Returning structs directly in LLVM does not necessarily align with the C ABI of
the platform. This might happen to work on Linux but for small structs this
breaks on Windows. With this change, the wrappers work platform independently.
Differential Revision: https://reviews.llvm.org/D98725
Added additional information about the SSA like properties
that has to be fulfilled in the bufferization steps.
Differential Revision: https://reviews.llvm.org/D95522
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
This allows for storage instances to store data that isn't uniqued in the context, or contain otherwise non-trivial logic, in the rare situations that they occur. Storage instances with trivial destructors will still have their destructor skipped. A consequence of this is that the storage instance definition must be visible from the place that registers the type.
Differential Revision: https://reviews.llvm.org/D98311
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
Based on the following discussion:
https://llvm.discourse.group/t/rfc-memref-memory-shape-as-attribute/2229
The goal of the change is to make memory space property to have more
expressive representation, rather then "magic" integer values.
It will allow to have more clean ASM form:
```
gpu.func @test(%arg0: memref<100xf32, "workgroup">)
// instead of
gpu.func @test(%arg0: memref<100xf32, 3>)
```
Explanation for `Attribute` choice instead of plain `string`:
* `Attribute` classes allow to use more type safe API based on RTTI.
* `Attribute` classes provides faster comparison operator based on
pointer comparison in contrast to generic string comparison.
* `Attribute` allows to store more complex things, like structs or dictionaries.
It will allows to have more complex memory space hierarchy.
This commit preserve old integer-based API and implements it on top
of the new one.
Depends on D97476
Reviewed By: rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D96145
* 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
To unify the naming scheme across all ops in the SPIR-V dialect, we are
moving from spv.camelCase to spv.CamelCase everywhere. For ops that
don't have a SPIR-V spec counterpart, we use spv.mlir.snake_case.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D98014
To unify the naming scheme across all ops in the SPIR-V dialect,
we are moving from spv.camelCase to spv.CamelCase everywhere.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D97918
* Mostly imported from experimental repo as-is with cosmetic changes.
* Temporarily left out emission code (for building ops at runtime) to keep review size down.
* Documentation and lit tests added fresh.
* Sample op library that represents current Linalg named ops included.
Differential Revision: https://reviews.llvm.org/D97995
To unify the naming scheme across all ops in the SPIR-V dialect, we are
moving from spv.camelCase to spv.CamelCase everywhere.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D97919
To unify the naming scheme across all ops in the SPIR-V dialect, we are
moving from `spv.camelCase` to `spv.CamelCase` everywhere.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D97917
To unify the naming scheme across all ops in the SPIR-V dialect, we are
moving from spv.camelCase to spv.CamelCase everywhere.
Differential Revision: https://reviews.llvm.org/D97920
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
DebugCounters allow for selectively enabling the execution of a debug action based upon a "counter". This counter is comprised of two components that are used in the control of execution of an action, a "skip" value and a "count" value. The "skip" value is used to skip a certain number of initial executions of a debug action. The "count" value is used to prevent a debug action from executing after it has executed for a set number of times (not including any executions that have been skipped). For example, a counter for a debug action with `skip=47` and `count=2`, would skip the first 47 executions, then execute twice, and finally prevent any further executions.
This is effectively the same as the DebugCounter infrastructure in LLVM, but using the DebugAction infrastructure in MLIR. We can't simply reuse the DebugCounter support already present in LLVM due to its heavy reliance on global constructors (which are not allowed in MLIR). The DebugAction infrastructure already nicely supports the debug counter use case, and promotes the separation of policy and mechanism design philosophy.
Differential Revision: https://reviews.llvm.org/D96395
This revision adds the infrastructure for `Debug Actions`. This is a DEBUG only
API that allows for external entities to control various aspects of compiler
execution. This is conceptually similar to something like DebugCounters in LLVM, but at a lower level. This framework doesn't make any assumptions about how the higher level driver is controlling the execution, it merely provides a framework for connecting the two together. This means that on top of DebugCounter functionality, we could also provide more interesting drivers such as interactive execution. A high level overview of the workflow surrounding debug actions is
shown below:
* Compiler developer defines an `action` that is taken by the a pass,
transformation, utility that they are developing.
* Depending on the needs, the developer dispatches various queries, pertaining
to this action, to an `action manager` that will provide an answer as to
what behavior the action should do.
* An external entity registers an `action handler` with the action manager,
and provides the logic to resolve queries on actions.
The exact definition of an `external entity` is left opaque, to allow for more
interesting handlers.
This framework was proposed here: https://llvm.discourse.group/t/rfc-debug-actions-in-mlir-debug-counters-for-the-modern-world
Differential Revision: https://reviews.llvm.org/D84986
`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
This commit introduced a cyclic dependency:
Memref dialect depends on Standard because it used ConstantIndexOp.
