Use template instead of duplicating code in elementwise_util.h#9058
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Use template instead of duplicating code in elementwise_util.h#9058
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This was referenced Mar 11, 2025
| ctx, | ||
| (internal::check_tensor_dtype(a, a_dtypes, compute_type) && | ||
| internal::check_tensor_dtype(out, out_dtypes, compute_type)), | ||
| (check_input_dtype(inputs, compute_type) && ...) && |
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TIL fold expressions in cpp
JacobSzwejbka
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Mar 11, 2025
This was referenced Mar 17, 2025
kedarnath03
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Jun 25, 2025
Now all the apply functions share a common implementation, which means further changes (e.g., parallel_for, generating specialized dtypes for the case where all inputs have the same type) don't need to be repeated 3 times. (Interestingly, this seems to increase the effectiveness of the following parallelization change. Not entirely sure why, but I checked the generated code for optimized op_where and it seems to have improved, which is surprising.) ghstack-source-id: 9344bf6 ghstack-comment-id: 2707405611 Pull Request resolved: pytorch/executorch#9058
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Now all the apply functions share a common implementation, which means further changes (e.g., parallel_for, generating specialized dtypes for the case where all inputs have the same type) don't need to be repeated 3 times.
(Interestingly, this seems to increase the effectiveness of the following parallelization change. Not entirely sure why, but I checked the generated code for optimized op_where and it seems to have improved, which is surprising.)