On: Deep Learning in JavaScript

[eiriklv]

Edit: Great work! I'd love to have a nice alternative to PyTorch in JavaScript :)

Edit: formatting

Making JavaScript look like Python in this case could potentially bite you in the ass.

From the example:

    const torch = require("js-pytorch");

    // Instantiate Tensors:
    x = torch.randn([8,4,5]);
    w = torch.randn([8,5,4], requires_grad = true);
    b = torch.tensor([0.2, 0.5, 0.1, 0.0], requires_grad = true);

And:

    class Transformer extends nn.Module {
      constructor(vocab_size, hidden_size, n_timesteps, n_heads, p) {
        //.....
        this.b1 = new nn.Block(hidden_size, hidden_size, n_heads, n_timesteps, dropout_p=p);

For both `requires_grad` and `dropout_p` you wouldn't be able to change the ordering + you're creating global variables.

    /**
     * All of the arguments for this function are positional
     * and cannot be provided in a different order than defined
     */
    function performOperation(values, arg1 = false, arg2 = -1) {
        //....
    }

    /**
     * This works, but only because of the order
     */
    const result = performOperation([1, 2, 3], arg1 = true, arg2 = 10);

    /**
     * This does not work
     */
    const result = performOperation([1, 2, 3], arg2 = 10, arg1 = true);

    /**
     \* What is actually happening
     \*/
    arg1 = true; // global variable
    arg2 = 10;   // global variable

    const result = performOperation([1, 2, 3], 10, true);

[eduardoleao052 → eiriklv]

Thats true, it’s a limitation of working between these languages. I tried to mitigate it by using clear JSDoc, so that each variable pops up alongside an explanation when calling a function.

[eiriklv → eduardoleao052]

I feel you - Python has much better (more flexible) argument support than JavaScript in this case. Converting the entire set of arguments into a keyed object is usually what happens, but then it wouldn't look like PyTorch anymore.