**Problem :**

I am trying to compute a loss on the jacobian of the network but encountered following error

**one of the variables needed for gradient computation has been modified by an inplace operation**

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Please note **grad_output.zero_()** is in-place and so is **grad_output[:, i-1] = 0**. In-place means "modify a tensor instead of returning a new one, which has the modifications applied". An example which uses the zero out the 1st column as follows :

e.g.

import torch t = torch.randn(3, 3) ixs = torch.arange(3, dtype=torch.int64) zeroed = torch.where(ixs[None, :] == 1, torch.tensor(0.), t) zeroed tensor([[-0.6616, 0.0000, 0.7329], [ 0.8961, 0.0000, -0.1978], [ 0.0798, 0.0000, -1.2041]]) t tensor([[-0.6616, -1.6422, 0.7329], [ 0.8961, -0.9623, -0.1978], [ 0.0798, -0.7733, -1.2041]])

Notice how the **t** retains values it had before and also zeroed has the values which you want.