Hi,

I try to understand Deepdetect right now, starting with the Plattforms Docker container.
It looks great on pictures, but I have a hard time right now using it :)

My Problem: The docs seems to step over important points, like using JupyterLab. All examples shows the finished Custom masks, but how do I get them?

Is there something missing in the docs?

Example: https://www.deepdetec

Changes made in #1874 to test/models/mxnet/1rnn_layer_3lstm.json reveal an error in the fusion of a sequence of LSTM cells into a single layer RNN for gpu.

The fused result should look like:

Instead, we currently see:
![rnn_fusion_issue](https://user-images.githubusercontent.com/48

We don't need accurate neural networks.
Often, we don't even need any "sound" neural networks.
Sometimes you just need to test if you can feed inputs and get outputs from the networks (e.g., #2155).

Thus, in many cases neural networks that do "Output[i,j,k] = Input[i,j,k] + Input[k.j.i]" (or anything similarly stupid) should be just fine. Let's not use really working neural networks for unit