This problem was solved by linking cuda and cuda_runtime libraries when I build
gotvm.
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Hi,
I have tried to implement gotvm as a GPU-accelerating deep learning runtime
system on my edge computing architecture.
When I make gotvm without cuda, there is no error.
However, when I uncomment the cuda-related lines in tvm_runtime_pack.cc, the
following errors are occurred.
$ make
The target device is jetson nano.
AutoTVM is used to derive best logs for conv2d layers on cuda backend with
sm_52 compute capability option.
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Siju,
The problem is solved!!
When I run Yolov3-tiny on jetson nano, it takes about 35 ms for single image
inference.
Now, it takes about 120 ms for four image inference.
Greatly appreciate for your response.
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[Visit
Topic](https://discuss.tvm.ai/t/yolov3-tiny-batch-input-test-faile
Hi,
I'm trying to inference "yolov3-tiny" model with input batch_size = 4.
The input shape was (4, 3, 416, 416).
However, the shape of the output is as follows:
module.get_output(0) --> (1, 255, 26, 26)
module.get_output(1) --> (1, 255, 13, 13)
IMHO, the problem has occurred when the foll
