[GitHub] [tvm] monklof commented on a change in pull request #7496: [Frontend,TOPI] Improve dynamism for BatchMatmul and Dense

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monklof commented on a change in pull request #7496:
URL: https://github.com/apache/tvm/pull/7496#discussion_r586076343



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File path: python/tvm/topi/nn/batch_matmul.py
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@@ -61,9 +62,17 @@ def batch_matmul(x, y, oshape=None, auto_scheduler_rewritten_layout=""):
     _, M, K = x.shape
     k = te.reduce_axis((0, K), name="k")
     if oshape is None:
-        assert XB == YB or XB == 1 or YB == 1, "batch dimension doesn't match"
-        assert x_shape[2] == y_shape[2], "shapes of x and y is inconsistent"
-        batch = te.max(XB, YB)
+        if isinstance(XB, int) and isinstance(YB, int):
+            assert XB == YB or XB == 1 or YB == 1, "batch dimension doesn't match"
+            batch = max(XB, YB)
+        elif isinstance(XB, tir.expr.Var):
+            batch = XB
+        else:
+            batch = YB

Review comment:
       I agree that my implementation here is incomplete, the basic principle is: one of XB and YB should be 1, and we choose the another as `batch`,
   
   But it is a little complicated here since XB/YB can be unknown at compile time:
   1. if XB and YB are both `int`, one of them should be 1, and we choose the bigger one as `batch` at compile time.
   2. if either or both them are `Var`, we actually should choose `batch` and do validation at runtime, may be we should use `TIR`'s `IfThenElse` and `AssertStmt` to complete the logic here.
   
   In my case, one of them is `var` and another is `1`, so I coded as above.
   
   Thanks for reminding, maybe we should implement it as strict as possible?




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