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Subject [GitHub] [incubator-tvm] icemelon9 commented on issue #4972: Performance regression of quantization on CUDA after [Relay][AutoTVM] Relay op strategy (#4644)
Date Mon, 02 Mar 2020 18:23:39 GMT
icemelon9 commented on issue #4972: Performance regression of quantization on CUDA after [Relay][AutoTVM]
Relay op strategy (#4644) 
URL: https://github.com/apache/incubator-tvm/issues/4972#issuecomment-593545631
 
 
   I guess the performance regression could be due to https://github.com/apache/incubator-tvm/blob/master/python/tvm/relay/op/strategy/cuda.py#L88.
Previously TVM might use `conv2d_NCHWc_int8` by default. However `conv2d_NCHWc_int8` is not
enabled now when layout is "NCHW" because its output shape is 5-dim and could be lead to wrong
shape if using opt_level=2 as `alter_op_layout` pass wouldn't be enabled. We need to fix it
by following x86 `conv2d_NCHWc`. 
   
   I don't have any idea what causes the accuracy problem. Could you share more about what
happens in the `quantize` function in your script?

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