MLIR spv modules, we move all the module-level ops
from all the input modules into one big combined module. To that end, the
combination process can proceed in 2 phases:
(1) resolving conflicts between pairs of ops from different modules
(2) deduplicate equivalent ops/sub-ops in the merged module. (TODO)
This patch implements only the first phase.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D90477
This commit adds a new library that merges/combines a number of spv
modules into a combined one. The library has a single entry point:
combine(...).
To combine a number of MLIR spv modules, we move all the module-level ops
from all the input modules into one big combined module. To that end, the
combination process can proceed in 2 phases:
(1) resolving conflicts between pairs of ops from different modules
(2) deduplicate equivalent ops/sub-ops in the merged module. (TODO)
This patch implements only the first phase.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D90022
Linalg "tile-and-fuse" is currently exposed as a Linalg pass "-linalg-fusion" but only the mechanics of the transformation are currently relevant.
Instead turn it into a "-test-linalg-greedy-fusion" pass which performs canonicalizations to enable more fusions to compose.
This allows dropping the OperationFolder which is not meant to be used with the pattern rewrite infrastructure.
Differential Revision: https://reviews.llvm.org/D90394
When compiling for code size, the use of a vtable causes a destructor(and constructor in certain cases) to be generated for the class. Interface models don't need a complex constructor or a destructor, so this can lead to many megabytes of code size increase(even in opt). This revision switches to a simpler struct of function pointers approach that accomplishes the same API requirements as before. This change requires no updates to user code, or any other code aside from the generator, as the user facing API is still exactly the same.
Differential Revision: https://reviews.llvm.org/D90085
A recent commit introduced a new syntax for specifying builder arguments in
ODS, which is better amenable to automated processing, and deprecated the old
form. Transition all dialects as well as Linalg ODS generator to use the new
syntax.
Add a deprecation notice to ODS generator.
Reviewed By: rriddle, jpienaar
Differential Revision: https://reviews.llvm.org/D90038
This patch introduces a SPIR-V runner. The aim is to run a gpu
kernel on a CPU via GPU -> SPIRV -> LLVM conversions. This is a first
prototype, so more features will be added in due time.
- Overview
The runner follows similar flow as the other runners in-tree. However,
having converted the kernel to SPIR-V, we encode the bind attributes of
global variables that represent kernel arguments. Then SPIR-V module is
converted to LLVM. On the host side, we emulate passing the data to device
by creating in main module globals with the same symbolic name as in kernel
module. These global variables are later linked with ones from the nested
module. We copy data from kernel arguments to globals, call the kernel
function from nested module and then copy the data back.
- Current state
At the moment, the runner is capable of running 2 modules, nested one in
another. The kernel module must contain exactly one kernel function. Also,
the runner supports rank 1 integer memref types as arguments (to be scaled).
- Enhancement of JitRunner and ExecutionEngine
To translate nested modules to LLVM IR, JitRunner and ExecutionEngine were
altered to take an optional (default to `nullptr`) function reference that
is a custom LLVM IR module builder. This allows to customize LLVM IR module
creation from MLIR modules.
Reviewed By: ftynse, mravishankar
Differential Revision: https://reviews.llvm.org/D86108
This dependency was already existing indirectly, but is now more direct
since the registration relies on a inline function. This fixes the
link of the tools with BFD.
Historically, custom builder specification in OpBuilder has been accepting the
formal parameter list for the builder method as a raw string containing C++.
While this worked well to connect the signature and the body, this became
problematic when ODS needs to manipulate the parameter list, e.g. to inject
OpBuilder or to trim default values when generating the definition. This has
also become inconsistent with other method declarations, in particular in
interface definitions.
Introduce the possibility to define OpBuilder formal parameters using a
TableGen dag similarly to other methods. Additionally, introduce a mechanism to
declare parameters with default values using an additional class. This
mechanism can be reused in other methods. The string-based builder signature
declaration is deprecated and will be removed after a transition period.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D89470
Have the ODS TypeDef generator write the getChecked() definition.
Also add to TypeParamCommaFormatter a `JustParams` format and
refactor around that.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D89438
Added an underlying matcher for generic constant ops. This
included a rewriter of RewriterGen to make variable use more
clear.
Differential Revision: https://reviews.llvm.org/D89161
This CL allows user to specify the same name for the operands in the source pattern which implicitly enforces equality on operands with the same name.
E.g., Pat<(OpA $a, $b, $a) ... > would create a matching rule for checking equality for the first and the last operands. Equality of the operands is enforced at any depth, e.g., OpA ($a, $b, OpB($a, $c, OpC ($a))).
Example usage: Pat<(Reshape $arg0, (Shape $arg0)), (replaceWithValue $arg0)>
Note, this feature only covers operands but not attributes.
