I can train NetModel's models with CPU. I'm on Windows 10 with Mathematica 11.2 GPU is GTX1080 with 8G memory.

My datasets is 1000 pictures with 224*224.

I can train some NetModel like Inception V1 Trained on ImageNet Competition Data with TargetDevice->"GPU"

But I cannot train some NetModel like ResNet-152 Trained on ImageNet Competition Data with TargetDevice->"GPU"

NetTrain::interr: An internal error occurred. Please contact Wolfram Research.

Since I can train some model with GPU, I think my graphics card driver is OK. Since I can train them with CPU, I think Mathematica implement their layers.

I can use ImageRestyle with TargetDevice->"GPU", if I encounter with the problem An internal error occurred in training NetModel, then ImageRestyle also gives the same error information unless I Quit or Restart Mathematica.

I can train with GPU:

"Inception V1 Trained on ImageNet Competition Data"

"Wolfram ImageIdentify Net for WL 11.1"

"Yahoo Open NSFW Model V1"

"SqueezeNet V1.1 Trained on ImageNet Competition Data" crashes my kernel like Quit.

Well, some net can be trained with 20/30 pictures, but some can be trained by 1000 pictures....I'm not sure whether this is normal?

Even I use File object, the Out of Core training, it also gives the error information, and has limit number of training set.

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    $\begingroup$ Could you post the output of: Internal`$LastInternalFailure and Internal`$LastUncaughtFailure? I'm pretty sure the problem is that your GPU is running out of memory, and this is not being reported correctly. $\endgroup$
    – Sebastian
    Commented Sep 17, 2017 at 10:03
  • $\begingroup$ @Sebastian wow, yes, your're right. MXNetError [19:32:16] : cudaMalloc failed: out of memory, I overrate the ability of GTX1080, my datasets is 1000 pictures. But the problem is even I use only 100 pictures, it alslo gives the error... $\endgroup$ Commented Sep 17, 2017 at 11:35
  • $\begingroup$ @Sebastian I can train ResNet-152 with 30 pictures. $\endgroup$ Commented Sep 17, 2017 at 11:48
  • $\begingroup$ 1000 images should be fine: its not loading them all into GPU memory. Can you try BatchSize -> 32 in NetTrain? Does it work now on the full dataset? $\endgroup$
    – Sebastian
    Commented Sep 18, 2017 at 10:51
  • $\begingroup$ @Sebastian It's OK, thank you, I think you can post an answer. $\endgroup$ Commented Sep 18, 2017 at 11:03

1 Answer 1


The cause is the GPU running out of memory, and Mathematica not correctly reporting the failure (ResNet 152 is very memory hungry!).

This can be seen by running Internal`$LastInternalFailure, which will include a line "cudaMalloc failed: out of memory". I have reported this incorrect reporting as a bug.

Try a smaller BatchSize in NetTrain to reduce your memory usage in order to train a large net like this.


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