Either is fine. You can try the fix if you apply the latest commit of the
repo. If you are not sure how to do it, cloning the whole repo may be easier
way to go.
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@kazum I have to git the whole repo and build?
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CC @MarisaKirisame if you are interested
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Can anyone help explain the tiling reduction axes part in the [Tuning High
Performance Convolution on NVIDIA
GPUs](https://docs.tvm.ai/tutorials/autotvm/tune_conv2d_cuda.html#tuning-high-performance-convolution-on-nvidia-gpus)?
The code of this part is:
```
# tile reduction axes
n, f, y, x
Got it. Thanks for the quick reply!
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Hi. Thinking that better later than never, I'd like to share the link to the
project I worked on a year ago. It is a Haskell binding to TVM IR. It worked at
the moment of its last update (a year ago).
https://github.com/grwlf/htvm
Currently, I have no plans of maintaining it.
The project con
I think the command `python` is aliased to Python 2.7. What happens if you do
`which python`? This should give you the alias of the `python` command. For
instance, in my case is `/usr/bin/python`. Then you can write `ls -al
/usr/bin/python` to see where the symbolic link points to.
A simple
By the codes it says, these are the opt_levels here some of the levels are
understandable like SimplifyInference,OpFusion,FoldConstant rest there are no
documentation about these.
any one can refer these
OPT_PASS_LEVEL = {
"SimplifyInference": 0,
"
some thing like this
%while_loop(0, 0, %255, %256, %259, %lstm_1/strided_slice_5/_25__cf__25,
%lstm_1/strided_slice_10/_20__cf__20, %lstm_1/strided_slice_4/_24__cf__24,
%lstm_1/strided_slice_3/_23__cf__23, %258, %lstm_1/strided_slice_1/_19__cf__19,
%264, %lstm_1/strided_slice_2/_22__cf__22,
