You will be already 5000 times slower by the fact alone that Google used 5000 servers, (if I recall correctly), and you only have a single PC. And each Google server contained 4 TPU boards, each capable of performing 256 (or was it 1024) multiplications per clock cycle, while a single core in a PC can do only 8. So I think you are way too optimistic.
I am not sure what your latest comment refers to. If it is the difference between AlphaZero and NNUE: the main point there is that the NNUE net uses 5 layers of 32 cells, plus an initial layer that can be calculated incrementally, (so that the size matters little). While the AlphaZero net typically has 32 layers of 8 x 8 x 256 cells.
I don't want to discourage you, but the task you want to tackle is gigantic, and not very suitable as an introductory exercise in chess programming. A faster approach would be to start with something simple (at the level of Fairy-Max or King Slayer, simple alpha-beta searchers with a hand-crafted evaluation) to get some experience with programming search, then replace its evaluation by NNUE, to get some experience programming neural nets. The experience you gain in the simpler preliminary tasks will speed up your progress on the more complex final goal by more than the simple tasks take. Also note that you will have the disadvantage compared to people who do this for orthodox chess of not having high-quality games available to train the networks.
You will be already 5000 times slower by the fact alone that Google used 5000 servers, (if I recall correctly), and you only have a single PC. And each Google server contained 4 TPU boards, each capable of performing 256 (or was it 1024) multiplications per clock cycle, while a single core in a PC can do only 8. So I think you are way too optimistic.
I am not sure what your latest comment refers to. If it is the difference between AlphaZero and NNUE: the main point there is that the NNUE net uses 5 layers of 32 cells, plus an initial layer that can be calculated incrementally, (so that the size matters little). While the AlphaZero net typically has 32 layers of 8 x 8 x 256 cells.
I don't want to discourage you, but the task you want to tackle is gigantic, and not very suitable as an introductory exercise in chess programming. A faster approach would be to start with something simple (at the level of Fairy-Max or King Slayer, simple alpha-beta searchers with a hand-crafted evaluation) to get some experience with programming search, then replace its evaluation by NNUE, to get some experience programming neural nets. The experience you gain in the simpler preliminary tasks will speed up your progress on the more complex final goal by more than the simple tasks take. Also note that you will have the disadvantage compared to people who do this for orthodox chess of not having high-quality games available to train the networks.