Thank you for this proposal! This work does make scheduling much easier. I have a concern about using this way to write a tensor expression. It looks like more complicated than tvm.compute when defining matmul. We need to define some buffers and creating block with corresponding shape dimension. It would be helpful if you can add a conv2d example which can replace existing topi.nn.conv2d definition to better understand what developer would need to write.
Another question is about representing generic programming style ops such as shape functions. Since these programs don't fit into tvm scheduling, I assume it would still be more convenient to use existing te hybrid script to create these ops? --- [Visit Topic](https://discuss.tvm.apache.org/t/rfc-tensorir-a-schedulable-ir-for-tvm/7872/9) 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/368fa3a2cf5e4531886a799e6f4ed9355e153e65b0c9853c9a0d477a7b7dbe8e).
