Now that all of the builtin dialect is generated from ODS, its documentation in LangRef can be split out and replaced with references to Dialects/Builtin.md. LangRef is quite crusty right now and should really have a full cleanup done in a followup.
Differential Revision: https://reviews.llvm.org/D98562
This removes the need to construct an APInt for each value, given that it is guaranteed to contain 32 bit elements.
BEGIN_PUBLIC
...text exposed to open source public git repo...
END_PUBLIC
This change combines for ROCm what was done for CUDA in D97463, D98203, D98360, and D98396.
I did not try to compile SerializeToHsaco.cpp or test mlir/test/Integration/GPU/ROCM because I don't have an AMD card. I fixed the things that had obvious bit-rot though.
Reviewed By: whchung
Differential Revision: https://reviews.llvm.org/D98447
Do not limit the number of arguments in rewriter pattern.
Introduce separate `FmtStrVecObject` class to handle
format of variadic `std::string` array.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D97839
This fixes broken JIT functionality on emulator platforms.
With Alex' recent movement towards squashing llvm ir dialects
into target specific dialects, we now must ensure these dialects
are registered to the cpu runner to ensure JIT can lower this
to proper LLVM IR before handing this off to the backend.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D98727
Add a feature to `EnumAttr` definition to generate
specialized Attribute class for the particular enumeration.
This class will inherit `StringAttr` or `IntegerAttr` and
will override `classof` and `getValue` methods.
With this class the enumeration predicate can be checked with simple
RTTI calls (`isa`, `dyn_cast`) and it will return the typed enumeration
directly instead of raw string/integer.
Based on the following discussion:
https://llvm.discourse.group/t/rfc-add-enum-attribute-decorator-class/2252
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D97836
Some parameters to attributes and types rely on special comparison routines other than operator== to ensure equality. This revision adds support for those parameters by allowing them to specify a `comparator` code block that determines if `$_lhs` and `$_rhs` are equal. An example of one of these paramters is APFloat, which requires `bitwiseIsEqual` for bitwise comparison (which we want for attribute equality).
Differential Revision: https://reviews.llvm.org/D98473
The commit in question changed the syntax but did not update the runner
tests. This also required registering the MemRef dialect for custom
parser to work correctly.
Start the description from a new line instead of putting the first
paragraph in the section header. Wrap the class name in backticks to
make it clear that it relates to the code.
Change CUDA integration tests to use mlir-opt + mlir-cpu-runner instead.
Depends On D98203
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D98396
Data layout information allows to answer questions about the size and alignment
properties of a type. It enables, among others, the generation of various
linear memory addressing schemes for containers of abstract types and deeper
reasoning about vectors. This introduces the subsystem for modeling data
layouts in MLIR.
The data layout subsystem is designed to scale to MLIR's open type and
operation system. At the top level, it consists of attribute interfaces that
can be implemented by concrete data layout specifications; type interfaces that
should be implemented by types subject to data layout; operation interfaces
that must be implemented by operations that can serve as data layout scopes
(e.g., modules); and dialect interfaces for data layout properties unrelated to
specific types. Built-in types are handled specially to decrease the overall
query cost.
A concrete default implementation of these interfaces is provided in the new
Target dialect. Defaults for built-in types that match the current behavior are
also provided.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D97067
Clean-up after D98279, remove one call to createConvertGPUKernelToBlobPass().
Depends On D98203
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D98360
Provide default for gpuBinaryAnnotation so that we don't need to specify it in tests.
The annotation likely only needs to be target specific if we want to lower to e.g. both CUDA and ROCDL.
Reviewed By: herhut, bondhugula
Differential Revision: https://reviews.llvm.org/D98168
This allows the caller to distinguish between a parse error or an
unmatched keyword. It fixes the redundant error that was emitted by the
caller when the generated parser would fail.
Differential Revision: https://reviews.llvm.org/D98162
Use `MLIR_LINALG_ODS_GEN` and `MLIR_LINALG_ODS_YAML_GEN` variables
instead of `MLIR_LINALG_ODS_GEN_EXE` and `MLIR_LINALG_ODS_YAML_GEN_EXE`.
