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Currently, we override the standard numpy type resolver, because, as seen in this extract:
Lines 535 to 545 in e33ee55
| * We provide our own type resolver, since the default one, | |
| * PyUFunc_DefaultTypeResolver from | |
| * numpy/core/src/umath/ufunc_type_resolution.c, has problems: | |
| * 1. It only looks for userloops if any of the operands have a user | |
| * type, which does not work if the inputs are normal and no explicit | |
| * output is given (see https://github.com/numpy/numpy/issues/11109). | |
| * 2. It only allows "safe" casting of inputs, which annoyingly prevents | |
| * passing in a python int for int32 input. | |
| * The resolver below solves both, and speeds up the process by | |
| * explicitly assuming that a ufunc has only one function built in, | |
| * either a regular one or a userloop (for structured dtype). |
However, as noted in numpy/numpy#11109 (comment), things should now work for us. So, this is a reminder to try removing our work-around.
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