MAINT: simplify torch dtype promotion

[crusaderky]

Salvaged from data-apis/array-api#298

• Simplify dtype promotion table
• Change sum(x, axis=(), dtype=x.dtype) and prod with the same parameters, which were previously returning x itself, to return a deep copy instead. While this is not part of the Array API, it's what both numpy an base torch do, and probably the most healthy thing to do xref https://data-apis.org/array-api/latest/design_topics/copies_views_and_mutation.html.
  Discussion here: Spell out where views are allowed #331

[Copilot]

Copilot reviewed 1 out of 1 changed files in this pull request and generated no comments.

Comments suppressed due to low confidence (2)

array_api_compat/torch/_aliases.py:140

• The try/except block in _result_type silently swallows a KeyError when a dtype pair is not found in the promotion table. Consider handling the error explicitly or adding a clarifying comment to document the intended fallback behavior.

return _promotion_table[xdt, ydt]

array_api_compat/torch/_aliases.py:296

• Consider adding tests for _sum_prod_no_axis to verify that the dtype conversion and deep copy behavior work as expected, especially for edge cases involving small integer types like uint8.

return x.clone() if dtype == x.dtype else x.to(dtype)

[crusaderky]

(complex, float) use cases were missing

[ev-br]

LGTM, thanks @crusaderky

[ev-br]

Note to self: this looks scary, but is in fact just a refactoring. Previously this stanza was duplicated in sum and prod.

Returning a copy looks reasonable, too.