The former are defined in PARENT SCOPE only, so the `if` condition
is never evaluates to `TRUE`.
The logic should be the following (taken from tblgen part):
1. `TOOL_NAME` - CACHE variable (default equal to target name).
User can override it to actual executable path.
2. `TOOL_NAME_EXE` - internal variable, initialized to `${TOOL_NAME}` first.
In case of cross-compilation (`LLVM_USE_HOST_TOOLS == TRUE`) if user
didn't set own path to native executable via `TOOL_NAME` variable,
CMake will create separate targets to build native tool and
will override `TOOL_NAME_EXE` to the executable produced by this target.
3. `TOOL_NAME_TARGET` - internal variable, which points to tool target name.
If the native tool is built as described above, it will point to the
target correspondant to that native tool.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D98025
* Only leaf packages are non-namespace packages. This allows most of the top levels to be split into different directories or deployment packages. In the previous state, the presence of __init__.py files at each level meant that the entire tree could only ever exist in one physical directory on the path.
* This changes the API usage slightly: `import mlir` will no longer do a deep import of `mlir.ir`, etc. This may necessitate some client code changes.
* Dialect gen code was restructured so that the user is responsible for providing the `my_dialect.py` file, which then must import its peer `_my_dialect_ops_gen`. This gives complete control of the dialect namespace to the user instead of to tablegen code, allowing further dialect-specific python APIs.
* Correspondingly, the previous extension modules `_my_dialect.py` are now `_my_dialect_ops_ext.py`.
* Now that the `linalg` namespace is open, moved the `linalg_opdsl` tool into it.
* This may require some corresponding downstream adjustments to npcomp, circt, et al:
* Probably some shallow imports need to be converted to deep imports (i.e. not `import mlir` brings in the world).
* Each tablegen generated dialect now needs an explicit `foo.py` which does a `from ._foo_ops_gen import *`. This is similar to the way that generated code operates in the C++ world.
* If providing dialect op extensions, those need to be moved from `_foo.py` -> `_foo_ops_ext.py`.
Differential Revision: https://reviews.llvm.org/D98096
This patch is a follow-up on D97217. It adds a new 'Skip' result to the Operation visitor
so that a callback can stop the ongoing visit of an operation/block/region and
continue visiting the next one without fully interrupting the walk. Skipping is
needed to be able to erase an operation/block in pre-order and do not continue
visiting the internals of that operation/block.
Related to the skipping mechanism, the patch also introduces the following changes:
* Added new TestIRVisitors pass with basic testing for the IR visitors.
* Fixed missing early increment ranges in visitor implementation.
* Updated documentation of walk methods to include erasure information and walk
order information.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D97820
The value type of the attribute can be specified by either overriding the typeBuilder field on the AttrDef, or by providing a parameter of type `AttributeSelfTypeParameter`. This removes the need to define custom storage class constructors for attributes that have a value type other than NoneType.
Differential Revision: https://reviews.llvm.org/D97590
There is no need for the interface implementations to be exposed, opaque
registration functions are sufficient for all users, similarly to passes.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D97852
The support for attributes closely maps that of Types (basically 1-1) given that Attributes are defined in exactly the same way as Types. All of the current ODS TypeDef classes get an Attr equivalent. The generation of the attribute classes themselves share the same generator as types.
Differential Revision: https://reviews.llvm.org/D97589
Use `StringLiteral` for function return type if it is known to return
constant string literals only.
This will make it visible to API users, that such values can be safely
stored, since they refers to constant data, which will never be deallocated.
`StringRef` is general is not safe to store for a long term,
since it might refer to temporal data allocated in heap.
