I think that's because of the function TransformShape in the file
data_layout.cc. It's used to split shape like from NCHW to NCHWc. But when you
want to convert your output shape from NCHW to NHWC for example, it will cause
error. So you need to add your own shape transform function.
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hallo! so, how can i to do it ?
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Hi:
Is is possible to auto tune a single TOPI operator? (e.g. conv2d_int8)
Do we have tutorial for this?
Thank you very much!
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@matt-arm the PR you posted solved the issue of tuple constant propagation, but
it seems not solving the tuple var node issue. In this particular case, for
example, we will still have a tuple of data in the first argument.
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I have a candidate fix with this PR:
https://github.com/apache/incubator-tvm/pull/5476
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My wechat is 17671689743.
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wow,thank you!can i add your friends?
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I think it is the correct way to handle it. This is the same as the doc:
https://docs.tvm.ai/tutorials/dev/low_level_custom_pass.html
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You can git clone from https://github.com/uwsampl/tvm-distro and mv tophub/ to
~/.tvm/tophub.
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Hi @FrozenGene, Could you please help in sharing your thoughts on this approach?
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Hi, welcome to the forum :) I'm working on fixing this exact issue at the
moment. It comes about because constant tuples are not correctly propagated
into the partitioned regions so you can't see the data of the tuple, only its
type. I hope to have a fix in review either later today or tomorro
Hello!
I have some questions about arm core ( rk3399 firefly board ).
I want to run Mali GPU and Arm CPU In parallel.
Therefore, after creating two threads, I want to execute a module running on
CPU and GPU in each thread.
and I want to use two big cores for the threads running the CPU, and a
it's really helpful. thanks.
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I'm stumbled by the same confusion when tracing the FoldConstant optimization
pass. Some of my debug print shows the process as below.
I don't know why (**anyone, please explain if you know**) but Relay kicks the
'whole compilation process' by using the Interpreter (interpreter.cc).
* 'EtaEx
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