tqchen commented on code in PR #20032:
URL: https://github.com/apache/tvm/pull/20032#discussion_r3610570245
##########
tests/python/relax/test_expr.py:
##########
@@ -243,11 +243,16 @@ def test_func():
seqe = rx.SeqExpr(blocks, x)
ret_ty = R.Tensor(dtype="float32", ndim=-1)
func = rx.Function([x], seqe, ret_ty)
- func = func.with_attr("global_symbol", "func")
- assert func.params[0] == x
- assert func.body == seqe
- assert func.ret_ty == ret_ty
- assert func.attrs["global_symbol"] == "func"
+ with_attr = func.with_attr("global_symbol", "func")
+ with_attrs = func.with_attr({"global_symbol": "func", "num_input": 1})
+
+ assert "global_symbol" not in func.attrs
Review Comment:
Thanks for checking this. For this concrete `relax.Function`, both
`Function.__init__` and `Function.create_empty` explicitly normalize
`attrs=None` to `tvm.ir.DictAttrs({})`. On the exact PR build, the new function
reports `func.attrs == {}` and `func.attrs is None == False`; after
`with_attr`, the original still reports `{}` and the result contains
`global_symbol`. The committed focused test also passes as written, while
`assert func.attrs is None` fails. I am therefore keeping the membership
assertion because it verifies that the original defined attribute map remains
unmodified.
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