areusch commented on a change in pull request #9385:
URL: https://github.com/apache/tvm/pull/9385#discussion_r746170648
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File path: python/tvm/target/target.py
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@@ -642,6 +642,27 @@ def create_tvm_options(cpu_ver, config): # pylint:
disable=unused-argument
return Target(" ".join(["hexagon"] + args_list))
+STM32_SUPPORTED_MODELS = {
+ #"stm32H7xx": ["-device=arm_cpu", "-mcpu=cortex-m7", "-march=armv7e-m"],
+ "stm32H7xx": ["-device=arm_cpu", "-mcpu=cortex-m7"],
Review comment:
> We first aligned with the CubeAI libraries that have a library per
series.
Do these libraries contain implemented kernels? (e.g. do you intend to
integrate them similarly to CMSIS-NN?)
if we move to one board id per target string, won't there be quite a lot of
repetition? possible to compress the table somehow (e.g. just look at the board
id prefix)? at least, perhaps we could start with something like that? in
general we'd like to avoid manual per-board configuration in TVM if possible
(but I'm asking the question above in case we need to consider that).
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