Now，I woulde like to use te.extern to add an extern op level library ，like
cuDNN. For complex ops, like conv2d or dense , we can add new dispatch rules
in op strategy,like @softmax_strategy.register(["cuda", "gpu"]), and then
redefine the compute with te.extern. But for some injective or broadc
Hi @xqdan, when you say "not in MindSpore for now", do you mean AKG is still a
standalone codegen toolkit? Or it currently has already been integrated into
your internal TensorFlow/PyTorch versions?
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Is there any details about the TVM + MKLDNN BERT integration work?
I would like to take a look to see its potential connection with Ansor.
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The proposal looks good. notably, the config will need to evolve as we migrate
to ansor, so perhaps we could try to keep it opaque, or find a way to upgrade
later.
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I've thought about this some more, and I'm changing my stance with respect to
ProtoBuf. While adding a Python class schema is a less invasive change than
introducing ProtoBuf and allows us to stick to the current log format exactly,
protos do have the added benefit of being language-neutral. A
We don't have vim plugin for FFI navigator now, but you are welcome to
contribute one :slight_smile:
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Is there some guide for vim ?
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@tobegit3hub thanks for this great work. I am trying to export an autotuned
model with TVMDSOOp. Now, I am stuck at how to register the func_name to the
tf_op.
```
with tvm.transform.PassContext(opt_level=3):
graph, lib, params = relay.build_module.build(
mod, target=target, params=
