{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import jax, jax.numpy as jnp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "LABELS = jax.random.uniform(jax.random.PRNGKey(0), (5, 1))  # the annotated labels y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pairwise_labels = LABELS - LABELS.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Array([[0.57450044],\n",
       "        [0.09968603],\n",
       "        [0.39316022],\n",
       "        [0.8941783 ],\n",
       "        [0.59656656]], dtype=float32),\n",
       " Array([[ 0.        ,  0.47481441,  0.18134022, -0.31967783, -0.02206612],\n",
       "        [-0.47481441,  0.        , -0.2934742 , -0.79449224, -0.49688053],\n",
       "        [-0.18134022,  0.2934742 ,  0.        , -0.50101805, -0.20340633],\n",
       "        [ 0.31967783,  0.79449224,  0.50101805,  0.        ,  0.2976117 ],\n",
       "        [ 0.02206612,  0.49688053,  0.20340633, -0.2976117 ,  0.        ]],      dtype=float32))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LABELS, pairwise_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def binary_cross_entropy(prediction, target):\n",
    "    return -(target * jnp.log(prediction) + (1 - target) * jnp.log(1 - prediction))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Array(0.6931472, dtype=float32, weak_type=True)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "binary_cross_entropy(0.5, 1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "jax_env",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