Add `inline` and `constexpr` methods support to `OpMethod`.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D97390
Some variables are unused after D97383 landed. We should generate one symbol for one attrUse.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D97794
These warnings are raised when compiling with gcc due to either having too few or too many commas, or in the case of lldb, the possibility of a nullptr.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D97586
This enables this kind of construct in the DSL to generate a named op that is polymorphic over numeric type variables `T` and `U`, generating the correct arithmetic casts at construction time:
```
@tc_def_op
def polymorphic_matmul(A=TensorDef(T1, S.M, S.K),
B=TensorDef(T2, S.K, S.N),
C=TensorDef(U, S.M, S.N, output=True)):
implements(ContractionOpInterface)
C[D.m, D.n] += cast(U, A[D.m, D.k]) * cast(U, B[D.k, D.n])
```
Presently, this only supports type variables that are bound to the element type of one of the arguments, although a further extension that allows binding a type variable to an attribute would allow some more expressiveness and may be useful for some formulations. This is left to a future patch. In addition, this patch does not yet materialize the verifier support which ensures that types are bound correctly (for such simple examples, failing to do so will yield IR that fails verification, it just won't yet fail with a precise error).
Note that the full grid of extensions/truncation/int<->float conversions are supported, but many of them are lossy and higher level code needs to be mindful of numerics (it is not the job of this level).
As-is, this should be sufficient for most integer matmul scenarios we work with in typical quantization schemes.
Differential Revision: https://reviews.llvm.org/D97603
This also exposed a bug in Dialect loading where it was not correctly identifying identifiers that had the dialect namespace as a prefix.
Differential Revision: https://reviews.llvm.org/D97431
Allows querying regions too via OpAdaptor's generated. This does not yet move region verification to adaptor nor require regions for ops where needed.
Differential Revision: https://reviews.llvm.org/D97519
If one operand is not used in the formula, it will be considered a
shaped operand. And the result of indexing map of the operand will be the first
reduction dims.
Depends On D97383
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D97384
This fixes the documentation emitted for type parameters. Also adds a
missing empty line, rendered as line break in mark down.
Co-authored-by: Simon Camphausen <simon.camphausen@iml.fraunhofer.de>
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D97267
This will allow us to define select(pred, in, out) for TC ops, which is useful
for pooling ops.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D97312
The cuda-runner registers two pass pipelines for nested passes,
so that we don't have to use verbose textual pass pipeline specification.
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D97091
`verifyConstructionInvariants` is intended to allow for verifying the invariants of an attribute/type on construction, and `getChecked` is intended to enable more graceful error handling aside from an assert. There are a few problems with the current implementation of these methods:
* `verifyConstructionInvariants` requires an mlir::Location for emitting errors, which is prohibitively costly in the situations that would most likely use them, e.g. the parser.
This creates an unfortunate code duplication between the verifier code and the parser code, given that the parser operates on llvm::SMLoc and it is an undesirable overhead to pre-emptively convert from that to an mlir::Location.
* `getChecked` effectively requires duplicating the definition of the `get` method, creating a quite clunky workflow due to the subtle different in its signature.
This revision aims to talk the above problems by refactoring the implementation to use a callback for error emission. Using a callback allows for deferring the costly part of error emission until it is actually necessary.
Due to the necessary signature change in each instance of these methods, this revision also takes this opportunity to cleanup the definition of these methods by:
* restructuring the signature of `getChecked` such that it can be generated from the same code block as the `get` method.
* renaming `verifyConstructionInvariants` to `verify` to match the naming scheme of the rest of the compiler.
Differential Revision: https://reviews.llvm.org/D97100
* It was decided that this was the end of the line for the existing custom tc parser/generator, and this is the first step to replacing it with a declarative format that maps well to mathy source languages.
* One such source language is implemented here: https://github.com/stellaraccident/mlir-linalgpy/blob/main/samples/mm.py
* In fact, this is the exact source of the declarative `polymorphic_matmul` in this change.
* I am working separately to clean this python implementation up and add it to MLIR (probably as `mlir.tools.linalg_opgen` or equiv). The scope of the python side is greater than just generating named ops: the ops are callable and directly emit `linalg.generic` ops fully dynamically, and this is intended to be a feature for frontends like npcomp to define custom linear algebra ops at runtime.
* There is more work required to handle full type polymorphism, especially with respect to integer formulations, since they require more specificity wrt types.
* Followups to this change will bring the new generator to feature parity with the current one and delete the current. Roughly, this involves adding support for interface declarations and attribute symbol bindings.
Differential Revision: https://reviews.llvm.org/D97135
The functions translating enums to LLVM IR are generated in a single
file included in many places, not all of which use all translations.