Current use cases are based on the operand equality and explicitly add the constraint into the pattern. Attribute equality will be worked out on the different CL.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D89254
The buffers are used as source or destination of transfer commands
so always add VK_BUFFER_USAGE_TRANSFER_{DST,SRC}_BIT to their usage
flags.
Signed-off-by: Kevin Petit <kevin.petit@arm.com>
This revision adds a programmable codegen strategy from linalg based on staged rewrite patterns. Testing is exercised on a simple linalg.matmul op.
Differential Revision: https://reviews.llvm.org/D89374
This reverts commit 7271c1bcb9.
This broke the gcc-5 build:
/usr/include/c++/5/ext/new_allocator.h:120:4: error: no matching function for call to 'std::pair<const std::__cxx11::basic_string<char>, mlir::tblgen::SymbolInfoMap::SymbolInfo>::pair(llvm::StringRef&, mlir::tblgen::SymbolInfoMap::SymbolInfo)'
{ ::new((void *)__p) _Up(std::forward<_Args>(__args)...); }
^
In file included from /usr/include/c++/5/utility:70:0,
from llvm/include/llvm/Support/type_traits.h:18,
from llvm/include/llvm/Support/Casting.h:18,
from mlir/include/mlir/Support/LLVM.h:24,
from mlir/include/mlir/TableGen/Pattern.h:17,
from mlir/lib/TableGen/Pattern.cpp:14:
/usr/include/c++/5/bits/stl_pair.h:206:9: note: candidate: template<class ... _Args1, long unsigned int ..._Indexes1, class ... _Args2, long unsigned int ..._Indexes2> std::pair<_T1, _T2>::pair(std::tuple<_Args1 ...>&, std::tuple<_Args2 ...>&, std::_Index_tuple<_Indexes1 ...>, std::_Index_tuple<_Indexes2 ...>)
pair(tuple<_Args1...>&, tuple<_Args2...>&,
^
Adds a TypeDef class to OpBase and backing generation code. Allows one
to define the Type, its parameters, and printer/parser methods in ODS.
Can generate the Type C++ class, accessors, storage class, per-parameter
custom allocators (for the storage constructor), and documentation.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D86904
This CL allows user to specify the same name for the operands in the source pattern which implicitly enforces equality on operands with the same name.
E.g., Pat<(OpA $a, $b, $a) ... > would create a matching rule for checking equality for the first and the last operands. Equality of the operands is enforced at any depth, e.g., OpA ($a, $b, OpB($a, $c, OpC ($a))).
Example usage: Pat<(Reshape $arg0, (Shape $arg0)), (replaceWithValue $arg0)>
Note, this feature only covers operands but not attributes.
Current use cases are based on the operand equality and explicitly add the constraint into the pattern. Attribute equality will be worked out on the different CL.
Differential Revision: https://reviews.llvm.org/D89254
This is the same diff as https://reviews.llvm.org/D88809/ except side effect
free check is removed for involution and a FIXME is added until the dependency
is resolved for shared builds. The old diff has more details on possible fixes.
Reviewed By: rriddle, andyly
Differential Revision: https://reviews.llvm.org/D89333
CMake Error at llvm/cmake/modules/AddLLVM.cmake:870 (add_dependencies):
The dependency target "Core" of target "mlir-cuda-runner" does not exist.
Call Stack (most recent call first):
llvm/cmake/modules/AddLLVM.cmake:1169 (add_llvm_executable)
mlir/tools/mlir-cuda-runner/CMakeLists.txt:69 (add_llvm_tool)
CMake Error at llvm/cmake/modules/AddLLVM.cmake:870 (add_dependencies):
The dependency target "LINK_COMPONENTS" of target "mlir-cuda-runner" does
not exist.
Call Stack (most recent call first):
llvm/cmake/modules/AddLLVM.cmake:1169 (add_llvm_executable)
mlir/tools/mlir-cuda-runner/CMakeLists.txt:69 (add_llvm_tool)
CMake Error at llvm/cmake/modules/AddLLVM.cmake:870 (add_dependencies):
The dependency target "Support" of target "mlir-cuda-runner" does not
exist.
Call Stack (most recent call first):
llvm/cmake/modules/AddLLVM.cmake:1169 (add_llvm_executable)
mlir/tools/mlir-cuda-runner/CMakeLists.txt:69 (add_llvm_tool)
This revision reduces the number of places that specific information needs to be modified when adding new named Linalg ops.
Differential Revision: https://reviews.llvm.org/D89223
This revision introduces support for buffer allocation for any named linalg op.
To avoid template instantiating many ops, a new ConversionPattern is created to capture the LinalgOp interface.
