Operation memref.reinterpret_cast was accept input like:
%out = memref.reinterpret_cast %in to offset: [%offset], sizes: [10],
strides: [1]
: memref<?xf32> to memref<10xf32>
A problem arises: while lowering, the true offset of %out is %offset,
but its data type indicates an offset of 0. Permitting this
inconsistency can result in incorrect outcomes, as certain pass might
erroneously extract the offset from the data type of %out.
This patch fixes this by enforcing that the return value's data type
aligns
with the input parameter.
Updates the return type of `getNumDynamicDims` and `getNumScalableDims`
from `int64_t` to `size_t`. This is for consistency with other
helpers/methods that return "size" and to reduce the number of
`static_cast`s in various places.
Add a convenience builder that infers the result type of
`memref.reinterpret_cast`.
Note: It is not possible to remove the result type from all builder
overloads because this op currently also allows certain
operand/attribute + result type combinations that do not match. The op
verifier should probably be made stricter, but that's a larger change
that requires additional `memref.cast` ops in some places that build
`reinterpret_cast` ops.
It is possible to have a subview with a fully static size and a type
that matches the source type, but a dynamic offset that may be
different. However, currently the memref dialect folds:
```mlir
func.func @subview_of_static_full_size(
%arg0: memref<16x4xf32, strided<[4, 1], offset: ?>>, %idx: index)
-> memref<16x4xf32, strided<[4, 1], offset: ?>>
{
%0 = memref.subview %arg0[%idx, 0][16, 4][1, 1]
: memref<16x4xf32, strided<[4, 1], offset: ?>>
to memref<16x4xf32, strided<[4, 1], offset: ?>>
return %0 : memref<16x4xf32, strided<[4, 1], offset: ?>>
}
```
To:
```mlir
func.func @subview_of_static_full_size(
%arg0: memref<16x4xf32, strided<[4, 1], offset: ?>>, %arg1: index)
-> memref<16x4xf32, strided<[4, 1], offset: ?>>
{
return %arg0 : memref<16x4xf32, strided<[4, 1], offset: ?>>
}
```
Which drops the dynamic offset from the `subview` op.
This change removes dependencies declared as either 'LINK_LIBS' or
'LINK_COMPONENTS' across several MLIR libraries. The removed
dependencies appear
to be incorrect and may have been required in older versions of the
project.
These dependencies cause many high level dialects to have transitive
dependence on the LLVM dialect and the LLVM 'Core' library
('llvm/lib/IR').
Note that if using the 'Ninja' CMake generator, one can inspect the
dependencies
(including all transitive libraries) of any given MLIR target but using
the command `ninja -C <build dir> -t browse` and navigating to the
library
of interest in a web browser.
The `elementPtrs` has changed meaning over time and the name is now
outdated which may be confusing. This PR updates it to a name
representative of current usage.
The `memref.subview` result type inference
(`SubViewOp::inferResultType`) sometimes used to produce a dynamic
offset when a static offset is possible.
When a dynamic value (stride, size, etc.) is multiplied with zero, the
result is always a "static 0". Based on this, the result type inference
implementation can be improved to produce more static type information
in memref types.
Implement folding and rewrite logic to eliminate no-op tensor and memref
operations. This handles two specific cases:
1. tensor.insert_slice operations where the size of the inserted slice
is known to be 0.
2. memref.copy operations where either the source or target memrefs are
known to be emtpy.
Co-authored-by: Spenser Bauman <sabauma@fastmail>
Previously this was only populated in the create method later. This
resolves some of invalid builder paths. This may also be sufficient that
type inference functions no longer have to consider whether property
conversion has happened (but haven't verified that yet).
This also makes Attributes corresponding to Properties as optional
inside the set from attributes method. Today that is in effect what
happens with Property value initialization and folks use it to define
custom C++ types whose default initialization is what they want. This is
the behavior users get if they use properties directly. Propagating
Attributes without allowing partial setting would require iterating over
the dictionary attribute considering the properties of the op type that
will be created. This could also have been an additional method
generated or optional behavior on the set method. But doing it
consistently seems better. In terms of whats lost, it doesn't seem like
anything compared to the pure Property path where Property is default
value initialized and then partially overwritten (this doesn't seem to
buy anything else verification wise).
