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License: MIT License
Javascript neural networks on top of general scalar/tensor reverse-mode automatic differentiation.
License: MIT License
Hi,
how can I save a nn I've trained up to disk, and load into NodeJS again?
thanks in advance.
In WebPPL, I've done something like this:
// Re-export Math constants etc.
Object.getOwnPropertyNames(Math).forEach(function(p) {
if (!ad.scalar.hasOwnProperty(p)) {
ad.scalar[p] = Math[p];
}
});
(Which is similar to what happens in ad.js.)
Would you accept a PR adding something similar to functions.js
, or would you prefer to handle it in some other way?
If there are some simple example for user like me. It will be great !
I really love adnn. It's beautiful and powerful. Thank you.
I am trying to work out some example for adnn.
An simple nnXor.js example run successfully as following.
https://github.com/ccckmit/ai6/tree/master/book/nn/adnn
But for the nnMlp.js example, the network output fail to approximate the training data.
https://github.com/ccckmit/ai6/blob/master/book/nn/adnn/nnMlp.js
Do I use the wrong optimization method ?
I don't know why ?
Modified version of Adam that tracks the relative change in the objective value to better adapt the learning rate:
https://arxiv.org/abs/1611.01505
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