D138330 updated the deprecated `getMemorySpaceAsInt` uses to `getMemorySpace`. There are few uses that were missed.
Differential Revision: https://reviews.llvm.org/D139526
MemRef has been accepting a general Attribute as memory space for
a long time. This commits updates bufferization side to catch up,
which allows downstream users to plugin customized symbolic memory
space. This also eliminates quite a few `getMemorySpaceAsInt`
calls, which is deprecated.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D138330
Even though iter_arg and init_arg of an scf.for loop may have the same tensor type, their bufferized memref types are not necessarily equal. It is sometimes necessary to insert a cast in case of differing layout maps.
Differential Revision: https://reviews.llvm.org/D132860
This change generalizes getBufferType. This function can be used to predict the buffer type of any tensor value (not just BlockArguments) without changing any IR. It also subsumes getMemorySpace. This is useful for loop bufferization, where the precise buffer type of an iter_arg cannot be known without examining the loop body.
Differential Revision: https://reviews.llvm.org/D132859
This reland includes changes to the Python bindings.
Switch variadic operand and result segment size attributes to use the
dense i32 array. Dense integer arrays were introduced primarily to
represent index lists. They are a better fit for segment sizes than
dense elements attrs.
Depends on D131801
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D131803
Switch variadic operand and result segment size attributes to use the
dense i32 array. Dense integer arrays were introduced primarily to
represent index lists. They are a better fit for segment sizes than
dense elements attrs.
Depends on D131738
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D131702
This op used to belong to the sparse dialect, but there are use cases for dense bufferization as well. (E.g., when a tensor alloc is returned from a function and should be deallocated at the call site.) This change moves the op to the bufferization dialect, which now has an `alloc_tensor` and a `dealloc_tensor` op.
Differential Revision: https://reviews.llvm.org/D129985
This is a partial revert of D128615.
to_memref(to_tensor(x)) always be folded to x. But to_tensor(to_memref(x)) cannot be folded in the general case because writes to the intermediary memref may go unnoticed.
Differential Revision: https://reviews.llvm.org/D129354
This change updates all remaining bufferization patterns (except for scf.while) and the remaining bufferization infrastructure to infer the memory space whenever possible instead of falling back to "0". (If a default memory space is set in the bufferization options, we still fall back to that value if the memory space could not be inferred.)
Differential Revision: https://reviews.llvm.org/D128423
This attribute is currently supported on AllocTensorOp only. Future changes will add support to other ops. Furthermore, the memory space is not propagated properly in all bufferization patterns and some of the core bufferization infrastructure. This will be addressed in a subsequent change.
Differential Revision: https://reviews.llvm.org/D128274
Putting some direct use restrictions on tensor allocations in the
sparse case enables the use of simplifying assumptions in the
bufferization analysis.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D128463
All bufferizable ops that bufferize to an allocation receive a `bufferization.escape` attribute during TensorCopyInsertion.
Differential Revision: https://reviews.llvm.org/D128137
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
If `copy` is specified, the newly allocated buffer is initialized with the given contents. Also add an optional `escape` attribute to indicate whether the buffer of the tensor may be returned from the parent block (aka. "escape") after bufferization.
This change is in preparation of connecting One-Shot Bufferize to the sparse compiler.
Differential Revision: https://reviews.llvm.org/D126570
No longer pass static dim sizes as an attribute. This was redundant and required extra checks in the verifier. This change also makes the op symmetrical to memref::AllocOp.
Differential Revision: https://reviews.llvm.org/D126178
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
Now that dialect constructors are generated in the .cpp file, we can
drop all of the dependent dialect includes from the .h file.
Differential Revision: https://reviews.llvm.org/D124298
The bufferization driver was previously using a GreedyPatternRewriter. This was problematic because bufferization must traverse ops top-to-bottom. The GreedyPatternRewriter was previously configured via `useTopDownTraversal`, but this was a hack; this API was just meant for performance improvements and should not affect the result of the rewrite.
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Differential Revision: https://reviews.llvm.org/D123618
NFC. Clean up memref utils library. This library had a single function
that was completely misplaced. MemRefUtils is expected to be (also per
its comment) a library providing analysis/transforms utilities on memref
dialect ops or memref types. However, in reality it had a helper that
was depended upon by the MemRef dialect, i.e., it was a helper for the
dialect ops library and couldn't contain anything that itself depends on
the MemRef dialect. Move the single method to the memref dialect that
will now allow actual utilities depending on the memref dialect to be
placed in it.
Put findDealloc in the `memref` namespace. This is a pure move.
Differential Revision: https://reviews.llvm.org/D121273
insert is soft deprecated, so remove all references so it's less likely
to be used and can be easily removed in the future.
Differential Revision: https://reviews.llvm.org/D120021
The pass can currently not handle to_memref(to_tensor(x)) folding where a cast is necessary. This is required with the new unified bufferization. There is already a canonicalization pattern that handles such foldings and it should be used during this pass.
Differential Revision: https://reviews.llvm.org/D117988
OwningRewritePatternList has been deprecated for ~10 months now, we can remove
the leftover using directives at this point.
Differential Revision: https://reviews.llvm.org/D118287
No longer go through an external model. Also put BufferizableOpInterface into the same build target as the BufferizationDialect. This allows for some code reuse between BufferizationOps canonicalizers and BufferizableOpInterface implementations.
Differential Revision: https://reviews.llvm.org/D117987
