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using CUDA | |
import CUDA.CUDNN: cudnnConvolutionForward | |
const W1 = cu(randn(5,5,3,6)) | |
function inference(imgs) | |
out = cudnnConvolutionForward(W1, imgs) | |
return maximum(Array(out)) | |
end |
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+-----------------------------------------------------------------------------+ | |
| NVIDIA-SMI 470.103.01 Driver Version: 470.103.01 CUDA Version: 11.4 | | |
|-------------------------------+----------------------+----------------------+ | |
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | |
| | | MIG M. | | |
|===============================+======================+======================| | |
| 0 NVIDIA GeForce ... Off | 00000000:01:00.0 Off | N/A | | |
| 0% 43C P8 10W / 250W | 2256MiB / 11175MiB | 0% Default | | |
| | | N/A | |
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ERROR: LoadError: TaskFailedException | |
Stacktrace: | |
[1] wait | |
@ ./task.jl:334 [inlined] | |
[2] fetch(t::Task) | |
@ Base ./task.jl:349 | |
[3] top-level scope | |
@ ~/knightvision/piece_recognition/KnightVisionServer/test/test_cuda.jl:46 | |
nested task error: Out of GPU memory trying to allocate 13.184 MiB |
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const LOCK = ReentrantLock() | |
function inference(imgs) | |
lock(LOCK) | |
try | |
out = nn(imgs) | |
return maximum(cpu(out)) | |
finally | |
unlock(LOCK) |
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ERROR: LoadError: TaskFailedException | |
Stacktrace: | |
[1] wait | |
@ ./task.jl:334 [inlined] | |
[2] fetch(t::Task) | |
@ Base ./task.jl:349 | |
[3] top-level scope | |
@ ~/knightvision/piece_recognition/KnightVisionServer/test/test_cuda.jl:39 | |
nested task error: CUDNNError: CUDNN_STATUS_INTERNAL_ERROR (code 4) |
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# After execution gets stuck, sending `schedule(t, nothing, error=true)` to the task: | |
Stacktrace: | |
[1] try_yieldto(undo::typeof(Base.ensure_rescheduled)) | |
@ Base ./task.jl:777 | |
[2] wait() | |
@ Base ./task.jl:837 | |
[3] wait(c::Base.GenericCondition{ReentrantLock}) | |
@ Base ./condition.jl:123 | |
[4] wait(e::Base.Event) | |
@ Base ./lock.jl:366 |
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ERROR: LoadError: TaskFailedException | |
Stacktrace: | |
[1] wait | |
@ ./task.jl:334 [inlined] | |
[2] fetch(t::Task) | |
@ Base ./task.jl:349 | |
[3] top-level scope | |
@ ~/knightvision/piece_recognition/KnightVisionServer/test/test_cuda.jl:39 | |
nested task error: CUDNNError: CUDNN_STATUS_INTERNAL_ERROR (code 4) |
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ERROR: LoadError: TaskFailedException | |
nested task error: Out of GPU memory trying to allocate 897.217 MiB | |
Effective GPU memory usage: 52.47% (5.726 GiB/10.913 GiB) | |
Memory pool usage: 3.117 GiB (3.656 GiB reserved) | |
Stacktrace: | |
[1] macro expansion | |
@ ~/.julia/packages/CUDA/0IDh2/src/pool.jl:219 [inlined] | |
[2] macro expansion | |
@ ./timing.jl:299 [inlined] |
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using Flux | |
const nn = gpu(Chain( | |
Conv((5, 5), 3=>6, relu), | |
MaxPool((2, 2)), | |
Conv((5, 5), 6=>16, relu), | |
MaxPool((2, 2)), | |
flatten, | |
Dense(256, 120, relu), | |
Dense(120, 84, relu), |
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hello |
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