[Apache TVM Discuss] [Questions] Repeatable build/compile

Yes, different autoTVM/autoscheduler runs on the same network can yield different implementations. If you know your model doesnt change, you would autoschedule once and save the log files of the optimized implementation. If for some reason you need to recompile your model you would tell TVM t

[Apache TVM Discuss] [Questions] How to add my custom Relay node to pattern matcher? [EthosU example]

@manupa-arm @matt-arm So maybe I can ask more directly. Is the ordering of first pattern matching your offloadable and then replacing, within the extracted composite, the native relay operators with your new ethosu.conv2d relay operator a solution to not being able to do what I said before

[Apache TVM Discuss] [Questions] How to add my custom Relay node to pattern matcher? [EthosU example]

Hello, I was looking at the Arm EthosU integration in TVM and [noticed that there was a new conv2d Relay operator defined](https://github.com/apache/tvm/blob/main/python/tvm/relay/backend/contrib/ethosu/op/convolution.py#L185). Obviously this operator is only legal/valid for offloading onto t

[Apache TVM Discuss] [Questions] Ops become slow when using te.var

Just inline the one stage into the other one? EDIT: wait your if statements require variables which are not defined (blockIdx.x andThreadIdx.x) --- [Visit Topic](https://discuss.tvm.apache.org/t/ops-become-slow-when-using-te-var/11486/4) to respond. You are receiving this because you en

[Apache TVM Discuss] [Questions] Ops become slow when using te.var

I guess what you are seeing are potential cases when the variable can have any value in the range of the data type you selected and therefore for correctness all those if statements are necessary? Any reason you want to use te.var ? I am guessing due to some dynamic shape you want to support,

[Apache TVM Discuss] [Questions] Hi, does anyone know the difference between @reg.register_strategy and reg.register_compute?

Hey, Take this with a grain of salt since I am not an official voice of the people who developed those things. The `compute` should be to register the naive/non-optimize/non-hwdependent computation rule of a Relay operator. You can think about it as a golden reference. Now, there can be man

[Apache TVM Discuss] [Questions] Passing a tuple to a packed func?

Thanks for your response, but I still dont understand what the solution is... except for decomposing the tuple into elementary arguments. --- [Visit Topic](https://discuss.tvm.apache.org/t/passing-a-tuple-to-a-packed-func/9117/3) to respond. You are receiving this because you enabled mai

[Apache TVM Discuss] [Questions] Tiled tensors for external (python) functions and TIR == te.extern?

@eric-haibin-lin @ziheng any thoughts? I saw you were involved in [PR6079](https://github.com/apache/tvm/pull/6079) which seems to have been the last modifications to `te.extern` --- [Visit Topic](https://discuss.tvm.apache.org/t/tiled-tensors-for-external-python-functions-and-tir-te-ext

[Apache TVM Discuss] [Questions] Passing a tuple to a packed func?

Hello everyone, I was wondering if there is a way to pass a tuple (or array) directly to a packed func. ``` tpl = tuple(1,2,3) tvm.tir.call_packed("func_name", tpl) ``` Reading the [packed_func documentation](https://tvm.apache.org/docs/dev/runtime.html?highlight=packed_func#packedfunc), I

[Apache TVM Discuss] [Questions] How to match the pattern of a function in Relay?

I also +1 this feature. It seems that what you want to do is very similar to a previous post I had https://discuss.tvm.apache.org/t/relay-pattern-replacing-with-custom-relay-ops/7531/13 The biggest fear I have of introducing a new Relay operator (which I guess is what would eventually happen

[Apache TVM Discuss] [Questions] [PassInfra] Relay Function Pass

Hello, In the [PassInfra Design and Development Doc](https://tvm.apache.org/docs/dev/pass_infra.html#pass-objects) the `function_pass` decorator is briefly explained. In the python codebase, there is also the `class FunctionPass`, objects of this type should be created with `function_pass`. I