Can't "coder.loa​dDeepLearn​ingNetwork​" import a custom network model?

When I am going to use GPU Coder to generate cuda code for my custom depth model, matlab2019b unexpectedly terminates, and matlab2019a reports that fopen generates invalid identifier), how can I solve it? In addition, the custom model I imported is also very simple, bvlc's googlenet, not comes with pre-trained googlenet, my code is as follows, the model see attachment (can be loaded to matlab normally, each layer also supports code generation)

my gpu environment is OK:

envCfg = coder.gpuEnvConfig('host');
envCfg.DeepLibTarget = 'cudnn';
envCfg.DeepCodegen = 1;
envCfg.Quiet = 1;
coder.checkGpuInstall(envCfg);

and the code deploy is:

function out = googlenet_predict(in) %#codegen
persistent mynet;

if isempty(mynet)
    mynet = coder.loadDeepLearningNetwork('bvlc_googlenet.mat','googlenet'); % can directly load to matlab workspace,but can't load to GPU Coder to generate??? 
end

% pass in input   
out = predict(mynet,in); 

The code that generates the configuration is：

cfg = coder.gpuConfig('dll');
cfg.TargetLang = 'C++';
cfg.DeepLearningConfig = coder.DeepLearningConfig('cudnn');
cfg.DeepLearningConfig.AutoTuning = true;
codegen -config cfg googlenet_predict -args {ones(224,224,3)} -report

My matlab version environment is：

MATLAB Version: 9.7.0.1190202 (R2019b)

OS：win10

download model: bvlc_googlenet.mat

reference:https://ww2.mathworks.cn/help/gpucoder/examples/code-generation-for-deep-learning-networks.html

Answer 1

[David Fink]

The crash in R2019b and error in R2019a are not expected.

Please reach out to MathWorks Technical Support with the reproduction steps (as you've described above) and files.