Some APIs are updated to remain consistent with MLIR style:
`OwningRewritePatternList * -> OwningRewritePatternList &`
`BufferAssignmentTypeConverter * -> BufferAssignmentTypeConverter &`
Differential revision: https://reviews.llvm.org/D89226
This reverts commit 1ceaffd95a.
The build is broken with -DBUILD_SHARED_LIBS=ON ; seems like a possible
layering issue to investigate:
tools/mlir/lib/IR/CMakeFiles/obj.MLIRIR.dir/Operation.cpp.o: In function `mlir::MemoryEffectOpInterface::hasNoEffect(mlir::Operation*)':
Operation.cpp:(.text._ZN4mlir23MemoryEffectOpInterface11hasNoEffectEPNS_9OperationE[_ZN4mlir23MemoryEffectOpInterface11hasNoEffectEPNS_9OperationE]+0x9c): undefined reference to `mlir::MemoryEffectOpInterface::getEffects(llvm::SmallVectorImpl<mlir::SideEffects::EffectInstance<mlir::MemoryEffects::Effect> >&)'
mlir-tblgen was incompatible with libLLVM, due to explicit linkage with
libLLVMSupport etc.
As it cannot link with libLLVM, make sure all lib it uses are not using libLLVM
either.
As a side effect, also remove some explicit references to LLVM libs and use
components instead.
Differential Revision: https://reviews.llvm.org/D88846
This change allows folds to be done on a newly introduced involution trait rather than having to manually rewrite this optimization for every instance of an involution
Reviewed By: rriddle, andyly, stephenneuendorffer
Differential Revision: https://reviews.llvm.org/D88809
This change replaces container used for storing temporary
strings for generated code to std::list.
SmallVector may reallocate internal data, which will invalidate
references when more than one extended instruction set is
generated.
Reviewed By: mravishankar, antiagainst
Differential Revision: https://reviews.llvm.org/D88626
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.
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
Class simplifies keeping track of the indentation while emitting. For every new line the current indentation is simply prefixed (if not at start of line, then it just emits as normal). Add a simple Region helper that makes it easy to have the C++ scope match the emitted scope.
Use this in op doc generator and rewrite generator.
This reverts revert commit be185b6a73 addresses shared lib failure by fixing up cmake files.
Differential Revision: https://reviews.llvm.org/D84107
Class simplifies keeping track of the indentation while emitting. For every new line the current indentation is simply prefixed (if not at start of line, then it just emits as normal). Add a simple Region helper that makes it easy to have the C++ scope match the emitted scope.
Use this in op doc generator and rewrite generator.
Differential Revision: https://reviews.llvm.org/D84107
The pattern is structured similar to other patterns like
LinalgTilingPattern. The fusion patterns takes options that allows you
to fuse with producers of multiple operands at once.
- The pattern fuses only at the level that is known to be legal, i.e
if a reduction loop in the consumer is tiled, then fusion should
happen "before" this loop. Some refactoring of the fusion code is
needed to fuse only where it is legal.
- Since the fusion on buffers uses the LinalgDependenceGraph that is
not mutable in place the fusion pattern keeps the original
operations in the IR, but are tagged with a marker that can be later
used to find the original operations.
This change also fixes an issue with tiling and
distribution/interchange where if the tile size of a loop were 0 it
wasnt account for in these.
Differential Revision: https://reviews.llvm.org/D88435
This tweaks the generated code for parsing attributes with a custom
directive to call `addAttribute` on the `OperationState` directly,
and adds a newline after this call. Previously, the generated code
would call `addAttribute` on the `OperationState` field `attributes`,
which has no such method and fails to compile. Furthermore, the lack
of newline would generate code with incorrectly formatted single line
`if` statements. Added tests for parsing and printing attributes with
a custom directive.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D87860
- Change the default builders to use TypeRange instead of ArrayRef<Type>
- Custom builders defined in LinalgStructuredOps now conflict with the default
separate param ones, but the default collective params one is still needed. Resolve
this by replicating the collective param builder as a custom builder and skipping
the generation of default builders for these ops.
Differential Revision: https://reviews.llvm.org/D87926
Instead of performing a transformation, such pass yields a new pass pipeline
to run on the currently visited operation.
This feature can be used for example to implement a sub-pipeline that
would run only on an operation with specific attributes. Another example
would be to compute a cost model and dynamic schedule a pipeline based
on the result of this analysis.
Discussion: https://llvm.discourse.group/t/rfc-dynamic-pass-pipeline/1637
Recommit after fixing an ASAN issue: the callback lambda needs to be
allocated to a temporary to have its lifetime extended to the end of the
current block instead of just the current call expression.