Default valued Properties (as specified ODS side rather than C++ side)
triggered error as the containing class was not yet complete but
referenced nested class, so that we couldn't have default initializer
for them in the parent class. Added an additional forwarding builder to
avoid needing to update call sites. This could be split out to separate
change.
Inlined templated function in unit test that was only used once. Moved
initialization earlier where seen.
This commit extends the SROA interfaces to ensure the interface
instantiations can communicate newly created allocators to the
algorithm. This ensures that the SROA implementation does no longer
require re-walking the IR to find new allocators.
This commit fixes Mem2Regs mutli-slot allocator handling and extends the
test dialect to test this.
Additionally, this modifies Mem2Reg's API to always attempt a full
promotion on all the passed in "allocators". This ensures that the pass
does not require unnecessary walks over the regions and improves caching
benefits.
I'm planning to remove StringRef::equals in favor of
StringRef::operator==.
- StringRef::operator==/!= outnumber StringRef::equals by a factor of
10 under mlir/ in terms of their usage.
- The elimination of StringRef::equals brings StringRef closer to
std::string_view, which has operator== but not equals.
- S == "foo" is more readable than S.equals("foo"), especially for
!Long.Expression.equals("str") vs Long.Expression != "str".
Torch-mlir integration is currently blocked on `memref.expand_shape`
verifier errors of the form
```
'memref.expand_shape' op invalid output shape provided at pos 1
```
The verifier code generating these errors was introduced in
https://github.com/llvm/llvm-project/pull/91245. I have commented there
why I believe it's incorrect. This PR has my suggested fix.
Unfortunately, this does not seem to be directly testable on `memref`
IR, because `static_output_shape` is not directly exposed in the custom
assembly format.
This commit changes the `MemorySlotInterface` back to using `OpBuilder`
instead of a rewriter. This was originally introduced in
https://reviews.llvm.org/D150432 but it was shown that patterns are a
bad idea for both Mem2Reg and SROA.
Mem2Reg suffers from the usage of a rewriter due to being forced to
create new basic blocks. This is an issue, as it leads to the
invalidation of the dominance information, which can be expensive to
recompute.
This is a new take on #89111. Now that #90040 is merged, this has become
trivial to implement. The added test shows the kind of benefit that we
get from this: now dim-of-expand-shape naturally folds without us
needing to implement an ad-hoc folding rewrite.
This patch generalizes tensor.expand_shape and memref.expand_shape to
consume the output shape as a list of SSA values. This enables us to
implement generic reshape operations with dynamic shapes using
collapse_shape/expand_shape pairs.
The output_shape input to expand_shape follows the static/dynamic
representation that's also used in `tensor.extract_slice`.
Differential Revision: https://reviews.llvm.org/D140821
---------
Signed-off-by: Gaurav Shukla<gaurav.shukla@amd.com>
Signed-off-by: Gaurav Shukla <gaurav.shukla@amd.com>
Co-authored-by: Ramiro Leal-Cavazos <ramiroleal050@gmail.com>
This commit enhances the LLVM dialect's Mem2Reg interfaces to support
partial stores to memory slots. To achieve this support, the `getStored`
interface method has to be extended with a parameter of the reaching
definition, which is now necessary to produce the resulting value after
this store.
This patch generalizes tensor.expand_shape and memref.expand_shape to
consume the output shape as a list of SSA values. This enables us to
implement generic reshape operations with dynamic shapes using
collapse_shape/expand_shape pairs.
The output_shape input to expand_shape follows the static/dynamic
representation that's also used in `tensor.extract_slice`.
Differential Revision: https://reviews.llvm.org/D140821
Co-authored-by: Ramiro Leal-Cavazos <ramiroleal050@gmail.com>
This commit improves LLVM dialect's Mem2Reg interfaces to support
promotions of partial loads from larger memory slots. To support this,
the Mem2Reg interface methods are extended with additional data layout
parameters. The data layout is required to determine type sizes to
produce correct conversion sequences.
Note: There will be additional followups that introduce a similar
functionality for stores, and there are plans to support accesses into
the middle of memory slots.
This commit relaxes the assumption of type consistency for LLVM dialect
load and store operations in SROA. Instead, there is now a check that
loads and stores are in the bounds specified by the sub-slot they
access.
This commit additionally removes the corresponding patterns from the
type consistency pass, as they are no longer necessary.
