Add propagation of thread dependent index sequences #292
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Signed-off-by: Harsh Menon <[email protected]>
raikonenfnu
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Nov 26, 2024
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| if dst_op: | ||
| for node in propagated_resolutions: | ||
| get_custom(node).index = dst_op.index |
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When would we use it without dst_op?
raikonenfnu
reviewed
Nov 26, 2024
| thread_dependent_index: dict[IndexSymbol, IndexSequence], | ||
| ) -> dict[IndexSymbol, IndexSequence]: | ||
| combined_index = {k: v for k, v in thread_independent_index.items()} | ||
| for k in combined_index: |
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Would be nice to add some docs, to different examples/cases on when we'd add the start offsets. (perhaps read -> read or offseted_read + mma?)
raikonenfnu
reviewed
Nov 26, 2024
| vector_shapes = ( | ||
| custom.vector_shapes if custom.vector_shapes else source_vector_shapes | ||
| ) | ||
| sources.append((custom, source_index, vector_shapes)) |
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why not use source.index? Seems like the only time sourc.index != source_index is when source.index has underlying indices before getting propagated. But wouldn't we want that?
raikonenfnu
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Nov 26, 2024
Hardcode84
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Nov 26, 2024
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This PR adds a major refactor of the index sequence analysis. Specifically,