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and getMemRefRegion() to work with specified loop depths; add support for
outgoing DMAs, store op's.
- add support for getMemRefRegion symbolic in outer loops - hence support for
DMAs symbolic in outer surrounding loops.
- add DMA generation support for outgoing DMAs (store op's to lower memory
space); extend getMemoryRegion to store op's. -memref-bound-check now works
with store op's as well.
- fix dma-generate (references to the old memref in the dma_start op were also
being replaced with the new buffer); we need replace all memref uses to work
only on a subset of the uses - add a new optional argument for
replaceAllMemRefUsesWith. update replaceAllMemRefUsesWith to take an optional
'operation' argument to serve as a filter - if provided, only those uses that
are dominated by the filter are replaced.
- Add missing print for attributes for dma_start, dma_wait op's.
- update the FlatAffineConstraints API
PiperOrigin-RevId: 221889223
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PiperOrigin-RevId: 221795407
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Array attributes can nested and function attributes can appear anywhere at that
level. They should be remapped to point to the generated CFGFunction after
ML-to-CFG conversion, similarly to plain function attributes. Extract the
nested attribute remapping functionality from the Parser to Utils. Extract out
the remapping function for individual Functions from the module remapping
function. Use these new functions in the ML-to-CFG conversion pass and in the
parser.
PiperOrigin-RevId: 221510997
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These functions are declared in Transforms/LoopUtils.h (included to the
Transforms/Utils library) but were defined in the loop unrolling pass in
Transforms/LoopUnroll.cpp. As a result, targets depending only on
TransformUtils library but not on Transforms could get link errors. Move the
definitions to Transforms/Utils/LoopUtils.cpp where they should actually live.
This does not modify any code.
PiperOrigin-RevId: 221508882
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Change the storage type to APInt from int64_t for IntegerAttr (following the change to APFloat storage in FloatAttr). Effectively a direct change from int64_t to 64-bit APInt throughout (the bitwidth hardcoded). This change also adds a getInt convenience method to IntegerAttr and replaces previous getValue calls with getInt calls.
While this changes updates the storage type, it does not update all constant folding calls.
PiperOrigin-RevId: 221082788
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Value type abstraction for locations differ from others in that a Location can NOT be null. NOTE: dyn_cast returns an Optional<T>.
PiperOrigin-RevId: 220682078
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This CL implement exclusive upper bound behavior as per b/116854378.
A followup CL will update the semantics of the for loop.
PiperOrigin-RevId: 220448963
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FuncBuilder is useful to build a operation to replace an existing operation, so change the constructor to allow constructing it with an existing operation. Change FuncBuilder to contain (effectively) a tagged union of CFGFuncBuilder and MLFuncBuilder (as these should be cheap to copy and avoid allocating/deletion when created via a operation).
PiperOrigin-RevId: 219532952
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Introduce analysis to check memref accesses (in MLFunctions) for out of bound
ones. It works as follows:
$ mlir-opt -memref-bound-check test/Transforms/memref-bound-check.mlir
/tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1
%x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
^
/tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1
%x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
^
/tmp/single.mlir:10:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#2
%x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
^
/tmp/single.mlir:10:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#2
%x = load %A[%idxtensorflow/mlir#0, %idxtensorflow/mlir#1] : memref<9 x 9 x i32>
^
/tmp/single.mlir:12:12: error: 'load' op memref out of upper bound access along dimension tensorflow/mlir#1
%y = load %B[%idy] : memref<128 x i32>
^
/tmp/single.mlir:12:12: error: 'load' op memref out of lower bound access along dimension tensorflow/mlir#1
%y = load %B[%idy] : memref<128 x i32>
^
#map0 = (d0, d1) -> (d0, d1)
#map1 = (d0, d1) -> (d0 * 128 - d1)
mlfunc @test() {
%0 = alloc() : memref<9x9xi32>
%1 = alloc() : memref<128xi32>
for %i0 = -1 to 9 {
for %i1 = -1 to 9 {
%2 = affine_apply #map0(%i0, %i1)
%3 = load %0[%2tensorflow/mlir#0, %2tensorflow/mlir#1] : memref<9x9xi32>
%4 = affine_apply #map1(%i0, %i1)
%5 = load %1[%4] : memref<128xi32>
}
}
return
}
- Improves productivity while manually / semi-automatically developing MLIR for
testing / prototyping; also provides an indirect way to catch errors in
transformations.
- This pass is an easy way to test the underlying affine analysis
machinery including low level routines.
Some code (in getMemoryRegion()) borrowed from @andydavis cl/218263256.
While on this:
- create mlir/Analysis/Passes.h; move Pass.h up from mlir/Transforms/ to mlir/
- fix a bug in AffineAnalysis.cpp::toAffineExpr
TODO: extend to non-constant loop bounds (straightforward). Will transparently
work for all accesses once floordiv, mod, ceildiv are supported in the
AffineMap -> FlatAffineConstraints conversion.
PiperOrigin-RevId: 219397961
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This is done by changing Type to be a POD interface around an underlying pointer storage and adding in-class support for isa/dyn_cast/cast.
PiperOrigin-RevId: 219372163
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Operation*'s, simplifying some code in GreedyPatternRewriteDriver.cpp.
Also add print/dump methods on Operation.
PiperOrigin-RevId: 219045764
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1) We incorrectly reassociated non-reassociative operations like subi, causing
miscompilations.
2) When constant folding, we didn't add users of the new constant back to the
worklist for reprocessing, causing us to miss some cases (pointed out by
Uday).
The code for tensorflow/mlir#2 is gross, but I'll add the new APIs in a followup patch.
PiperOrigin-RevId: 218803984
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distinction. FunctionPasses can now choose to get called on all functions, or
have the driver split CFG/ML Functions up for them. NFC.
PiperOrigin-RevId: 218775885
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make operations provide a list of canonicalizations that can be applied to
them. This allows canonicalization to be general to any IR definition.
As part of this, sink PatternMatch.h/cpp down to the IR library to fix a
layering problem.
PiperOrigin-RevId: 218773981
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This is done by changing Attribute to be a POD interface around an underlying pointer storage and adding in-class support for isa/dyn_cast/cast.
PiperOrigin-RevId: 218764173
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just having the pattern matcher in its own library. At this point,
lib/Transforms/*.cpp are all actually passes themselves (and will probably
eventually be themselves move to a new subdirectory as we accrete more).
PiperOrigin-RevId: 218745193
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