Hello community,
I would like to create a simple NADE model with Tensorflow, only with a few dense layers, and applied to Mnist dataset.
Here is my (really untidy sketch of) model :
The idea is to predict the next pixel of a flattened image from the previous one. Concerning the maths behind, everything’s clear, it’s really with the coding that I am getting confused 
.
I sliced my inputs using tf.slice() in a for loop, then concatenate, to gather back everything in one layer. I am getting value errors from the slices that I do not understand.
Note : I introduced some approximations in the notebook for the debugging, even though I am sure it won’t work (to debug).
Maybe the error is obvious but I can’t see it thanks a lot for the help ! And also, making tidy work is really, pathologically hard for me, then thanks for helping make my question and work also clearer 
I am really grateful for your patience
Have all a nice day !
Nicolas