# Single weight-sharing across a network

**URL:** <https://discuss.pytorch.org/t/single-weight-sharing-across-a-network/67798>\
**Category:** Uncategorized\
**Created:** [January 27, 2020, 4:41pm UTC](https://discuss.pytorch.org/t/single-weight-sharing-across-a-network/67798 "2020-01-27T16:41:39Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![adamr](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/adamr/32/27859_2.png) [@adamr](https://discuss.pytorch.org/u/adamr)\
**Post date:** [August 16, 2020, 11:01am UTC](https://discuss.pytorch.org/t/single-weight-sharing-across-a-network/67798/2 "2020-08-16T11:01:46Z")

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I am not sure if you can share _part_ of the tensor. Try [How to use shared weights in different layers of a model](https://discuss.pytorch.org/t/how-to-use-shared-weights-in-different-layers-of-a-model/71263) and see if that works if you apply it to your case. I am curious too.

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