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Posted to discuss-archive@tvm.apache.org by sqchao via Apache TVM Discuss <no...@discuss.tvm.ai> on 2020/11/03 11:25:51 UTC
[Apache TVM Discuss] [Questions] After auto tuning， what other optimizations based on tir will be done?
I am a newer to TVM, from my point, compute + schedule + auto tuning convert the relay IR to Tensor IR.
this process includes many hardware special optimizations related with schedule primitives. After the auto tuning, Tensor IR was generated.
Q1: Besides the AutoTVM(include schedules), what are the optimizations based on TIR？These optimizations are the operations in /tir/transform files?
I did not find any related knowledge about optimizations based on tir in **tvm paper**
Q2: whether relay.build() execute the related call below？
If there are any mistakes, please help me correct it.
Thanks in advance！
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[Apache TVM Discuss] [Questions] 【TIR】After auto tuning， what other optimizations based on tir will be done?
Posted by Matt Barrett via Apache TVM Discuss <no...@discuss.tvm.ai>.
I'm no expert with this, but if you take a look in build_module.py, you can see what TIR passes are run after the schedules have been lowered. I'll paste them here for convenience:
```
tvm.tir.transform.InjectPrefetch(),
tvm.tir.transform.StorageFlatten(64, instrument_bound_checkers),
tvm.tir.transform.BF16Legalize(),
tvm.tir.transform.NarrowDataType(32),
tvm.tir.transform.Simplify(),
tvm.tir.transform.LoopPartition(),
tvm.tir.transform.VectorizeLoop(not disable_vectorize),
tvm.tir.transform.InjectVirtualThread(),
tvm.tir.transform.InjectDoubleBuffer(),
tvm.tir.transform.StorageRewrite(),
tvm.tir.transform.UnrollLoop(),
tvm.tir.transform.Simplify(),
tvm.tir.transform.RemoveNoOp(),
tvm.tir.transform.RewriteUnsafeSelect(),
tvm.tir.transform.HoistIfThenElse()
```
I'm only familiar with a few of these, but sometimes to get a better understanding I'll just print the module between passes and see what changed.
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[Apache TVM Discuss] [Questions] 【TIR】After auto tuning， what other optimizations based on tir will be done?
Posted by "Cody H. Yu via Apache TVM Discuss" <no...@discuss.tvm.ai>.
What @matt-arm pointed out is correct. In addition, your figure is not exactly correct. relay.build actually goes the same flow as AutoTVM/TE schedule. When calling relay.build, it lowers each operator to TE according to Relay op strategy. The op strategy will select a TE compute/schedule for each Relay op based on certain rules. For example, if you provide the tuning logs like:
```
with ApplyHistoryBest('tune.log'):
relay.build(mod, target)
```
Then the op strategy will be based on the tuning results. On the other hand, it selects schedules based on the default priority order.
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