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Describe the feature and the current behavior/state. iNALU (improved Neural Arithmetic Logic Modules) is the layer to learn addition, subtraction, multiplication, and division in a fully explainable/transparent way. Due to the mathematical nature of the layer, inference works well on OOD (out of distribution) inputs. Relevant information

• Are you willing to contribute it (yes/no): yes If you wish to contribute, then read the requirements for new contributions in CONTRIBUTING.md
• Are you willing to maintain it going forward? (yes/no): yes
• Is there a relevant academic paper? (if so, where): iNALU
• Does the relavent academic paper exceed 50 citations? (yes/no): no
• Is there already an implementation in another framework? (if so, where): inalu
• Was it part of tf.contrib? (if so, where):

Which API type would this fall under (layer, metric, optimizer, etc.) layer Who will benefit with this feature? Everyone Any other info. Original NALU paper has 160+ citations . Thank you