尝试 运行 nvidia 在 Jetson TX2 上的教程代码时，为什么层权重为空且 TRT 未找到缓存？

Question

我正在尝试 运行 来自 nvidia 的 repo here. 的教程代码 这是我的 Jetson TX2 上的控制台 imagenet 程序发生的情况：

    nvidia@tegra-ubuntu:~/jetson-inference/build/aarch64/bin$ ./imagenet-console orange_0.pjg output_0.jpg
imagenet-console
  args (3):  0 [./imagenet-console]  1 [orange_0.pjg]  2 [output_0.jpg]  


imageNet -- loading classification network model from:
         -- prototxt     networks/googlenet.prototxt
         -- model        networks/bvlc_googlenet.caffemodel
         -- class_labels networks/ilsvrc12_synset_words.txt
         -- input_blob   'data'
         -- output_blob  'prob'
         -- batch_size   2

[TRT]  TensorRT version 4.0.2
[TRT]  attempting to open cache file networks/bvlc_googlenet.caffemodel.2.tensorcache
[TRT]  cache file not found, profiling network model
[TRT]  platform has FP16 support.
[TRT]  loading networks/googlenet.prototxt networks/bvlc_googlenet.caffemodel
Weights for layer conv1/7x7_s2 doesn't exist
[TRT]  CaffeParser: ERROR: Attempting to access NULL weights
Weights for layer conv1/7x7_s2 doesn't exist
[TRT]  CaffeParser: ERROR: Attempting to access NULL weights
[TRT]  Parameter check failed at: ../builder/Network.cpp::addConvolution::40, condition: kernelWeights.values != NULL
error parsing layer type Convolution index 1
[TRT]  failed to parse caffe network
failed to load networks/bvlc_googlenet.caffemodel
failed to load networks/bvlc_googlenet.caffemodel
imageNet -- failed to initialize.
imagenet-console:   failed to initialize imageNet

我的Jetson板子上没有安装Caffe，因为教程中明确说明不需要。我不确定如果 TRT 能够正确缓存，空权重错误是否会得到修复。有什么想法吗？

• Python 2.7
• Cuda 9.0
• TensorRT 4.0

Answer 1

公司防火墙阻止正确下载模型。手动下载模型并将它们放入网络文件夹解决了问题。