This allows for specifying additional get/getChecked methods that should be generated on the type, and acts similarly to how OpBuilders work. TypeBuilders have two additional components though:
* InferredContextParam
- Bit indicating that the context parameter of a get method is inferred from one of the builder parameters
* checkedBody
- A code block representing the body of the equivalent getChecked method.
Differential Revision: https://reviews.llvm.org/D94274
This removes the need for OpDefinitionsGen to use raw tablegen API, and will also
simplify adding builders to TypeDefs as well.
Differential Revision: https://reviews.llvm.org/D94273
Lowering of async dialect uses a fixed type converter and therefore does not support lowering non-standard types.
This revision adds a structural conversion so that non-standard types in `!async.value`s can be lowered to LLVM before lowering the async dialect itself.
Reviewed By: ezhulenev
Differential Revision: https://reviews.llvm.org/D94404
This wasn't possible before because there was no support for affine expressions
as maps. Now that this support is available, provide the mechanism for
constructing maps with a layout and inspecting it.
Rework the `get` method on MemRefType in Python to avoid needing an explicit
memory space or layout map. Remove the `get_num_maps`, it is too low-level,
using the length of the now-avaiable pseudo-list of layout maps is more
pythonic.
Depends On D94297
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D94302
Now that the bindings for AffineExpr have been added, add more bindings for
constructing and inspecting AffineMap that consists of AffineExprs.
Depends On D94225
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D94297
This adds the Python bindings for AffineExpr and a couple of utility functions
to the C API. AffineExpr is a top-level context-owned object and is modeled
similarly to attributes and types. It is required, e.g., to build layout maps
of the built-in memref type.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D94225
When fusing tensor_reshape ops with generic/indexed_Generic op, new
linalg.init_tensor operations were created for the `outs` of the fused
op. While correct (technically) it is better to just reshape the
original `outs` operands and rely on canonicalization of init_tensor
-> tensor_reshape to achieve the same effect.
Differential Revision: https://reviews.llvm.org/D93774
This allow more accurate modeling of the side effects and allow dead code
elimination to remove dead transfer ops.
Differential Revision: https://reviews.llvm.org/D94318
Linalg ops are perfect loop nests. When materializing the concrete
loop nest, the default order specified by the Linalg op's iterators
may not be the best for further CodeGen: targets frequently need
to plan the loop order in order to gain better data access. And
different targets can have different preferences. So there should
exist a way to control the order.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D91795
With this, now we can specify a list of attributes on named ops
generated from the spec. The format is defined as
```
attr-id ::= bare-id (`?`)?
attr-typedef ::= type (`[` `]`)?
attr-def ::= attr-id `:` attr-typedef
tc-attr-def ::= `attr` `(` attr-def-list `)`
tc-def ::= `def` bare-id
`(`tensor-def-list`)` `->` `(` tensor-def-list`)`
(tc-attr-def)?
```
For example,
```
ods_def<SomeCppOp>
def some_op(...) -> (...)
attr(
f32_attr: f32,
i32_attr: i32,
array_attr : f32[],
optional_attr? : f32
)
```
where `?` means optional attribute and `[]` means array type.
Reviewed By: hanchung, nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94240
Do not cache gpu.async.token type so that the pass can be created before the GPU dialect is registered.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D94397
This commit adds support for (de-)serializing SpecConstantOpeation. One
thing worth noting is that during deserialization, we assign a fake ID to
enclosed ops inside SpecConstantOpeation. We need to do this in order
for deserialization logic to properly update ID to value map and to
later reference the created value from the sibling 'spv::YieldOp'.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D93591
This assertion is an old remnant from earlier days when only affine functions existed.
It is not the place of affine map composition to check whether orthogonal considerations
on what is allowed to be a symbol under the AffineScope trait.
mlir-opt supports many more test cases. All available dialects supported by latest mlir-opt should be coverted in the test case.
Reviewed By: aartbik, stephenneuendorffer, mehdi_amini
Differential Revision: https://reviews.llvm.org/D93821
This change makes the scatter/gather syntax more consistent with
the syntax of all the other memory operations in the Vector dialect
(order of types, use of [] for index, etc.). This will make the MLIR
code easier to read. In addition, the pass_thru parameter of the
gather has been made mandatory (there is very little benefit in
using the implicit "undefined" values).
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94352
The dialect conversion framework was enhanced to handle type
conversion automatically. OpConversionPattern already contains
a pointer to the TypeConverter. There is no need to duplicate it
in a separate subclass. This removes the only reason for a
SPIRVOpLowering subclass. It adapts to use core infrastructure
and simplifies the code.
Also added a utility function to OpConversionPattern for getting
TypeConverter as a certain subclass.
Reviewed By: hanchung
Differential Revision: https://reviews.llvm.org/D94080
Large integers are generated in Circt commonly which exceed 4kbits. This aligns the maximum bitwidth in MLIR and LLVM.
