Posted PR - https://github.com/apache/incubator-tvm/pull/5204
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@jroesch, is there any update on this feature? I'm really excited to try it out
:)
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I tried this approch and able to run the code, but this gives rise to different
error, where my model is having output.shape of (1,4) now if the check the
model after importing random_uniform it changes my model output to shape of
(1,15.512). Not sure where its changing the graph output
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Let us open the discussion open for a bit, if we agree that it is a good idea,
we can carry it out during a weekend(when there is less on-going PRs).
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There was a related issue https://github.com/apache/incubator-tvm/issues/1732
that resulted in the introduction of .clang-format file. But we didn't do
anything else to improve consistency of existing code or enforce the style for
future code.
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There is something wrong with my code. for example, When 'RandomUniform' is in
a loop, the shape keeps changing. If your shape of 'RandomUniform' doesn't
changeļ¼ you can print shape or inputs[0] on _random_uniform.
If there is any discovery, welcome timely feedback.
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To be clear, we are enforcing the Google C style via cpplint. Although the
cpplint checks seems to be weaker than the clang-format
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Thanks @tqchen for comments.
To elaborate more here, the support for Relay to ONNX serialization will help
us to take advantage of hardware-specific optimizations supported by different
compilers. The ONNX format is mostly adopted. If a particular compiler supports
a specific format, support f
