This commit folds a `tensor.cast` op into a `tensor.collapse_shape` op
when following two conditions meet:
1. the `tensor.collapse_shape` op consumes result of the `tensor.cast` op.
2. `tensor.cast` op casts to a more dynamic version of the source tensor.
This is added as a canonicalization pattern in `tensor.collapse_shape` op.
Signed-Off-By: Gaurav Shukla <gaurav@nod-labs.com>
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D130650
The result shape of a rank-reducing subview cannot be inferred in the general case. Just the result rank is not enough. The only thing that we can infer is the layout map.
This change also improves the bufferization patterns of tensor.extract_slice and tensor.insert_slice to fully support rank-reducing operations.
Differential Revision: https://reviews.llvm.org/D129144
This revision updates the op semantics to also allow rank-reducing behavior as well
as updates the implementation to reuse code between the sequential and the parallel
version of the op.
Depends on D128920
Differential Revision: https://reviews.llvm.org/D128985
This is moslty NFC and will allow tensor.parallel_insert_slice to gain
rank-reducing semantics by reusing the vast majority of the tensor.insert_slice impl.
Depends on D128857
Differential Revision: https://reviews.llvm.org/D128920
All bufferizable ops that bufferize to an allocation receive a `bufferization.escape` attribute during TensorCopyInsertion.
Differential Revision: https://reviews.llvm.org/D128137
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
It is sometimes better to make a copy of the OpResult instead of making a copy of the OpOperand. E.g., when bufferizing tensor.extract_slice.
This implementation will eventually make parts of extract_slice's `bufferize` implementation obsolete (and simplify it). It will only need to handle in-place OpOperands.
Differential Revision: https://reviews.llvm.org/D126819
This simplifies the bufferization itself and is in preparation of connecting with the sparse compiler.
Differential Revision: https://reviews.llvm.org/D126814
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
This changes replaces the `fully-dynamic-layout-maps` options (which was badly named) with two new options:
* `unknown-type-conversion` controls the layout maps on buffer types for which no layout map can be inferred.
* `function-boundary-type-conversion` controls the layout maps on buffer types inside of function signatures.
Differential Revision: https://reviews.llvm.org/D125615
This patch augments the `tensor-bufferize` pass by adding a conversion
rule to translate ReshapeOp from the `tensor` dialect to the `memref`
dialect, in addition to adding a unit test to validate the translation.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D125031
Run `one-shot-bufferize` instead of `linalg-comprehensive-module-bufferize` and move some test cases to their respective dialects.
Differential Revision: https://reviews.llvm.org/D124323
This change fixes `CollapsedLayoutMap` for cases where the collapsed
dims are size 1. The cases where inner most dims are size 1 and
noncontiguous can be represented by the strided form and therefore can
be allowed. For such cases, the new stride should be of the next entry
in an association whose dimension is not size 1. If the next entry is
dynamic, it's not possible to decide which stride to use at compilation
time and the stride is set to dynamic.
Differential Revision: https://reviews.llvm.org/D124137
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
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
Reland Note: Adds a fix to properly mark a commutative operation as folded if we change the order
of its operands. This was uncovered by the fact that we no longer re-process constants.
This avoids accidentally reversing the order of constants during successive
application, e.g. when running the canonicalizer. This helps reduce the number
of iterations, and also avoids unnecessary changes to input IR.
Fixes#51892
Differential Revision: https://reviews.llvm.org/D122692
https://reviews.llvm.org/D122641 introduced fixes to the ExpandShapeOp verifier
but also introduced an artificial layout limitation that prevents the consideration of transposed layouts.
This revision fixes the omissions and reimplements the logic using saturated arithmetic which is more
idiomatic and avoids leaking internal implementation details.
Tests cases are added for transposed layouts.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D122845
This reverts commit 59bbc7a0851b6e0054bb3ed47df0958822f08880.
This exposes an issue breaking the contract of
`applyPatternsAndFoldGreedily` where we "converge" without applying
remaining patterns.
This avoids accidentally reversing the order of constants during successive
application, e.g. when running the canonicalizer. This helps reduce the number
of iterations, and also avoids unnecessary changes to input IR.
Fixes#51892
Differential Revision: https://reviews.llvm.org/D122692
Infer a tighter MemRef type instead of always falling back to the most dynamic MemRef type. This is inefficient and caused op verification errors.
Differential Revision: https://reviews.llvm.org/D122649
This commit moves FuncOp out of the builtin dialect, and into the Func
dialect. This move has been planned in some capacity from the moment
we made FuncOp an operation (years ago). This commit handles the
functional aspects of the move, but various aspects are left untouched
to ease migration: func::FuncOp is re-exported into mlir to reduce
the actual API churn, the assembly format still accepts the unqualified
`func`. These temporary measures will remain for a little while to
simplify migration before being removed.
Differential Revision: https://reviews.llvm.org/D121266
This improves the modularity of the bufferization.
From now on, all ops that do not implement BufferizableOpInterface are considered hoisting barriers. Previously, all ops that do not implement the interface were not considered barriers and such ops had to be marked as barriers explicitly. This was unsafe because we could've hoisted across unknown ops where it was not safe to hoist.
As a side effect, this allows for cleaning up AffineBufferizableOpInterfaceImpl. This build unit no longer needed and can be deleted.
Differential Revision: https://reviews.llvm.org/D121519
In this CL, update the function name of verifier according to the
behavior. If a verifier needs to access the region then it'll be updated
to `verifyRegions`.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D120373
The last remaining operations in the standard dialect all revolve around
FuncOp/function related constructs. This patch simply handles the initial
renaming (which by itself is already huge), but there are a large number
of cleanups unlocked/necessary afterwards:
* Removing a bunch of unnecessary dependencies on Func
* Cleaning up the From/ToStandard conversion passes
* Preparing for the move of FuncOp to the Func dialect
See the discussion at https://discourse.llvm.org/t/standard-dialect-the-final-chapter/6061
Differential Revision: https://reviews.llvm.org/D120624
Add a pattern matcher for ExtractSliceOp when its source is a constant.
The matching heuristics can be governed by the control function since
generating a new constant is not always beneficial.
Differential Revision: https://reviews.llvm.org/D119605
This change changes the handling of trailing dimensions with unknown
extent. Users of the changessociationIndicesForReshape helper should
see benefits when transforming reshape like operations into
expand/collapse pairs if the higher-rank type has trailing unknown
dimensions.
The motivating example is a reshape from tensor<16x1x?xi32> to
tensor<16xi32> that can be modeled as collapsing the three dimensions.
Differential Revision: https://reviews.llvm.org/D119730
This commit adds a pattern to wrap a tensor.pad op with
an scf.if op to separate the cases where we don't need padding
(all pad sizes are actually zeros) and where we indeed need
padding.
This pattern is meant to handle padding inside tiled loops.
Under such cases the padding sizes typically depend on the
loop induction variables. Splitting them would allow treating
perfect tiles and edge tiles separately.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D117018
This is part of the larger effort to split the standard dialect. This will also allow for pruning some
additional dependencies on Standard (done in a followup).
Differential Revision: https://reviews.llvm.org/D118202
This commit switches the `tensor-bufferize` pass over to BufferizableOpInterface-based bufferization.
Differential Revision: https://reviews.llvm.org/D118246
If we are extracting it is more useful to push the index_cast past the
extraction. This increases the chance the tensor.extract can evaluated at
compile time.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D118204
There is not much of a benefit to reshape a from element vs reloading it.
Updated to progagate shape manipulations into the output type of
tensor.from_elements.
Reviewed By: NatashaKnk
Differential Revision: https://reviews.llvm.org/D118201