Generate functions with "unused" attribute to silence compiler warnings.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D96880
A series of preceding patches changed the mechanism for translating MLIR to
LLVM IR to use dialect interface with delayed registration. It is no longer
necessary for specific dialects to derive from ModuleTranslation. Remove all
virtual methods from ModuleTranslation and factor out the entry point to be a
free function.
Also perform some cleanups in ModuleTranslation internals.
Depends On D96774
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96775
Port the translation of five dialects that define LLVM IR intrinsics
(LLVMAVX512, LLVMArmNeon, LLVMArmSVE, NVVM, ROCDL) to the new dialect
interface-based mechanism. This allows us to remove individual translations
that were created for each of these dialects and just use one common
MLIR-to-LLVM-IR translation that potentially supports all dialects instead,
based on what is registered and including any combination of translatable
dialects. This removal was one of the main goals of the refactoring.
To support the addition of GPU-related metadata, the translation interface is
extended with the `amendOperation` function that allows the interface
implementation to post-process any translated operation with dialect attributes
from the dialect for which the interface is implemented regardless of the
operation's dialect. This is currently applied to "kernel" functions, but can
be used to construct other metadata in dialect-specific ways without
necessarily affecting operations.
Depends On D96591, D96504
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96592
Currently, vector.contract joins the intermediate result and the accumulator
argument (of ranks K) using summation. We desire more joining operations ---
such as max --- to help vector.contract express reductions. This change extends
Vector_ContractionOp to take an optional attribute (called "kind", of enum type
CombiningKind) specifying the joining operation to be add/mul/min/max for int/fp
, and and/or/xor for int only. By default this attribute has value "add".
To implement this we also need to extend vector.outerproduct, since
vector.contract gets transformed to vector.outerproduct (and that to
vector.fma). The extension for vector.outerproduct is also an optional kind
attribute that uses the same enum type and possible values. The default is
"add". In case of max/min we transform vector.outerproduct to a combination of
compare and select.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D93280
This revision takes advantage of the newly extended `ref` directive in assembly format
to allow better region handling for LinalgOps. Specifically, FillOp and CopyOp now build their regions explicitly which allows retiring older behavior that relied on specific op knowledge in both lowering to loops and vectorization.
This reverts commit 3f22547fd1 and reland 973e133b76 with a workaround for
a gcc bug that does not accept lambda default parameters:
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=59949
Differential Revision: https://reviews.llvm.org/D96598
This reverts commit 973e133b76.
It triggers an issue in gcc5 that require investigation, the build is
broken with:
/tmp/ccdpj3B9.s: Assembler messages:
/tmp/ccdpj3B9.s:5821: Error: symbol `_ZNSt17_Function_handlerIFvjjEUljjE2_E9_M_invokeERKSt9_Any_dataOjS6_' is already defined
/tmp/ccdpj3B9.s:5860: Error: symbol `_ZNSt14_Function_base13_Base_managerIUljjE2_E10_M_managerERSt9_Any_dataRKS3_St18_Manager_operation' is already defined
Migrate the translation of the OpenMP dialect operations to LLVM IR to the new
dialect-based mechanism.
Depends On D96503
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96504
The existing approach to translation to the LLVM IR relies on a single
translation supporting the base LLVM dialect, extensible through inheritance to
support intrinsic-based dialects also derived from LLVM IR such as NVVM and
AVX512. This approach does not scale well as it requires additional
translations to be created for each new intrinsic-based dialect and does not
allow them to mix in the same module, contrary to the rest of the MLIR
infrastructure. Furthermore, OpenMP translation ingrained itself into the main
translation mechanism.
Start refactoring the translation to LLVM IR to operate using dialect
interfaces. Each dialect that contains ops translatable to LLVM IR can
implement the interface for translating them, and the top-level translation
driver can operate on interfaces without knowing about specific dialects.
Furthermore, the delayed dialect registration mechanism allows one to avoid a
dependency on LLVM IR in the dialect that is translated to it by implementing
the translation as a separate library and only registering it at the client
level.
