Add support to Python bindings for the MLIR execution engine to load a
specified list of shared libraries - for eg. to use MLIR runtime
utility libraries.
Differential Revision: https://reviews.llvm.org/D104009
A test in ir.c makes use of casting a void* to an integer type to print it's address. This cast is currently done with the datatype `long` however, which is only guaranteed to be equal to the pointer width on LP64 system. Other platforms may use a length not equal to the pointer width. 64bit Windows as an example uses 32 bit for `long` which does not match the 64 bit pointers.
This also results in clang warning due to `-Wvoid-pointer-to-int-cast`.
Technically speaking, since the test only passes the value 42, it does not cause any issues, but it'd be nice to fix the warning at least.
Differential Revision: https://reviews.llvm.org/D103085
Also, fix a small typo where the "unsigned" splat variants were not
being created with an unsigned type.
Differential Revision: https://reviews.llvm.org/D102797
At the moment `MlirModule`s can be converted to `MlirOperation`s, but not
the other way around (at least not without going around the C API). This
makes it impossible to e.g. run passes over a `ModuleOp` created through
`mlirOperationCreate`.
Reviewed By: nicolasvasilache, mehdi_amini
Differential Revision: https://reviews.llvm.org/D102497
Provide an option to specify optimization level when creating an
ExecutionEngine via the MLIR JIT Python binding. Not only is the
specified optimization level used for code generation, but all LLVM
optimization passes at the optimization level are also run prior to
machine code generation (akin to the mlir-cpu-runner tool).
Default opt level continues to remain at level two (-O2).
Contributions in part from Prashant Kumar <prashantk@polymagelabs.com>
as well.
Differential Revision: https://reviews.llvm.org/D102551
* Adds dialect registration, hand coded 'encoding' attribute and test.
* An MLIR CAPI tablegen backend for attributes does not exist, and this is a relatively complicated case. I opted to hand code it in a canonical way for now, which will provide a reasonable blueprint for building out the tablegen version in the future.
* Also added a (local) CMake function for declaring new CAPI tests, since it was getting repetitive/buggy.
Differential Revision: https://reviews.llvm.org/D102141
This adds `mlirOperationSetOperand` to the IR C API, similar to the
function to get an operand.
In the Python API, this adds `operands[index] = value` syntax, similar
to the syntax to get an operand with `operands[index]`.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D101398
This CL introduces a generic attribute (called "encoding") on tensors.
The attribute currently does not carry any concrete information, but the type
system already correctly determines that tensor<8xi1,123> != tensor<8xi1,321>.
The attribute will be given meaning through an interface in subsequent CLs.
See ongoing discussion on discourse:
[RFC] Introduce a sparse tensor type to core MLIR
https://llvm.discourse.group/t/rfc-introduce-a-sparse-tensor-type-to-core-mlir/2944
A sparse tensor will look something like this:
```
// named alias with all properties we hold dear:
#CSR = {
// individual named attributes
}
// actual sparse tensor type:
tensor<?x?xf64, #CSR>
```
I see the following rough 5 step plan going forward:
(1) introduce this format attribute in this CL, currently still empty
(2) introduce attribute interface that gives it "meaning", focused on sparse in first phase
(3) rewrite sparse compiler to use new type, remove linalg interface and "glue"
(4) teach passes to deal with new attribute, by rejecting/asserting on non-empty attribute as simplest solution, or doing meaningful rewrite in the longer run
(5) add FE support, document, test, publicize new features, extend "format" meaning to other domains if useful
Reviewed By: stellaraccident, bondhugula
Differential Revision: https://reviews.llvm.org/D99548
In particular for Graph Regions, the terminator needs is just a
historical artifact of the generalization of MLIR from CFG region.
Operations like Module don't need a terminator, and before Module
migrated to be an operation with region there wasn't any needed.
To validate the feature, the ModuleOp is migrated to use this trait and
the ModuleTerminator operation is deleted.
This patch is likely to break clients, if you're in this case:
- you may iterate on a ModuleOp with `getBody()->without_terminator()`,
the solution is simple: just remove the ->without_terminator!
- you created a builder with `Builder::atBlockTerminator(module_body)`,
just use `Builder::atBlockEnd(module_body)` instead.
- you were handling ModuleTerminator: it isn't needed anymore.
- for generic code, a `Block::mayNotHaveTerminator()` may be used.
Differential Revision: https://reviews.llvm.org/D98468
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
This adds minimalistic bindings for the execution engine, allowing to
invoke the JIT from the C API. This is still quite early and
experimental and shouldn't be considered stable in any way.
