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Kotlin extension function to convert Java8 Optional<T> to Kotlin nullable T?
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:: This is based mostly on my own personal research and testing. My objective is to secure/harden Windows 10 as much as possible while not impacting usability at all. (Think being able to run on this computer's of family members so secure them but not increase the chances of them having to call you to troubleshoot something related to it later on). References for virtually all settings can be found at the bottom. Just before the references section, you will always find several security settings commented out as they could lead to compatibility issues in common consumer setups but they're worth considering.
:: Obligatory 'views are my own'. :)
:: Thank you @jaredhaight for the Win Firewall config recommendations!
:: Thank you @ricardojba for the DLL Safe Order Search reg key!
:: Thank you @jessicaknotts for the help on testing Exploit Guard configs and checking privacy settings!
:: Best script I've found for Debloating Windows 10: https://github.com/Sycnex/Windows10Debloater
And indeed, after a while, Authy changed something in their backend which now prevents the old desktop app from logging in. If you are already logged in, then you are in luck, and you can follow the instructions below to export your tokens.
If you are not logged in anymore, but can find a backup of the necessary files, then restore those files, and re-install Authy 2.2.3 following the instructions below, and it should work as expected.
This is an Keras implementation of ResNet-152 with ImageNet pre-trained weights. I converted the weights from Caffe provided by the authors of the paper. The implementation supports both Theano and TensorFlow backends. Just in case you are curious about how the conversion is done, you can visit my blog post for more details.
ResNet Paper:
Deep Residual Learning for Image Recognition.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
arXiv:1512.03385
Keras Layer that implements an Attention mechanism, with a context/query vector, for temporal data. Supports Masking. Follows the work of Yang et al. [https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf] "Hierarchical Attention Networks for Document Classification"
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In your local clone of your forked repository, you can add the original GitHub repository as a "remote". ("Remotes" are like nicknames for the URLs of repositories - origin is one, for example.) Then you can fetch all the branches from that upstream repository, and rebase your work to continue working on the upstream version. In terms of commands that might look like:
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