This change introduces the new mechanism and factors out the translation of the
"main" LLVM dialect. The remaining dialects will follow suit.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96503
This revision takes advantage of the newly extended `ref` directive in assembly format
to allow better region handling for LinalgOps. Specifically, FillOp and CopyOp now build their regions explicitly which allows retiring older behavior that relied on specific op knowledge in both lowering to loops and vectorization.
Differential Revision: https://reviews.llvm.org/D96598
ModuleTranslation contains multiple fields that keep track of the mappings
between various MLIR and LLVM IR components. The original ModuleTranslation
extension model was based on inheritance, with these fields being protected and
thus accessible in the ModuleTranslation and derived classes. The
inheritance-based model doesn't scale to translation of more than one derived
dialect and will be progressively replaced with a more flexible one based on
dialect interfaces and a translation state that is separate from
ModuleTranslation. This change prepares the replacement by making the mappings
private and providing public methods to access them.
Depends On D96436
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D96437
Historically, JitRunner has been registering all available dialects with the
context and depending on them without the real need. Make it take a registry
that contains only the dialects that are expected in the input and stop linking
in all dialects.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D96436
MLIRContext allows its users to access directly to the DialectRegistry it
contains. While sometimes useful for registering additional dialects on an
already existing context, this breaks the encapsulation by essentially giving
raw accesses to a part of the context's internal state. Remove this mutable
access and instead provide a method to append a given DialectRegistry to the
one already contained in the context. Also provide a shortcut mechanism to
construct a context from an already existing registry, which seems to be a
common use case in the wild. Keep read-only access to the registry contained in
the context in case it needs to be copied or used for constructing another
context.
With this change, DialectRegistry is no longer concerned with loading the
dialects and deciding whether to invoke delayed interface registration. Loading
is concentrated in the MLIRContext, and the functionality of the registry
better reflects its name.
Depends On D96137
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D96331
Previously it reported an op had side-effects iff it declared that it
didn't have any side-effects. This had the undesirable result that
canonicalization would always delete any intrinsic calls that did memory
stores and returned void.
Reviewed By: ftynse, mehdi_amini
Differential Revision: https://reviews.llvm.org/D96369
This allows for referencing nearly every component of an operation from within a custom directive.
It also fixes a bug with the current type_ref implementation, PR48478
Differential Revision: https://reviews.llvm.org/D96189
This revision adds a new `AliasAnalysis` class that represents the main alias analysis interface in MLIR. The purpose of this class is not to hold the aliasing logic itself, but to provide an interface into various different alias analysis implementations. As it evolves this should allow for users to plug in specialized alias analysis implementations for their own needs, and have them immediately usable by other analyses and transformations.
This revision also adds an initial simple generic alias, LocalAliasAnalysis, that provides support for performing stateless local alias queries between values. This class is similar in scope to LLVM's BasicAA.
Differential Revision: https://reviews.llvm.org/D92343
Indexing maps for named ops can reference attributes so that
we can synthesize the indexing map dynamically. This supports
cases like strides for convolution ops. However, it does cause
an issue: now the indexing_maps() function call is dependent
on those attributes.
Linalg ops inherit LinalgOpInterfaceTraits, which calls
verifyStructuredOpInterface() to verify the interface.
verifyStructuredOpInterface() further calls indexing_maps().
Note that trait verification is done before the op itself,
where ODS generates the verification for those attributes.
So we can have indexing_maps() referencing non-existing or
invalid attribute, before the ODS-generated verification
kick in.
There isn't a dependency handling mechansim for traits.
This commit adds new interface methods to query whether an
op hasDynamicIndexingMaps() and then perform
verifyIndexingMapRequiredAttributes() in
verifyStructuredOpInterface() to handle the dependency issue.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96297
This reverts commit 511dd4f438 along with
a couple fixes.
Original message:
Now the context is the first, rather than the last input.
This better matches the rest of the infrastructure and makes
it easier to move these types to being declaratively specified.
Phabricator: https://reviews.llvm.org/D96111
Now the context is the first, rather than the last input.
This better matches the rest of the infrastructure and makes
it easier to move these types to being declaratively specified.
Differential Revision: https://reviews.llvm.org/D96111
This makes ignoring a result explicit by the user, and helps to prevent accidental errors with dropped results. Marking LogicalResult as no discard was always the intention from the beginning, but got lost along the way.
