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Benchmark scripts for TVM
Models I added in #5 were downloadable at least for a few days, but the link is no longer valid, apparently due to the github storage limit (same issue as https://stackoverflow.com/questions/58219778/how-to-get-a-direct-link-to-a-file-in-github-lfs-large-file-storage).
What is an alternative location to store large models?
Hi,
I was trying to reproduce the performance results on g4dn.4xlarge instance but got the following error:
~/TLCBench$ python3 benchmark_autoscheduler.py --network bert --target "cuda -model=t4" --logdir saved_logs/latest
Benchmark bert-B1-float32 ...
python3: /tmp/build/80754af9/llvmdev_1560805331146/work/lib/ExecutionEngine/MCJIT/MCJIT.cpp:204: virtual void llvm::MCJIT::generateCodeForModule(llvm::Module*): Assertion `M->getDataLayout() == getDataLayout() && "DataLayout Mismatch"' failed.
Aborted (core dumped)
My speculation is that the issue might be caused by LLVM version incompatibility. Would you mind sharing the LLVM version that you are using? I have been using LLVM Ver. 10.
Currently, TVM lacks an up-to-date and reproducible benchmark. The only benchmark is hosted at tvm/apps/benchmark. However, this benchmark is too old and has several flaws.
This repo aims at building a new open, reproducible bechmark for TVM. When the repo is ready, we can run evaluation nightly and run auto-tuning weekly or monthly.
As the first step, we target three models, three hardware platforms and four code generation strategies.
To make the comparision with other frameworks easier, we choose ONNX as the input model format.
All logs generated during the auto-tuning should be uploaded for future references.
reference: the old autotvm benchmark
reference: https://github.com/microsoft/onnxruntime
reference: https://tvm.apache.org/docs/tutorials/frontend/using_external_lib.html
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