`linalg.generic` ops with sparse tensors do not necessarily bufferize to
element-wise access, because insertions into a sparse tensor may change
the layout of (or reallocate) the underlying sparse data structures.
Rename interface functions as follows:
* `hasTensorSemantics` -> `hasPureTensorSemantics`
* `hasBufferSemantics` -> `hasPureBufferSemantics`
These two functions return "true" if the op has tensor/buffer operands
but not buffer/tensor operands.
Also drop the "ranked" part from the interface, i.e., do not distinguish
between ranked/unranked types.
The new function names describe the functions more accurately. They also
align their semantics with the notion of "tensor semantics" with the
bufferization framework. (An op is supposed to be bufferized if it has
tensor operands, and we don't care if it also has memref operands.)
This change is in preparation of #75273, which adds
`BufferizableOpInterface::hasTensorSemantics`. By renaming the functions
in the `DestinationStyleOpInterface`, we can avoid name clashes between
the two interfaces.
The operands for which elementwise access is relevant can now be specified. All other operands are ignored. This is useful because only two particular operands participate in a RaW conflict. Furthermore, the two tensors no longer must be equivalent to rule out conflicts due to elementwise access. Equivalent tensor sets may be formed after an inplace bufferization decision is made. The two tensors are actually not required to be equivalent. The only important thing is that they have "equivalent" indexing into the same base buffer.
Differential Revision: https://reviews.llvm.org/D158428
Before this change, two equivalent operands that bufferize to a memory read and write, respectively, were always conflicting. This change improves the analysis for ops that bufferize to element-wise access. Such ops can bufferize in-place, because an original element value is not needed anymore after computing and writing an updated element value.
This change allows ops such as the following one to bufferize in-place:
```
%0 = linalg.elemwise_binary {fun = #linalg.binary_fn<add>}
ins(%a, %b : tensor<5xf32>, tensor<5xf32>)
outs(%a : tensor<5xf32>) -> tensor<5xf32>
```
Differential Revision: https://reviews.llvm.org/D156887
* `getAliasingOpOperand` => `getAliasingOpOperands`
* `getAliasingOpResult` => `getAliasingOpResults`
Also a few minor code cleanups and better documentation.
Differential Revision: https://reviews.llvm.org/D142979
This is the second (and final) step of making "destination style" usable without depending on the Linalg dialect. (The first step was D135129.)
This change allows us to provide default bufferization implementations for all destination-style ops. It also allows us to simplify `TilingInterface`. (E.g., `getDestinationOperands` can be removed.)
Differential Revision: https://reviews.llvm.org/D136179
Now that C++17 is enabled in LLVM, a lot of the TODOs and patterns to emulate C++17 features can be eliminated.
The steps I have taken were essentially:
```
git grep C++17
git grep c++17
git grep "initializer_list<int>"
```
and address given comments and patterns.
Most of the changes boiled down to just using fold expressions rather than initializer_list.
While doing this I also discovered that Clang by default restricts the depth of fold expressions to 256 elements. I specifically hit this with `TestDialect` in `addOperations`. I opted to not replace it with fold expressions because of that but instead adding a comment documenting the issue.
If any other functions may be called with more than 256 elements in the future we might have to revert other parts as well.
I don't think this is a common occurence besides the `TestDialect` however. If need be, this could potentially be fixed via `mlir-tblgen` in the future.
Differential Revision: https://reviews.llvm.org/D131323
With the recent refactorings, this class is no longer needed. We can use BufferizationOptions in all places were BufferizationState was used.
Differential Revision: https://reviews.llvm.org/D127653
This change changes the bufferization so that it utilizes the new TensorCopyInsertion pass. One-Shot Bufferize no longer calls the One-Shot Analysis. Instead, it relies on the TensorCopyInsertion pass to make the entire IR fully inplacable. The `bufferize` implementations of all ops are simplified; they no longer have to account for out-of-place bufferization decisions. These were already materialized in the IR in the form of `bufferization.alloc_tensor` ops during the TensorCopyInsertion pass.
Differential Revision: https://reviews.llvm.org/D127652
This change adds a new op `alloc_tensor` to the bufferization dialect. During bufferization, this op is always lowered to a buffer allocation (unless it is "eliminated" by a pre-processing pass). It is useful to have such an op in tensor land, because it allows users to model tensor SSA use-def chains (which drive bufferization decisions) and because tensor SSA use-def chains can be analyzed by One-Shot Bufferize, while memref values cannot.
This change also replaces all uses of linalg.init_tensor in bufferization-related code with bufferization.alloc_tensor.
linalg.init_tensor and bufferization.alloc_tensor are similar, but the purpose of the former one is just to carry a shape. It does not indicate a memory allocation.
linalg.init_tensor is not suitable for modelling SSA use-def chains for bufferization purposes, because linalg.init_tensor is marked as not having side effects (in contrast to alloc_tensor). As such, it is legal to move linalg.init_tensor ops around/CSE them/etc. This is not desirable for alloc_tensor; it represents an explicit buffer allocation while still in tensor land and such allocations should not suddenly disappear or get moved around when running the canonicalizer/CSE/etc.
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Differential Revision: https://reviews.llvm.org/D126003
Insert a buffer copy unless the dims are guaranteed to be collapsible. In the verifier, accept collapses unless they are guaranteed to be non-collapsible.
Differential Revision: https://reviews.llvm.org/D123316
The current dialect registry allows for attaching delayed interfaces, that are added to attrs/dialects/ops/etc.
when the owning dialect gets loaded. This is clunky for quite a few reasons, e.g. each interface type has a
separate tracking structure, and is also quite limiting. This commit refactors this delayed mutation of
dialect constructs into a more general DialectExtension mechanism. This mechanism is essentially a registration
callback that is invoked when a set of dialects have been loaded. This allows for attaching interfaces directly
on the loaded constructs, and also allows for loading new dependent dialects. The latter of which is
extremely useful as it will now enable dependent dialects to only apply in the contexts in which they
are necessary. For example, a dialect dependency can now be conditional on if a user actually needs the
interface that relies on it.
Differential Revision: https://reviews.llvm.org/D120367
In D115022, we introduced an optimization where OpResults of a `linalg.generic` may bufferize in-place with an "in" OpOperand if the corresponding "out" OpOperand is not used in the computation.
This optimization can lead to unexpected behavior if the newly chosen OpOperand is in the same alias set as another OpOperand (that is used in the computation). In that case, the newly chosen OpOperand must bufferize out-of-place. This can be confusing to users, as always choosing the "out" OpOperand (regardless of whether it is used) would be expected when having the notion of "destination-passing style" in mind.
With this change, we go back to always bufferizing in-place with "out" OpOperands by default, but letting users override the behavior with a bufferization option.
Differential Revision: https://reviews.llvm.org/D120182
