Wheest commented on pull request #7142:
URL: https://github.com/apache/tvm/pull/7142#issuecomment-749822386


   Thanks, I understand better what a good test for this PR would be: one that 
fails on the current `main` branch but not this PR.
   
   I've been working on devising a test like this, but haven't got one that 
fails yet.  Will keep working on it, but here's my reasoning so far:
   
   afaik the workload data is only used the creation of fallback schedules.  
e.g. [for creating the `"tile_ow"` parameter for spatial pack 
convolution](https://github.com/apache/tvm/blob/main/python/tvm/topi/x86/conv2d_avx_common.py#L54).
    
   So I imagine I would want to create a test that has padding such that 
something like `"tile_ow"` is generated with an incorrect value, creating a 
schedule that causes an invalid transformation.
   
   e.g. `verify_conv2d_nchw(1, 64, 8, 128, 3, 1, (6, 6, 0, 0))`
   
   If we are to focus on NCHWc convolution, which uses `"tile_ow"` in its 
schedule (via SplitEntity with `reg` in the `_fallback_schedule`) 
[`python/tvm/topi/x86/conv2d_avx_common.py#L119`](https://github.com/apache/tvm/blob/main/python/tvm/topi/x86/conv2d_avx_common.py#L119).
   There is no value we can set `reg` or `"tile_ow"` to that will cause an 
invalid transformation, even through silly hardcoding like `out_width = 10000` 
or `ow_chunk, ow_block = s[C].split(ow, factor=10000)`
   
   It always works.  Though perhaps it suffers a performance regression? 
   
   It could be happenstance that none of the conv2d schedules make 
transformations that are rendered invalid by having an incorrect value for the 
output height/width.  That being the case, I'm unsure how I would devise a test 
for this.


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