tqchen opened a new issue #8579:
URL: https://github.com/apache/tvm/issues/8579


   Looking at the test time log, 
https://ci.tlcpack.ai/job/tvm/job/main/1356/testReport/ctypes.tests.python.relay/test_op_grad_level2/
   
   conv2d grad takes a long time to finish(1h). This is likely due to our 
numerical gradient checker trying to do numerical gradient for all directions 
which scales linearly to the number of entries. 
   
   Possible resolutions:
   - K0: Use memoization to cache the numerical gradient needs.
   - K1: run a different kind of test that randomizes the direction and check 
consistency, see page 8 of this 
[slide](https://catalyst.cs.cmu.edu/15-884-mlsys-sp21/slides/2-MLSys-AutomaticDifferentiation.pdf)
   
   I would suggest we go with K1 and have an option in check numercial gradient 
to do so.
   
   
   


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