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Takes a 4d Tensor (-1,gs,ags,param) and transforms it using a simple Dense Layer into a 3d one (-1,gs,paramo). Respects Graph permutation Symmetry. So Basically Transforms each set of vectors into one vector of different size
Arguments
* **gs**: The Number of Lists of Feature Vectors and the Number of Nodes in the Output
* **ags**: The Number of Vectors in each List of Input vector, could be understood as the opposite of c
* **param**: The Number of Features for each Input Node
* **paramo**: The Number of Features each Outputvector should have
* **initializer=glorot_uniform**: The Transformation initializer
* **learnabel=True**: Shall the Transformation be learnable