Researcher in Machine learning, Data Mining, Social Science, and Natural Language Processing
Programming languages: Python, Java, and Java Script
Public
Edited
Oct 31, 2023
plot_array_multi(
data,
{
title: "Comparison of Softmax variants",
subtitle: "Online Softmax versus Safe Softmax",
caption: "Figure 1. Comparison of Softmax variants."
},
["online_softmax", "safe_softmax", "online_softmax_functional"]
)
function get_online_softmax(logits) {
let max_val = -Infinity;
let prev_max = max_val;
let Z = 0;
for (let i = 0; i < logits.length; i++) {
max_val = Math.max(max_val, logits[i]);
Z = Z * Math.exp(prev_max - max_val) + Math.exp(logits[i] - max_val);
prev_max = max_val;
}
// console.log({ max_val, Z });
return logits.map((x) => Math.exp(x - max_val) / Z);
}
function online_softmax_reduction(state, logit) {
const max_val = Math.max(state.max_val, logit);
const Z =
state.Z * Math.exp(state.max_val - max_val) + Math.exp(logit - max_val);
return {
max_val: max_val,
Z: Z
};
}
online_softmax_state = logits.reduce(online_softmax_reduction, {
max_val: -Infinity,
Z: 0
})
online_softmax_functional = logits.map(
(x) => Math.exp(x - online_softmax_state.max_val) / online_softmax_state.Z
)
plot_array(safe_softmax)
safe_softmax
.map((x, i) => x == online_softmax[i])
.reduce((x, y) => x && y, true)
data = get_combined_data_from_object({
safe_softmax,
online_softmax,
online_softmax_functional
})
function get_combined_data_from_object(obj) {
return Object.entries(obj)
.map(([k, v]) => v.map((x, i) => Object({ index: i, val: x, source: k })))
.reduce((x, y) => x.concat(y), []);
}
[1, 2, 3].indexOf(5)
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