save function
The best retro video game consoles for 2022
Since the hugely successful launch of the Nintendo NES Classic Edition back in 2016, the retro games console has become a lucrative little side hustle for the big console manufacturers and smaller retro hardware companies; so much so that machines such as the SNES Classic Mini and Mega Drive Mini – which are both excellent – are now hard to get hold of without paying vastly inflated prices. Here, though, are six superb alternatives you can buy now without too much of a hunt or the need to take out a second mortgage. You can still grab one of these on Amazon in the UK and it's worth it. If you never owned a PC Engine (or TurboGrafx as it was known in the west) here's your chance to appreciate one of the great 16bit machines, where well-known favourites Castlevania and R-Type rub pixellated shoulders with arcane wonders such as Military Madness and JJ and Jeff. You get a save function, some basic screen display modification options and two joystick ports for multiplayer fun.
- Europe > United Kingdom (0.36)
- Asia > China > Guangdong Province > Shenzhen (0.05)
Loading tensorflow models from Amazon S3 with Tensorflow Serving
In this article, I am going to show you how to store a Tensorflow model in a file, upload it to Amazon S3, and configure the Docker image of Tensorflow Serving to serve that model via REST API. Before we start, we have to save a Tensorflow model in a file using the simple_save function. I'm going to assume that you have already trained your model. We need to specify the output directory and make sure that such a location exists. When the target directory is ready, we can call the simple_save function.
Loading tensorflow models from Amazon S3 with Tensorflow Serving
In this article, I am going to show you how to store a Tensorflow model in a file, upload it to Amazon S3, and configure the Docker image of Tensorflow Serving to serve that model via REST API. Before we start, we have to save a Tensorflow model in a file using the simple_save function. I'm going to assume that you have already trained your model. We need to specify the output directory and make sure that such a location exists. When the target directory is ready, we can call the simple_save function.