Reviewed By: silvas
Differential Revision: https://reviews.llvm.org/D86392
The OpBuilder is required to start with OpBuilder and OperationState, so remove
the need for the user to specify it. To make it simpler to update callers,
retain the legacy behavior for now and skip injecting OpBuilder/OperationState
when params start with OpBuilder.
Related to bug 47442.
Differential Revision: https://reviews.llvm.org/D88050
This reverts commit 385c3f43fc.
Test mlir/test/Pass:dynamic-pipeline-fail-on-parent.mlir.test fails
when run with ASAN:
ERROR: AddressSanitizer: stack-use-after-scope on address ...
Reviewed By: bkramer, pifon2a
Differential Revision: https://reviews.llvm.org/D88079
Instead of performing a transformation, such pass yields a new pass pipeline
to run on the currently visited operation.
This feature can be used for example to implement a sub-pipeline that
would run only on an operation with specific attributes. Another example
would be to compute a cost model and dynamic schedule a pipeline based
on the result of this analysis.
Discussion: https://llvm.discourse.group/t/rfc-dynamic-pass-pipeline/1637
Reviewed By: silvas
Differential Revision: https://reviews.llvm.org/D86392
check-mlir target run tests simultaneously with multiple threads. This caused multiple threads to invoke the `lld:🧝:link()` interface at the same time. Since the interface does not have a thread-safe implementation, add a metex to prevent multi-threaded access.
I discovered this by looking the the failure stack trace. lld/ELF/symbolTable.cpp, SymbolTable::insert() hit into an assert with related to Epoch Trackers. The root cause is to due to there is no protection around the symMap (update) which is implemented in non-thread safe data structure: denseMap.
Differential Revision: https://reviews.llvm.org/D88038
This revision allows representing a reduction at the level of linalg on tensors for named ops. When a structured op has a reduction and returns tensor(s), new conventions are added and documented.
As an illustration, the syntax for a `linalg.matmul` writing into a buffer is:
```
linalg.matmul ins(%a, %b : memref<?x?xf32>, tensor<?x?xf32>)
outs(%c : memref<?x?xf32>)
```
, whereas the syntax for a `linalg.matmul` returning a new tensor is:
```
%d = linalg.matmul ins(%a, %b : tensor<?x?xf32>, memref<?x?xf32>)
init(%c : memref<?x?xf32>)
-> tensor<?x?xf32>
```
Other parts of linalg will be extended accordingly to allow mixed buffer/tensor semantics in the presence of reductions.
- Change OpClass new method addition to find and eliminate any existing methods that
are made redundant by the newly added method, as well as detect if the newly added
method will be redundant and return nullptr in that case.
- To facilitate that, add the notion of resolved and unresolved parameters, where resolved
parameters have each parameter type known, so that redundancy checks on methods
with same name but different parameter types can be done.
- Eliminate existing code to avoid adding conflicting/redundant build methods and rely
on this new mechanism to eliminate conflicting build methods.
Fixes https://bugs.llvm.org/show_bug.cgi?id=47095
Differential Revision: https://reviews.llvm.org/D87059
Add support to tile affine.for ops with parametric sizes (i.e., SSA
values). Currently supports hyper-rectangular loop nests with constant
lower bounds only. Move methods
- moveLoopBody(*)
- getTileableBands(*)
- checkTilingLegality(*)
- tilePerfectlyNested(*)
- constructTiledIndexSetHyperRect(*)
to allow reuse with constant tile size API. Add a test pass -test-affine
-parametric-tile to test parametric tiling.
Differential Revision: https://reviews.llvm.org/D87353
Now backends spell out which namespace they want to be in, instead of relying on
clients #including them inside already-opened namespaces. This also means that
cppNamespaces should be fully qualified, and there's no implicit "::mlir::"
prepended to them anymore.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D86811
This revision refactors and cleans up a bunch of things to simplify StructuredOpInterface
before work can proceed on Linalg on tensors:
- break out pieces of the StructuredOps trait that are part of the StructuredOpInterface,
- drop referenceIterators and referenceIndexingMaps that end up being more confusing than useful,
- drop NamedStructuredOpTrait
In this commit a new way of convolution ops lowering is introduced.
The conv op vectorization pass lowers linalg convolution ops
into vector contractions. This lowering is possible when conv op
is first tiled by 1 along specific dimensions which transforms
it into dot product between input and kernel subview memory buffers.
This pass converts such conv op into vector contraction and does
all necessary vector transfers that make it work.
Differential Revision: https://reviews.llvm.org/D86619
Drops the include on InitAllDialects.h, as dialects are now initialized in the translation passes.
Differential Revision: https://reviews.llvm.org/D87129
Alex Zinenko