Update debug_to_file API to remove type_code #8183
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The .npy format is NumPy's native format for storing multidimensional arrays (aka tensors/buffers). Being able to load/save in this format makes it (potentially) a lot easier to interchange data with the Python ecosystem, as well as providing a file format that support floating-point data more robustly than any of the others that we current support. This adds load/save support for a useful subset: - We support the int/uint/float types common in Halide (except for f16/bf16 for now) - We don't support reading or writing files that are in `fortran_order` - We don't support any object/struct/etc files, only numeric primitives - We only support loading files that are in the host's endianness (typically little-endian) Note that at present this doesn't support f16 / bf16 formats, but that could likely be added with minimal difficulty. The tricky bit of this is that the reading code has to parse a (limited) Python dict in text form. Please review that part carefully. TODO: we could probably add this as an option for `debug_to_file()` without too much pain in a followup PR.
Built on top of #8175, this adds .npy as an option. This is actually pretty great because it's easy to do something like ``` ss = numpy.load("my_file.npy") print(ss) ``` in Python and get nicely-formatted output, which can sometimes be a lot easier for debugging that inserting lots of print() statements (see #8176) Did a drive-by change to the correctness test to use this format instead of .mat.
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PTAL |
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Finally clean, PTAL |
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Monday Morning Review Ping |
abadams
approved these changes
Apr 29, 2024
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