Thanks for the reply @comaniac.
I don't need these _exact_ tensors, just to recreate them from the available properties (e.g. their shapes, expressions of how they are generated). I'm wondering if it's possible to recreate them from scratch at the Relay level, just by reading the properties at the TE level. E.g. for the placeholder tensors I store in `my_vars`, I make them from scratch, only copying the shape property from the lowered TE tensors to make new tensors at the Relay level. Tthe final tensor, which is not a placeholder, is made from the expression `T_dense[ax0, ax1] + placeholder[ax1]`. I am not looking to convert `tensors[-1].op` to an `tvm.relay.Expr`. Instead, I am wondering if I can define a fresh expression that takes this information (e.g. the `body`, `axis`, etc) to make a new `tvm.relay.Expr`. --- [Visit Topic](https://discuss.tvm.apache.org/t/create-a-relay-expr-from-a-auto-scheduler-searchtask/10795/3) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/6c6224cb00ab02cb157bf7a94d949d90155ffc7ebf8eec93e476e856910830b7).