Note: It will be necessary to extend Mem2Reg with the logic for
differently sized accesses as well. This is non-the-less a strict
upgrade for productive flows, as the type consistency pass can produce
invalid IR for some odd cases.
This commit expends the Mem2Reg and SROA interface methods with passed
in handles to a `DataLayout` structure. This is done to avoid
superfluous retreiving of data layouts during each conversion of
intrinsics.
This change, additionally, enables subsequent changes to make the LLVM
dialect implementation of these interfaces type agnostic.
This PR adds promised interface declarations for all interfaces declared
in `InitAllDialects.h`.
Promised interfaces allow a dialect to declare that it will have an
implementation of a particular interface, crashing the program if one
isn't provided when the interface is used.
The current canonicalization of `memref.dim` operating on the result of
`memref.reshape` into `memref.load` is incorrect as it doesn't check
whether the `index` operand of `memref.dim` dominates the source
`memref.reshape` op. It always introduces `memref.load` right after
`memref.reshape` to ensure the `memref` is not mutated before the
`memref.load` call. As a result, the following error is observed:
```
$> mlir-opt --canonicalize input.mlir
func.func @reshape_dim(%arg0: memref<*xf32>, %arg1: memref<?xindex>, %arg2: index) -> index {
%c4 = arith.constant 4 : index
%reshape = memref.reshape %arg0(%arg1) : (memref<*xf32>, memref<?xindex>) -> memref<*xf32>
%0 = arith.muli %arg2, %c4 : index
%dim = memref.dim %reshape, %0 : memref<*xf32>
return %dim : index
}
```
results in:
```
dominator.mlir:22:12: error: operand #1 does not dominate this use
%dim = memref.dim %reshape, %0 : memref<*xf32>
^
dominator.mlir:22:12: note: see current operation: %1 = "memref.load"(%arg1, %2) <{nontemporal = false}> : (memref<?xindex>, index) -> index
dominator.mlir:21:10: note: operand defined here (op in the same block)
%0 = arith.muli %arg2, %c4 : index
```
Properly fixing this issue requires a dominator analysis which is
expensive to run within a canonicalization pattern. So, this patch fixes
the canonicalization pattern by being more strict/conservative about the
legality condition in which we perform this canonicalization.
The more general pattern is also added to `tensor.dim`. Since tensors are
immutable we don't need to worry about where to introduce the
`tensor.extract` call after canonicalization.
Before: op verifiers failed if the input and output ranks were the same
(i.e. no expansion or collapse). This behavior requires users of these
shape ops to verify manually that they are not creating identity
versions of these ops every time they build them -- problematic. This PR
removes this strict verification, and introduces folders for the the
identity cases.
The PR also removes the special case handling of rank-0 tensors for
expand_shape and collapse_shape, there doesn't seem to be any reason to
treat them differently.
When creating a new block in (conversion) rewrite patterns,
`OpBuilder::createBlock` must be used. Otherwise, no
`notifyBlockInserted` notification is sent to the listener.
Note: The dialect conversion relies on listener notifications to keep
track of IR modifications. Creating blocks without the builder API can
lead to memory leaks during rollback.
The `memref.subview` verifier currently checks result shape, element type, memory space and offset of the result type. However, the strides of the result type are currently not verified. This commit adds verification of result strides for non-rank reducing ops and fixes invalid IR in test cases.
Verification of result strides for ops with rank reductions is more complex (and there could be multiple possible result types). That is left for a separate commit.
Also refactor the implementation a bit:
* If `computeMemRefRankReductionMask` could not compute the dropped dimensions, there must be something wrong with the op. Return `FailureOr` instead of `std::optional`.
* `isRankReducedMemRefType` did much more than just checking whether the op has rank reductions or not. Inline the implementation into the verifier and add better comments.
* `produceSubViewErrorMsg` does not have to be templatized.
* Fix comment and add additional assert to `ExpandStridedMetadata.cpp`, to make sure that the memref.subview verifier is in sync with the memref.subview -> memref.reinterpret_cast lowering.
Note: This change is identical to #79865, but with a fixed comment and an additional assert in `ExpandStridedMetadata.cpp`. (I reverted #79865 in #80116, but the implementation was actually correct, just the comment in `ExpandStridedMetadata.cpp` was confusing.)