Reviewed By: rriddle, lattner, mehdi_amini
Differential Revision: https://reviews.llvm.org/D94116
Adding the ability to index the base address brings these operations closer
to the transfer read and write semantics (with lowering advantages), ensures
more consistent use in vector MLIR code (easier to read), and reduces the
amount of code duplication to lower memrefs into base addresses considerably
(making codegen less error-prone).
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D94278
This revision adds a new `initialize(MLIRContext *)` hook to passes that allows for them to initialize any heavy state before the first execution of the pass. A concrete use case of this is with patterns that rely on PDL, given that PDL is compiled at run time it is imperative that compilation results are cached as much as possible. The first use of this hook is in the Canonicalizer, which has the added benefit of reducing the number of expensive accesses to the context when collecting patterns.
Differential Revision: https://reviews.llvm.org/D93147
Use custom mlir runner init/destroy functions to safely init and destroy shared libraries loaded by the JitRunner.
This mechanism is ignored for Windows builds (for now) because init/destroy functions are not exported, and library unloading relies on static destructors.
Re-submit https://reviews.llvm.org/D94270 with a temporary workaround for windows
Differential Revision: https://reviews.llvm.org/D94312
Change the implementation of LinalgOp with TensorReshapeOp by
expansion to be more modular and easier to follow.
Differential Revision: https://reviews.llvm.org/D93748
The existing verification of reshape ops in linalg (linalg.reshape and
linalg.tensor_reshape) allows specification of illegal ops, where
- A dynamic dimension is expanded into multiple dynamic
dimensions. This is ill-specified.
- A static dimension is expanded into dynamic dimension or viceversa,
- The product of extents of the static dimensions in the expanded type
doesnt match the static dimension of the collapsed type.
Making all of these illegal. This also implies that some pessimization
in canonicalization due to incomplete semantics of the operation can
be dropped.
Differential Revision: https://reviews.llvm.org/D93724
Continue the convergence between LLVM dialect and built-in types by replacing
the bfloat, half, float and double LLVM dialect types with their built-in
counterparts. At the API level, this is a direct replacement. At the syntax
level, we change the keywords to `bf16`, `f16`, `f32` and `f64`, respectively,
to be compatible with the built-in type syntax. The old keywords can still be
parsed but produce a deprecation warning and will be eventually removed.
Depends On D94178
Reviewed By: mehdi_amini, silvas, antiagainst
Differential Revision: https://reviews.llvm.org/D94179
Use custom mlir runner init/destroy functions to safely init and destroy shared libraries loaded by the JitRunner.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D94270
This patch adds an attribute `inclusive` which if present causes
the upperbound to be included in the loop iteration interval.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D94235
Instead of checking explicitly checking for whether an op is usalbe
inside a `SpecConstantOperationOP`, this commit adds a new trait to
filter such ops.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D94288
to the conversion of LLVM IR dialect. These attributes are used in FIR to
support the lowering of Fortran using target-specific calling conventions.
Add roundtrip tests.
Add changes per review comments/concerns.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D94052
Some Python bindings tests were using FileCheck to match parts of the
error description produced only in the debug compilation mode. Remove
these parts (but keep the main message) to ensure tests also pass when
running them in the release compilation mode.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D94221
The LLVM dialect type system has been closed until now, i.e. did not support
types from other dialects inside containers. While this has had obvious
benefits of deriving from a common base class, it has led to some simple types
being almost identical with the built-in types, namely integer and floating
point types. This in turn has led to a lot of larger-scale complexity: simple
types must still be converted, numerous operations that correspond to LLVM IR
intrinsics are replicated to produce versions operating on either LLVM dialect
or built-in types leading to quasi-duplicate dialects, lowering to the LLVM
dialect is essentially required to be one-shot because of type conversion, etc.
In this light, it is reasonable to trade off some local complexity in the
internal implementation of LLVM dialect types for removing larger-scale system
complexity. Previous commits to the LLVM dialect type system have adapted the
API to support types from other dialects.
Replace LLVMIntegerType with the built-in IntegerType plus additional checks
that such types are signless (these are isolated in a utility function that
replaced `isa<LLVMType>` and in the parser). Temporarily keep the possibility
to parse `!llvm.i32` as a synonym for `i32`, but add a deprecation notice.
Reviewed By: mehdi_amini, silvas, antiagainst
Differential Revision: https://reviews.llvm.org/D94178
the conversion of LLVM IR dialect. These attributes are used in FIR to
support the lowering of Fortran using target-specific calling
conventions.
Add roundtrip tests. Add changes per review comments/concerns.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D94052
The original implementation of the OpenMP dialect to LLVM IR translation has
been relying on a stack of insertion points for delayed insertion of branch
instructions that correspond to terminator ops. This is an intrusive into
ModuleTranslation and makes the translation non-local. A recent addition of the
WsLoop translation exercised another approach where the parent op is
responsible for converting terminators of all blocks in its regions. Use this
approach for other OpenMP dialect operations with regions, remove the stack and
deduplicate the code for converting such regions.
Reviewed By: kiranchandramohan
Differential Revision: https://reviews.llvm.org/D94086
The functions will be removed by January 20th.
All call sites within MLIR have been converted in previous changes.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D94191
