MobilenetV2-ssd is failed!

[linuxsky]

onverted to TensorRT: Fill, Merge, Switch, Range, ConcatV2, ZerosLike, Identity, NonMaxSuppressionV3, Minimum, StridedSlice, Shape, Split, Where, Exp, ExpandDims, Unpack, GatherV2, NoOp, TopKV2, Cast, Placeholder, Mul, Pack, Reshape, ResizeBilinear, Squeeze, Add, Greater, Const, Sub, Transpose, Slice, (For more information see https://docs.nvidia.com/deeplearning/dgx/integrate-tf-trt/index.html#support-ops). 2019-03-29 13:17:01.262911: I tensorflow/contrib/tensorrt/convert/convert_graph.cc:928] Number of TensorRT candidate segments: 1 [1] 27275 killed python3 camera_tf_trt.py --image --filename --model ssd_mobilenet_v2_coco

[lbcastro]

I'm having the exact same problem when running that script on the Jetson Nano.

[atyshka]

Are you getting out of memory? That's the problem I've been having. Does anyone know if Tensorrt is device agnostic? If so we could try the tensorrt optimization on a desktop with more memory and transfer the model to the nano.

[isra60]

You should modify the default parameters on the optimize function.

AFAIK the optimization must be done in the device you are going to use for inference.

[jaybdub]

Hi All,

I was able to optimize on Jetson Nano with 4GB of swap enabled using the released TensorFlow 1.13

You can permanently add 4GB of swap with the following commands

sudo fallocate -l 4G /var/swapfile
sudo chmod 600 /var/swapfile
sudo mkswap /var/swapfile
sudo swapon /var/swapfile
sudo bash -c 'echo "/var/swapfile swap swap defaults 0 0" >> /etc/fstab'

Please let me know if you run into any issues.

Thanks! John