scalar-autograd/dist/ValueActivation.js

Scalar-based reverse-mode automatic differentiation in TypeScript.

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.ValueActivation = void 0;
const Value_1 = require("./Value");
class ValueActivation {
    static relu(x) {
        const r = Math.max(0, x.data);
        return Value_1.Value.make(r, x, null, (out) => () => {
            if (x.requiresGrad)
                x.grad += (x.data > 0 ? 1 : 0) * out.grad;
        }, `relu(${x.label})`);
    }
    static softplus(x) {
        const s = Math.log(1 + Math.exp(x.data));
        return Value_1.Value.make(s, x, null, (out) => () => {
            x.grad += 1 / (1 + Math.exp(-x.data)) * out.grad;
        }, `softplus(${x.label})`);
    }
    static tanh(x) {
        const t = Math.tanh(x.data);
        return Value_1.Value.make(t, x, null, (out) => () => {
            if (x.requiresGrad)
                x.grad += (1 - t ** 2) * out.grad;
        }, `tanh(${x.label})`);
    }
    static sigmoid(x) {
        const s = 1 / (1 + Math.exp(-x.data));
        return Value_1.Value.make(s, x, null, (out) => () => {
            if (x.requiresGrad)
                x.grad += s * (1 - s) * out.grad;
        }, `sigmoid(${x.label})`);
    }
}
exports.ValueActivation = ValueActivation;