Differential Revision: https://reviews.llvm.org/D96651
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
Replace MlirDialectRegistrationHooks with MlirDialectHandle, which under-the-hood is an opaque pointer to MlirDialectRegistrationHooks. Then we expose the functionality previously directly on MlirDialectRegistrationHooks, as functions which take the opaque MlirDialectHandle struct. This makes the actual structure of the registration hooks an implementation detail, and happens to avoid this issue: https://llvm.discourse.group/t/strange-swift-issues-with-dialect-registration-hooks/2759/3
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D96229
* Adds a flag to MlirOperationState to enable result type inference using the InferTypeOpInterface.
* I chose this level of implementation for a couple of reasons:
a) In the creation flow is naturally where generated and custom builder code will be invoking such a thing
b) it is a bit more efficient to share the data structure and unpacking vs having a standalone entry-point
c) we can always decide to expose more of these interfaces with first-class APIs, but that doesn't preclude that we will always want to use this one in this way (and less API surface area for common things is better for API stability and evolution).
* I struggled to find an appropriate way to test it since we don't link the test dialect into anything CAPI accessible at present. I opted instead for one of the simplest ops I found in a regular dialect which implements the interface.
* This does not do any trait-based type selection. That will be left to generated tablegen wrappers.
Differential Revision: https://reviews.llvm.org/D95283
* Registers a small set of sample dialects.
* NFC with respect to existing C-API symbols but some headers have been moved down a level to the Dialect/ sub-directory.
* Adds an additional entry point per dialect that is needed for dynamic discovery/loading.
* See discussion: https://llvm.discourse.group/t/dialects-and-the-c-api/2306/16
Differential Revision: https://reviews.llvm.org/D94370
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
This mirror the C++ API for NamedAttribute, and has the advantage or
internalizing earlier in the Context and not requiring the caller to
keep the StringRef alive beyong this call.
Differential Revision: https://reviews.llvm.org/D93133
This reverts commit 0d48d265db.
This reapplies the following commit, with a fix for CAPI/ir.c:
[mlir] Start splitting the `tensor` dialect out of `std`.
This starts by moving `std.extract_element` to `tensor.extract` (this
mirrors the naming of `vector.extract`).
Curiously, `std.extract_element` supposedly works on vectors as well,
and this patch removes that functionality. I would tend to do that in
separate patch, but I couldn't find any downstream users relying on
this, and the fact that we have `vector.extract` made it seem safe
enough to lump in here.
This also sets up the `tensor` dialect as a dependency of the `std`
dialect, as some ops that currently live in `std` depend on
`tensor.extract` via their canonicalization patterns.
Part of RFC: https://llvm.discourse.group/t/rfc-split-the-tensor-dialect-from-std/2347/2
Differential Revision: https://reviews.llvm.org/D92991
This is part of a larger refactoring the better congregates the builtin structures under the BuiltinDialect. This also removes the problematic "standard" naming that clashes with the "standard" dialect, which is not defined within IR/. A temporary forward is placed in StandardTypes.h to allow time for downstream users to replaced references.
Differential Revision: https://reviews.llvm.org/D92435
While this makes the unit tests a bit more verbose, this simplifies the creation of bindings because only the bidirectional mapping between the host language's string type and MlirStringRef need to be implemented.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D91905
Previously, there was no way to add context to the diagnostic engine via the C API. Adding this ability makes it much easier to reason about memory ownership, particularly in reference-counted languages such as Swift. There are more details in the review comments.
Reviewed By: ftynse, mehdi_amini
Differential Revision: https://reviews.llvm.org/D91738
- Add `mlirElementsAttrGetType` C API.
- Add `def_buffer` binding to PyDenseElementsAttribute.
- Implement the protocol to access the buffer.
Differential Revision: https://reviews.llvm.org/D91021
The tests are intended to exercise the public C API and will link to a
specific shared library exposing only the C API, this library itself may
link to libMLIR.so.
If we link some LLVM library statically in the test themselves, we end
up with duplicated cl::opt registrations in LLVM. A possible setup if
these libraries were needed could be to link libMLIR.so directly when
available and link statically when it isn't available (in which case the
libary exposing the C API would be statically link and isolated from the
cl::opt registry, hopefully).
Differential Revision: https://reviews.llvm.org/D90993
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
The test file is a long list of functions, followed by equally long FileCheck
comments inside "main". Distribute FileCheck comments closer to the functions
that produce the output we are checking.
Reviewed By: mehdi_amini, stellaraccident
Differential Revision: https://reviews.llvm.org/D90743
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
* Removes index based insertion. All insertion now happens through the insertion point.
* Introduces thread local context managers for implicit creation relative to an insertion point.
* Introduces (but does not yet use) binding the Context to the thread local context stack. Intent is to refactor all methods to take context optionally and have them use the default if available.
* Adds C APIs for mlirOperationGetParentOperation(), mlirOperationGetBlock() and mlirBlockGetTerminator().
* Removes an assert in PyOperation creation that was incorrectly constraining. There is already a TODO to rework the keepAlive field that it was guarding and without the assert, it is no worse than the current state.
Differential Revision: https://reviews.llvm.org/D90368
Adam Paszke