Std depends on the MemRef dialect in its EDSC/Intrinsics.h
Working on a fix.
This reverts commit 8aa6c3765b.
Create the memref dialect and move several dialect-specific ops without
dependencies to other ops from std dialect to this dialect.
Moved ops:
AllocOp -> MemRef_AllocOp
AllocaOp -> MemRef_AllocaOp
DeallocOp -> MemRef_DeallocOp
MemRefCastOp -> MemRef_CastOp
GetGlobalMemRefOp -> MemRef_GetGlobalOp
GlobalMemRefOp -> MemRef_GlobalOp
PrefetchOp -> MemRef_PrefetchOp
ReshapeOp -> MemRef_ReshapeOp
StoreOp -> MemRef_StoreOp
TransposeOp -> MemRef_TransposeOp
ViewOp -> MemRef_ViewOp
The roadmap to split the memref dialect from std is discussed here:
https://llvm.discourse.group/t/rfc-split-the-memref-dialect-from-std/2667
Differential Revision: https://reviews.llvm.org/D96425
After discussion, it seems like we want to go with
"inherent/discardable". These seem to best capture the relationship with
the op semantics and don't conflict with other terms.
Please let me know your preferences. Some of the other contenders are:
```
"intrinsic" side | "annotation" side
-----------------+------------------
characteristic | annotation
closed | open
definitional | advisory
essential | discardable
expected | unexpected
innate | acquired
internal | external
intrinsic | extrinsic
known | unknown
local | global
native | foreign
inherent | acquired
```
Rationale:
- discardable: good. discourages use for stable data.
- inherent: good
- annotation: redundant and doesn't convey difference
- intrinsic: confusable with "compiler intrinsics".
- definitional: too much of a mounthful
- extrinsic: too exotic of a word and hard to say
- acquired: doesn't convey the relationship to the semantics
- internal/external: not immediately obvious: what is internal to what?
- innate: similar to intrinsic but worse
- acquired: we don't typically think of an op as "acquiring" things
- known/unknown: by who?
- local/global: to what?
- native/foreign: to where?
- advisory: confusing distinction: is the attribute itself advisory or
is the information it provides advisory?
- essential: an intrinsic attribute need not be present.
- expected: same issue as essential
- unexpected: by who/what?
- closed/open: whether the set is open or closed doesn't seem essential
to the attribute being intrinsic. Also, in theory an op can have an
unbounded set of intrinsic attributes (e.g. `arg<N>` for func).
- characteristic: unless you have a math background this probably
doesn't make as much sense
Differential Revision: https://reviews.llvm.org/D96093
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
- attribute-dict production is redundant with dictionary-attribute
- definitions of attribute aliases were part of the same production as
uses of attribute aliases
- `std.dim` now accepts the dimension number as an operand, so the
example is out of date. Use the predicate of std.cmpi as a better
example.
Differential Revision: https://reviews.llvm.org/D96076
Fixes a few small issues in the docs. It seems one of the examples was missing
the expected MLIR output due to a copy-paste typo.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D95599
* 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
Add factory to create streams for logging the reproducer. Allows for more general logging (beyond file) and logging the configuration/module separately (logged in order, configuration before module).
Also enable querying filename of ToolOutputFile.
Differential Revision: https://reviews.llvm.org/D94868
A cast-like operation is one that converts from a set of input types to a set of output types. The arity of the inputs may be from 0-N, whereas the arity of the outputs may be anything from 1-N. Cast-like operations are removable in cases where they produce a "no-op", i.e when the input types and output types match 1-1.
Differential Revision: https://reviews.llvm.org/D94831
* 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
* Development setup recommendations.
* Test updates to match what we actually do.
* Update cmake variable `PYTHON_EXECUTABLE` -> `Python3_EXECUTABLE` to match the upgrade to python3 repo wide.
The standard and gpu dialect both have `alloc` operations which use the
memory effect `MemAlloc`. In both cases, it is specified on both the
operation itself and on the result. This results in two memory effects
being created for these operations. When `MemAlloc` is defined on an
operation, it represents some background effect which the compiler
cannot reason about, and inhibits the ability of the compiler to
remove dead `std.alloc` operations. This change removes the uneeded
`MemAlloc` effect from these operations and leaves the effect on the
result, which allows dead allocs to be erased.
There is the same problem, but to a lesser extent, with MemFree, MemRead
and MemWrite. Over-specifying these traits is not currently inhibiting
any optimization.
Differential Revision: https://reviews.llvm.org/D94662
This spilts out BufferDeallocationInternals.md, since buffer
deallocation is not part of bufferization per se.
Differential Revision: https://reviews.llvm.org/D94351
River Riddle