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Efficiently Update a 3x3 Tensor Patch in TensorFlow Using Center Index

Discover how to efficiently update a 3x3 patch in a TensorFlow tensor based on a center index, ideal for larger tensors. --- This video is based on the question https://stackoverflow.com/q/71170858/ asked by the user 'Amit Davidi' ( https://stackoverflow.com/u/14558417/ ) and on the answer https://stackoverflow.com/a/71172464/ provided by the user 'AloneTogether' ( https://stackoverflow.com/u/9657861/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: updating an entire 3x3 patch based on a center index, (efficiently) - tensorflow Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l... The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license. If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. --- Efficiently Update a 3x3 Tensor Patch in TensorFlow Using Center Index In deep learning and data manipulation, especially when working with tensors, there may come a time when you need to update a specific part of your tensor. In this guide, we will tackle how to efficiently update an entire 3x3 patch of a tensor centered around a given index using TensorFlow. The Problem: Updating a Tensor Patch Consider a scenario where you have a tensor that looks like this: [[See Video to Reveal this Text or Code Snippet]] You want to modify the entire 3x3 patch based on a center index, in this example [0, 0, 1, 1], which corresponds to the value -0.44149. The goal is to change all elements in that patch to 0.0. The Solution: Efficiently Updating the Tensor Patch To achieve this, we'll utilize TensorFlow's tf.tensor_scatter_nd_update to ensure efficiency, especially if you're working with larger tensors like (1, 16, 30, 30). Here's a step-by-step process on how to implement this. Step-by-Step Implementation Define the Tensor: Start by defining your tensor. [[See Video to Reveal this Text or Code Snippet]] Specify the Center Index: Define the center index that you will be using to modify the patch. [[See Video to Reveal this Text or Code Snippet]] Calculate the Indices for the Patch: Use tf.meshgrid to generate the correct indices for updating the tensor. [[See Video to Reveal this Text or Code Snippet]] Create Updates: Prepare the updates to be applied to the tensor. [[See Video to Reveal this Text or Code Snippet]] Update the Tensor: Finally, perform the update using tf.tensor_scatter_nd_update. [[See Video to Reveal this Text or Code Snippet]] Expected Result Running the above code will yield an updated tensor as follows: [[See Video to Reveal this Text or Code Snippet]] Conclusion By following the steps outlined above, you can efficiently update a 3x3 patch of a tensor in TensorFlow based on a central index. This method not only proves effective for the given example but can also seamlessly scale to larger tensors, making it a valuable technique in your TensorFlow toolkit. Feel free to adjust the indices and tensor values in this code snippet to fit your specific use case. Happy coding!