Reverts llvm/llvm-project#79865
I think there is a bug in the stride computation in
`SubViewOp::inferResultType`. (Was already there before this change.)
Reverting this commit for now and updating the original pull request
with a fix and more test cases.
The `memref.subview` verifier currently checks result shape, element
type, memory space and offset of the result type. However, the strides
of the result type are currently not verified. This commit adds
verification of result strides for non-rank reducing ops and fixes
invalid IR in test cases.
Verification of result strides for ops with rank reductions is more
complex (and there could be multiple possible result types). That is
left for a separate commit.
Also refactor the implementation a bit:
* If `computeMemRefRankReductionMask` could not compute the dropped
dimensions, there must be something wrong with the op. Return
`FailureOr` instead of `std::optional`.
* `isRankReducedMemRefType` did much more than just checking whether the
op has rank reductions or not. Inline the implementation into the
verifier and add better comments.
* `produceSubViewErrorMsg` does not have to be templatized.
This folded casts into `memref.transpose` without updating the result
type of the transpose op, which resulted in IR that failed to verify for
statically sized memrefs.
i.e.
```mlir
%cast = memref.cast %0 : memref<?x4xf32> to memref<?x?xf32>
%transpose = memref.transpose %cast : memref<?x?xf32> to memref<?x?xf32>
```
would fold to:
```mlir
// Fails verification:
%transpose = memref.transpose %cast : memref<?x4xf32> to memref<?x?xf32>
```
This commit renames 4 pattern rewriter API functions:
* `updateRootInPlace` -> `modifyOpInPlace`
* `startRootUpdate` -> `startOpModification`
* `finalizeRootUpdate` -> `finalizeOpModification`
* `cancelRootUpdate` -> `cancelOpModification`
The term "root" is a misnomer. The root is the op that a rewrite pattern
matches against
(https://mlir.llvm.org/docs/PatternRewriter/#root-operation-name-optional).
A rewriter must be notified of all in-place op modifications, not just
in-place modifications of the root
(https://mlir.llvm.org/docs/PatternRewriter/#pattern-rewriter). The old
function names were confusing and have contributed to various broken
rewrite patterns.
Note: The new function names use the term "modify" instead of "update"
for consistency with the `RewriterBase::Listener` terminology
(`notifyOperationModified`).
Currently, the `memref.transpose` verifier forces the result type of the
Op to have an explicit `StridedLayoutAttr` via the method
`inferTransposeResultType`. This means that the example Op
given in the documentation is actually invalid because it uses an `AffineMap`
to specify the layout.
It also means that we can't "un-transpose" a transposed memref back to
the implicit layout form, because the verifier will always enforce the
explicit strided layout.
This patch makes the following changes:
1. The verifier checks whether the canonicalized strided layout of the
result Type is identitcal to the canonicalized infered result type
layout. This way, it's only important that the two Types have the same
strided layout, not necessarily the same representation of it.
2. The folder is extended to support folding away the trivial case of
identity permutation and to fold one transposition into another by
composing the permutation maps.
This PR adds promised interface declarations for
`ConvertToLLVMPatternInterface` in all the dialects that support the
`ConvertToLLVM` dialect extension.
Promised interfaces allow a dialect to declare that it will have an
implementation of a particular interface, crashing the program if one
isn't provided when the interface is used.
Fixes https://github.com/llvm/llvm-project/issues/71326.
The cause of the issue was that a new `LoadOp` was created which looked
something like:
```mlir
%arg4 =
func.func main(%arg1 : index, %arg2 : index) {
%alloca_0 = memref.alloca() : memref<vector<1x32xi1>>
%1 = vector.type_cast %alloca_0 : memref<vector<1x32xi1>> to memref<1xvector<32xi1>>
%2 = memref.load %1[%arg1, %arg2] : memref<1xvector<32xi1>>
return
}
```
which crashed inside the `LoadOp::verify`. Note here that `%alloca_0` is
0 dimensional, `%1` has one dimension, but `memref.load` tries to index
`%1` with two indices.
This is now fixed by using the fact that `unpackOneDim` always unpacks
one dim
1bce61e6b0/mlir/lib/Conversion/VectorToSCF/VectorToSCF.cpp (L897-L903)
and so the `loadOp` should just index only one dimension.
---------
Co-authored-by: Benjamin Maxwell <macdue@dueutil.tech>
