[GitHub] [tvm] Lunderberg commented on issue #12907: [Bug] Metaschedule ThreadedTraceApply::Apply failed with error ScheduleError: An error occurred in the schedule primitive 'parallel'

[GitBox <gi...@apache.org>]

Lunderberg commented on issue #12907:
URL: https://github.com/apache/tvm/issues/12907#issuecomment-1262311429

   This looks like it might be a good case for `T.assume`.  If I make an init block that assumes the `C` has already been zeroed out, then the `meta_schedule.tune_tir` call passes successfully.
   
   ```python
   @T.prim_func
   def matmul(
       A: T.Buffer[(512, 512), "float32"],
       B: T.Buffer[(512, 512), "float32"],
       C: T.Buffer[(512, 512), "float32"],
   ) -> None:
       for i in range(512):
           for j in range(512):
               for k in range(512):
                   with T.block("update"):
                       with T.init():
                           T.assume(C[i, j] == 0.0)
                       C[i, j] = C[i, j] + A[i, k] * B[j, k]
   ```


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