feat[dace][next]: Deterministic gt_split_access_nodes()
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Performance seems to be okay: 
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edopao
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Jan 15, 2026
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edopao
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edopao
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LGTM, only some minor comments/questions.
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| # Since the transformation only applies to single use data, the order in which the | ||
| # states are processed is irrelevant. Furthermore, the fragments generated through |
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"Furthermore, the fragments generated..." I don't see how this is relevant. Are you considering the case in which gt_split_access_nodes() is called multiple times?
| # NOTE: Turning them into a string is the best solution is probably the only way | ||
| # to achieve some stability. The only downside is that the order now depends | ||
| # on the specialization level that is used, i.e. to we have numbers or symbols. | ||
| split_description = sorted(split_description, key=lambda split: str(split)) |
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split_description is a Sequence, so it is already sorted. As alternative, we could ensure the deterministic order in the place where the sequence is created.
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| # Bring the split description in a deterministic order. | ||
| # NOTE: See note in `split_node()` why the sorting is done in this way. | ||
| # NOTE: The main benefit of bringing `split_description` into a deterministic | ||
| # order is that the output of this function is deterministic as well. I am | ||
| # not sure if there is any benefit beside that. | ||
| split_description = sorted(split_description, key=lambda split: str(split)) |
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| # Allocate the return `dict` the order is important, first the reordered split | ||
| # description followed by the `None` key. |
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Can you also explain why it is important?
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Makes
gt_split_access_nodes()deterministic by processing it in the order ofAccessNodes.However, this means that the name of the data must be predictable and stable.
ToDo
gt_auto_optimization()gt_split_access_nodes(). C2SM/icon4py#937