[TVM Discuss] [Questions] Quick start tutorial gives " Cannot find config for target=cuda -model=unknown, workload=('conv2d_nchw.cuda'"

Thank you so much, for your immediate input. Let me try tuning in my local machine. --- [Visit Topic](https://discuss.tvm.ai/t/quick-start-tutorial-gives-cannot-find-config-for-target-cuda-model-unknown-workload-conv2d-nchw-cuda/5874/5) to respond. You are receiving this because you enab

[TVM Discuss] [Questions] TVM/VTA questions & use computer as SoC?

This thread proposes some changes: there is an upcoming PR in the works: https://discuss.tvm.ai/t/rfc-vta-support-for-cloud-devices-opencl-compatible/6676/22 --- [Visit Topic](https://discuss.tvm.ai/t/tvm-vta-questions-use-computer-as-soc/3267/5) to respond. You are receiving this becaus

[TVM Discuss] [Questions] TVM/VTA questions & use computer as SoC?

Hi @faku Any updates on support fr PCI-e based FPGAs? --- [Visit Topic](https://discuss.tvm.ai/t/tvm-vta-questions-use-computer-as-soc/3267/4) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.ai

[TVM Discuss] [Questions] Install error TVM on Windows

No, I just copied flies in a zip folder. I restart with `git --recursive` it worked. Thanks a lot --- [Visit Topic](https://discuss.tvm.ai/t/install-error-tvm-on-windows/6938/3) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [

[TVM Discuss] [Questions] Tvm.contrib.graph_runtime.create error

If you are using Python, another possible solution is to use C++. In my experience, model deployment using C++ is more memory efficient. --- [Visit Topic](https://discuss.tvm.ai/t/tvm-contrib-graph-runtime-create-error/6868/7) to respond. You are receiving this because you enabled mailin

[TVM Discuss] [Questions] Install error TVM on Windows

Did you use `git --recursive` when you clone the project? --- [Visit Topic](https://discuss.tvm.ai/t/install-error-tvm-on-windows/6938/2) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.ai/email/

[TVM Discuss] [Questions] Install error TVM on Windows

HI all ! I’m trying to install tvm on my Windows10 computer but I'm unsuccessful untill now. I have made all steps from the “Building on Windows” on [[https://docs.tvm.ai/install/from_source.html ](https://docs.tvm.ai/install/from_source.html)]. Namely: 1. Installed Visual Studio Community

[TVM Discuss] [Questions] Quick start tutorial gives " Cannot find config for target=cuda -model=unknown, workload=('conv2d_nchw.cuda'"

I am not sure, but titan, 2080ti, 1080ti have tuned configuration in TVM. So if you want to get the optimal performance for the 1070ti, tuning seems to be the right choice. also There is a simple tuning template provided in the TVM tutorial, so use it to tune it. --- [Visit Topic](https:

[TVM Discuss] [Questions] Relay.build can't find config for a conv2d that doesn't exist in model

I'm using tvm to convert a tensorflow model. when I call relay.build, there comes a warning, > Cannot find config for target=cuda, workload=('conv2d_nchw.cuda', ('TENSOR', > (1, 384, 35, 35), 'float32'), ('TENSOR', (224, 384, 1, 1), ' but in fact, I searched the tf model and can't find a conv2

[TVM Discuss] [Questions] How to use a specific aarch64 llvm intrinsic

Hi all, I was wondering how can I call a specific llvm intrinsic from within a compute node. Something on the line of: ``` def test(x): def _compute(*indices): value = x(*indices) return call_llvm_aarch64_intrinsic(value) return te.compute(x.shape, _co

[TVM Discuss] [Questions] Quick start tutorial gives " Cannot find config for target=cuda -model=unknown, workload=('conv2d_nchw.cuda'"

Hi, I am also facing same warning issue while running ***resnet-50*** on **'GeForce GTX 1070'** with *--model=1080ti*, and taking **4.58ms** for [inferencing](https://github.com/apache/incubator-tvm/blob/master/apps/benchmark/gpu_imagenet_bench.py) which is nearly twice than actual expected v