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I have a PyTorch tensor with 0 and non 0 values, and I want to copy the non zero values in a new tensor such that it is as compact as possible. ie its shape is [num_rows,max([number of non0 values in each row])]. What is the a vectorised way to do this without putting a for loop? The following image should illustrate(black = non zero values):

enter image description here

Amogh
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    This works - [`Python: Justifying NumPy array`](https://stackoverflow.com/questions/44558215/python-justifying-numpy-array)? – Divakar Oct 01 '20 at 19:01
  • Please explain exactly what output you expect.The output you gave in the illustration isn't the most compact representation of the input's non-zero values. In fact, there are much less white(assuming they refer to the non-zero pixels) pixels in the output than in the input. – Gil Pinsky Oct 01 '20 at 20:12
  • Okay, I updated the convention : (black = non zero values) – Amogh Oct 01 '20 at 22:24

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