# \[Solved\]\[Pytorch1.5\] RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation

**URL:** <https://discuss.pytorch.org/t/solved-pytorch1-5-runtimeerror-one-of-the-variables-needed-for-gradient-computation-has-been-modified-by-an-inplace-operation/90256>\
**Category:** autograd\
**Created:** [July 23, 2020, 9:52am UTC](https://discuss.pytorch.org/t/solved-pytorch1-5-runtimeerror-one-of-the-variables-needed-for-gradient-computation-has-been-modified-by-an-inplace-operation/90256 "2020-07-23T09:52:12Z")\
**Posts on this page:** 1\
**Showing post:** 22

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**Author:** ![ptrblck](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/ptrblck/32/1823_2.png) [@ptrblck](https://discuss.pytorch.org/u/ptrblck)\
**Post date:** [July 4, 2021, 10:20pm UTC](https://discuss.pytorch.org/t/solved-pytorch1-5-runtimeerror-one-of-the-variables-needed-for-gradient-computation-has-been-modified-by-an-inplace-operation/90256/22 "2021-07-04T22:20:57Z")

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I guess the error is raised, since you are not detaching the hidden state, are retaining the graph, and updating the parameters in each iteration. This would cause the intermediate forward activations from the previous iterations be become “stale” and the gradient computation would fail.  
I don’t know what your exact use case is, but you might want to `detach()` the hidden and cell states in each iteration and remove `retain_graph=True` as well.

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