compiler: Enable blocking-before-CIRE#2948
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| else: | ||
| self.umt_reduce = UnboundTuple(*par_tile.default, 1) | ||
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| def next(self, prefix, d, clusters): |
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significant reduction in complexity
| assert iters[0].step == par_tile[1] | ||
| assert iters[1].step == par_tile[0] | ||
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| def test_custom_rule0(self): |
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unused feature, dropped; so dropping the tests too
Codecov Report❌ Patch coverage is Additional details and impacted files@@ Coverage Diff @@
## main #2948 +/- ##
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Coverage 83.60% 83.61%
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Files 250 250
Lines 52908 53053 +145
Branches 4564 4574 +10
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+ Hits 44235 44358 +123
- Misses 7895 7914 +19
- Partials 778 781 +3
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| """Return the DataSpace of this ClusterGroup.""" | ||
| return DataSpace.union(*[i.dspace.reset() for i in self]) | ||
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| @property |
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| # Overrides the default values in the main Operator class | ||
| BLOCK_LEVELS = 0 | ||
| CIRE_BLOCK_TEMPS = False |
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Is it intended to be a default or enforced?
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enforced or things would break
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then it needs to be moved to line 81 below and prevent it from being a user option (i.e no oo.pop)
| if not mapper: | ||
| return self | ||
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| if self.halo_scheme: |
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Can probably be relaxed to self.halo_scheme.distributed_aindices & mapper.keys()
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this is a false problem anyway. The halo_scheme attribute only gets populated at stree-construction time, so none of the compiler passes across the entire Cluster layer will ever have to worry about this
| # Handle ComponentAccesses | ||
| subs = {i: Symbol(f'dummy{n}') for n, i in enumerate(compaccs)} | ||
| exprs1 = uxreplace(exprs, subs) | ||
| terms1 = retrieve_terminals(exprs1, **kwargs) |
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would likely be "cheaper" to have an ignore=compaccs in retrieve_terminals
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FabioLuporini
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| def promote(self, subs): | ||
| m = self | ||
| for d, v in subs.items(): | ||
| guards = {self.get(i) for i in d._defines} - {true} |
| interval = imapper[d] | ||
| except KeyError: | ||
| if i.dim in a.free_symbols: | ||
| if d in a.free_symbols: |
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a.has(d) is likely slightly faster
| # Given the iteration `interval`, lower distances to indices | ||
| for distance, indices in zip(a.distances, indicess, strict=True): | ||
| v = distance[interval.dim] or 0 | ||
| v = distance[i.dim] or 0 |
2 participants
This is key for features in PRO
In doing so, several utility functions are added, which might come in handy in the future as well
Some clean up also, which is never a bad thing