frugally-deep: Test fails during load

Hi Tobias, thanks for this great library!

I’m having problems with a model and I’m not sure how to debug it.

I’m using the functional API with the following layer types: Dense, Conv1D, Concatenate, Embedding and Flatten. The conversion of the model runs without any problem, but when I’m loading in it I get the following error:

Running test 1 of 1 ... libc++abi.dylib: terminating with uncaught exception of type std::runtime_error: size_dim_5, size_dim_4, height and width dimension must be 1, but shape is '[(1, 1, 1, 200, 20)]'

I can set false to the test, but then I get the exception when running a prediction.

I’ve run it with lldb and the problem seems to be a mismatch in the output layer dimension (which is supposed to have 2 neurons). The described shape [(1,1,1,200,20)] matches one of the inputs’ shape (I’m using 5 input tensors).

I’m not really sure how to debug this. Any idea?

The Keras model and the fdeep conversion can be found in this file.

I’m using the last commit of this repo. Keras and Tensorflor versions:

Using TensorFlow backend.
2.2.4

$ python3 -c 'import tensorflow as tf; print(tf.__version__)'
1.12.0

Thanks in advance!