The dimension order of a filter in tensorflow is
[filter_height, filter_width, in_channels, out_channels], which is different
from current definition. The current definition follows TOSA spec. Add TF
version conv ops to .tc, so we do not have to insert a transpose op around a
conv op.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D96038
This revision connects the generated sparse code with an actual
sparse storage scheme, which can be initialized from a test file.
Lacking a first-class citizen SparseTensor type (with buffer),
the storage is hidden behind an opaque pointer with some "glue"
to bring the pointer back to tensor land. Rather than generating
sparse setup code for each different annotated tensor (viz. the
"pack" methods in TACO), a single "one-size-fits-all" implementation
has been added to the runtime support library. Many details and
abstractions need to be refined in the future, but this revision
allows full end-to-end integration testing and performance
benchmarking (with on one end, an annotated Lingalg
op and, on the other end, a JIT/AOT executable).
Reviewed By: nicolasvasilache, bixia
Differential Revision: https://reviews.llvm.org/D95847
This reverts commit 11f32a41c2.
The build is broken because this commit conflits with the refactoring of
the DialectRegistry APIs in the context. It'll reland shortly after
fixing the API usage.
This revision fixes the indexing logic into the packed tensor that result from hoisting padding. Previously, the index was incorrectly set to the loop induction variable when in fact we need to compute the iteration count (i.e. `(iv - lb).ceilDiv(step)`).
Differential Revision: https://reviews.llvm.org/D96417
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
This introduces a mechanism to register interfaces for a dialect without making
the dialect itself depend on the interface. The registration request happens on
DialectRegistry and, if the dialect has not been loaded yet, the actual
registration is delayed until the dialect is loaded. It requires
DialectRegistry to become aware of the context that contains it and the context
to expose methods for querying if a dialect is loaded.
This mechanism will enable a simple extension mechanism for dialects that can
have interfaces defined outside of the dialect code. It is particularly helpful
for, e.g., translation to LLVM IR where we don't want the dialect itself to
depend on LLVM IR libraries.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D96137
Previously broadcast was a binary op. Now it can support more inputs.
This has been changed in such a way that for now, this is an NFC for
all broadcast operations that were previously legal.
Differential Revision: https://reviews.llvm.org/D95777
These are similar to maxnum and minnum, but they're defined to treat -0
as less than +0. This behavior can't be expressed using float
comparisons and selects, since comparisons are defined to treat
different-signed zeros as equal. So, the only way to communicate this
behavior into LLVM IR without defining target-specific intrinsics is to
add the corresponding ops.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D96373
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
These properties were useful for a few things before traits had a better integration story, but don't really carry their weight well these days. Most of these properties are already checked via traits in most of the code. It is better to align the system around traits, and improve the performance/cost of traits in general.
Differential Revision: https://reviews.llvm.org/D96088
Add a build method that pads the source with a scalar value.
Reviewed By: nicolasvasilache, antiagainst
Differential Revision: https://reviews.llvm.org/D96343
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
The patch extends the runner utils by verification methods that compare two memrefs. The methods compare the content of the two memrefs and print success if the data is identical up to a small numerical error. The methods are meant to simplify the development of integration tests that for example compare optimized and unoptimized code paths (cf. the updates to the linalg matmul integration tests).
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96326
This commit defines linalg.depthwise_conv_2d_nhwc for depthwise
2-D convolution with NHWC input/output data format.
This op right now only support channel multiplier == 1, which is
the most common case.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94966
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 revision fixes the fact that the padding transformation did not have enough information to set the proper type for the padding value.
Additionally, the verifier for Yield in the presence of PadTensorOp is fixed to properly report incorrect number of results or operands. Previously, the error would be silently ignored which made the core issue difficult to debug.
Differential Revision: https://reviews.llvm.org/D96264
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 will allow to use `NativeOpTrait` and Operations
declared outside of `mlir` namespace.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D96128
This new invoke will pack a list of argument before calling the
`invokePacked` method. It accepts returned value as output argument
wrapped in `ExecutionEngine::Result<T>`, and delegate the packing of
arguments to a trait to allow for customization for some types.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D95961
These patterns move vector.bitcast ops to be before
insert ops or after extract ops where suitable.
With them, bitcast will happen on smaller vectors
and there are more chances to share extract/insert
ops.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D96040
Those types are not needed any longer since LLVM dialect
has migrated to using MLIR's I1, I8, I32 types directly.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D96127
This patch adds patterns to use vector.shape_cast to cast
away leading 1-dimensions from a few vector operations.
It allows exposing more canonical forms of vector.transfer_read,
vector.transfer_write, vector_extract_strided_slice, and
vector.insert_strided_slice. With this, we can have more
opportunity to cancelling extract/insert ops or forwarding
write/read ops.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D95873
The `AffineMap` class follows the same semantic as Type and Attribute.
It is immutable object, so it make sence to mark its methods as const.
Also part of its API is already marked as const, this change just make the API consistent.
Reviewed By: ftynse, bondhugula
Differential Revision: https://reviews.llvm.org/D96026
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
To allow it usage for Operation classes defined outside of `mlir` namespace.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D95952
* Introduce separate `RankedTensorOf` class. Use it as base class for `AnyRankedTensor`.
* Add C++ class specification (`::mlir::MemRefType`) to `MemRefRankOf` and `StaticShapeMemRefOf`.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D95936
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