Differential Revision: https://reviews.llvm.org/D95841
This reverts commit 953086ddbb because
it breaks GCC 5 build:
error: could not convert '(const char*)""' from 'const char*' to 'llvm::StringLiteral'
static ::llvm::StringLiteral getDialectNamespace() { return ""; }
Use `StringLiteral` for function return type if it is known to return
constant string literals only.
This will make it visible to API users, that such values can be safely
stored, since they refers to constant data, which will never be deallocated.
`StringRef` is general is not safe to store for a long term,
since it might refer to temporal data allocated in heap.
Reviewed By: mehdi_amini, bkramer
Differential Revision: https://reviews.llvm.org/D95945
This revision takes advantage of recent extensions to vectorization to refactor contraction detection into a bona fide Linalg interface.
The mlit-linalg-ods-gen parser is extended to support adding such interfaces.
The detection that was originally enabling vectorization is refactored to serve as both a test on a generic LinalgOp as well as to verify ops that declare to conform to that interface.
This is plugged through Linalg transforms and strategies but it quickly becomes evident that the complexity and rigidity of the C++ class based templating does not pay for itself.
Therefore, this revision changes the API for vectorization patterns to get rid of templates as much as possible.
Variadic templates are relegated to the internals of LinalgTransformationFilter as much as possible and away from the user-facing APIs.
It is expected other patterns / transformations will follow the same path and drop as much C++ templating as possible from the class definition.
Differential revision: https://reviews.llvm.org/D95973
This separation improves the layering and paves the way for more interfaces coming up in the future.
Differential revision: https://reviews.llvm.org/D95941
This makes the generated code independent from actual namespace of its users.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D95520
Add printer and parser hooks for a custom directive that allows
parsing and printing of idioms that can represent a list of values
each of which is either an integer or an SSA value. For example in
`subview %source[%offset_0, 1] [4, %size_1] [%stride_0, 3]`
each of the list (which represents offset, size and strides) is a mix
of either statically know integer values or dynamically computed SSA
values. Since this is used in many places adding a custom directive to
parse/print this idiom allows using assembly format on operations
which use this idiom.
Differential Revision: https://reviews.llvm.org/D95773
Depending on the headers only is fine, but we do not want to use any symbols from LLVMSupport. If we do, static registration of cl options is linked in as well, and loading multiple such libraries in the cuda/rocm-runner fails because the same cl options are registered multiple times.
The cuda/rocm-runners also depend on LLVMSupport, so one could think that already loading a single such library would fail. It does not because the map of cl options is not shared between the runner and the loaded libraries (but it is shared across all loaded libraries, presumably because it has external linkage, in contrast to the static registration which has internal linkage).
This change is a preparation step for dynamically loading the mlir_async_runtime.so and cuda-runtime-wrappers.so in the same test. The async runtime depends on LLVMSupport in a more fundamental way (llvm::ThreadPool), and as explained above there can only be one.
This change also switches to add_mlir_library to make it consistent with the other runner_utils libraries.
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D95613
The current context is thread-local state, and in preparation of GPU async execution (on multiple threads) we need to set the context before calling API that create resources.
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D94495
* As discussed, fixes the ordering or (operands, results) -> (results, operands) in various `create` like methods.
* Fixes a syntax error in an ODS accessor method.
* Removes the linalg example in favor of a test case that exercises the same.
* Fixes FuncOp visibility to properly use None instead of the empty string and defaults it to None.
* Implements what was documented for requiring that trailing __init__ args `loc` and `ip` are keyword only.
* Adds a check to `InsertionPoint.insert` so that if attempting to insert past the terminator, an exception is raised telling you what to do instead. Previously, this would crash downstream (i.e. when trying to print the resultant module).
* Renames `_ods_build_default` -> `build_generic` and documents it.
* Removes `result` from the list of prohibited words and for single-result ops, defaults to naming the result `result`, thereby matching expectations and what is already implemented on the base class.
* This was intended to be a relatively small set of changes to be inlined with the broader support for ODS generating the most specific builder, but it spidered out once actually testing various combinations, so rolling up separately.
