WIP fuse elemwise+careduce#2200
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The fused loop writes the elementwise result to the write buffer, never to the inplaced input, but the inner fgraph kept the inplace Elemwise: the Python-mode fallback (OpFromGraph.perform) would destroy that input without the outer destroy map declaring it, losing the ordering constraint for other readers of the destroyed buffer. The JIT path was unaffected (write buffers shadow the inplace pattern in make_outputs). Write-and-direct duplication now runs before the strip and preserves the inplace pattern, so an inplace on an output that stays materialized (the write consuming a duplicate) still survives the fusion.
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An output consumed by several eligible CAReduces previously disqualified itself entirely (the detection required exactly one reduce client). Peel one extra reduction per rewrite pass onto a duplicate output until each reduction has its own copy, so e.g. [sum(f), max(f), prod(f), f] becomes a single FusedElemwise with three fused reductions.
sum(x[idx]) had no Elemwise for FuseElemwise to anchor on, so the gather materialized and the reduction stayed external. A new pre-rewrite wraps such reductions in an identity Elemwise (covering the bare AdvancedSubtensor1, axis-swap DimShuffle and flattened-ND-index Reshape forms), letting gather, identity and reduction collapse into one fused loop.
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