Differential Revision: https://reviews.llvm.org/D95320
This revision adds support for using either operand or result types to anchor an optional group. It also removes the arbitrary restriction that type directives must refer to variables in the same group, which is overly limiting for a declarative format syntax.
Fixes PR#48784
Differential Revision: https://reviews.llvm.org/D95109
I attempted to write a test case for this, but the situations in which the kind is used for RegionDirective and ResultsDirective have zero overlap; meaning that there isn't a situation in which sharing the kind creates a conflict.
Differential Revision: https://reviews.llvm.org/D94988
The patch adapts the rocm runtime wrapper due to subtle differences between the cuda and the rocm/hip runtime api.
Reviewed By: csigg
Differential Revision: https://reviews.llvm.org/D95027
The runtime-wrappers depend on LLVMSupport, pulling in static initialization code (e.g. command line arguments). Dynamically loading multiple such libraries results in ODR violoations.
So far this has not been an issue, but in D94421, I would like to load both the async-runtime and the cuda-runtime-wrappers as part of a cuda-runner integration test. When doing this, code that asserts that an option category is only registered once fails (note that I've only experienced this in Google's bazel where the async-runtime depends on LLVMSupport, but a similar issue would happen in cmake if more than one runtime-wrapper starts to depend on LLVMSupport).
The underlying issue is that we have a mix of static and dynamic linking. If all dependencies were loaded as shared objects (i.e. if LLVMSupport was linked dynamically to the runtime wrappers), each dependency would only get loaded once. However, linking dependencies dynamically would require special attention to paths (one could dynamically load the dependencies first given explicit paths). The simpler approach seems to be to link all dependencies statically into a single shared object.
This change basically applies the same logic that we have in the c_runner_utils: we have a shared object target that can be loaded dynamically, and we have a static library target that can be linked to other runtime-wrapper shared object targets.
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D94399
* This isn't exclusive with other mechanisms for more ODS centric op definitions, but based on discussions, we feel that we will always benefit from a python escape hatch, and that is the most natural way to write things that don't fit the mold.
* I suspect this facility needs further tweaking, and once it settles, I'll document it and add more tests.
* Added extensions for linalg, since it is unusable without them and continued to evolve my e2e example.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D94752
* This allows us to hoist trait level information for regions and sized-variadic to class level attributes (_ODS_REGIONS, _ODS_OPERAND_SEGMENTS, _ODS_RESULT_SEGMENTS).
* Eliminates some splicey python generated code in favor of a native helper for it.
* Makes it possible to implement custom, variadic and region based builders with one line of python, without needing to manually code access to the segment attributes.
* Needs follow-on work for region based callbacks and support for SingleBlockImplicitTerminator.
* A follow-up will actually add ODS support for generating custom Python builders that delegate to this new method.
* Also includes the start of an e2e sample for constructing linalg ops where this limitation was discovered (working progressively through this example and cleaning up as I go).
Differential Revision: https://reviews.llvm.org/D94738
Use cross-compilation approach for `mlir-linalg-ods-gen` application
similar to TblGen tools.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94598
This commit adds support to generate an additional builder for
each named op that has attributes. This gives better experience
when creating the named ops.
Along the way adds support for i64.
Reviewed By: hanchung
Differential Revision: https://reviews.llvm.org/D94733
In the overwhelmingly common case, enum attribute case strings represent valid identifiers in MLIR syntax. This revision updates the format generator to format as a keyword in these cases, removing the need to wrap values in a string. The parser still retains the ability to parse the string form, but the printer will use the keyword form when applicable.
Differential Revision: https://reviews.llvm.org/D94575
This is a variant of TypesMatchWith that provides support for variadic arguments. This is necessary because ranges generally can't use the default operator== comparators for checking equality.
Differential Revision: https://reviews.llvm.org/D94574
This commit adds support for parsing attribute uses in indexing
maps. These attribute uses are represented as affine symbols in
the resultant indexing maps because we can only know their
concrete value (which are coming from op attributes and are
constants) for specific op instances. The `indxing_maps()`
calls are synthesized to read these attributes and create affine
constants to replace the placeholder affine symbols and simplify.
Depends on D94240
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94335
River Riddle