third module: Federated Learning & HE

leriomaggio · Sep 9, 2021 · 4c58d8d · 4c58d8d
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diff --git a/3-federated-learning-he/1 Intro to Federated Learning.ipynb b/3-federated-learning-he/1 Intro to Federated Learning.ipynb
diff --git a/3-federated-learning-he/2 Homomorphic Encryption.ipynb b/3-federated-learning-he/2 Homomorphic Encryption.ipynb
diff --git a/3-federated-learning-he/3 Federated Learning and HE.ipynb b/3-federated-learning-he/3 Federated Learning and HE.ipynb
diff --git a/3-federated-learning-he/Duet/duet_fl/Duet_FL_1_Data_Owner.ipynb b/3-federated-learning-he/Duet/duet_fl/Duet_FL_1_Data_Owner.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "composed-receipt",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import syft as sy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "continent-climb",
+   "metadata": {},
+   "source": [
+    "# Part 1: Launch a Duet Server and upload data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "parental-classics",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "duet = sy.launch_duet(loopback=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dying-switch",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch as th\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "focused-error",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = th.FloatTensor(np.array([5, 15, 25, 35, 45, 55]).reshape(-1, 1))\n",
+    "\n",
+    "data = data.tag(\"DO1 data\")\n",
+    "data = data.describe(\"Dataset of 6 samples, 1 feature\")\n",
+    "\n",
+    "data_ptr = data.send(duet, pointable=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "circular-commodity",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "duet.store.pandas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "undefined-keeping",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "thousand-borough",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "duet.requests.add_handler(\n",
+    "    action=\"accept\",\n",
+    "    print_local=True,  # print the result in your notebook\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "assigned-tomato",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/3-federated-learning-he/Duet/duet_fl/Duet_FL_2_Data_Owner.ipynb b/3-federated-learning-he/Duet/duet_fl/Duet_FL_2_Data_Owner.ipynb
@@ -0,0 +1,120 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "electric-requirement",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import syft as sy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dependent-pharmacy",
+   "metadata": {},
+   "source": [
+    "# Part 1: Launch a Duet Server and upload data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dirty-subject",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "duet = sy.duet(loopback=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "different-setup",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch as th\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "continent-sixth",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = th.FloatTensor(np.array([60, 65, 75, 85, 95]).reshape(-1, 1))\n",
+    "\n",
+    "data = data.tag(\"DO2 data\")\n",
+    "data = data.describe(\"Dataset of 5 samples, 1 feature\")\n",
+    "\n",
+    "data_ptr = data.send(duet, pointable=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "tropical-addition",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "duet.store.pandas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "nearby-usage",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "under-revolution",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "duet.requests.add_handler(\n",
+    "    action=\"accept\",\n",
+    "    print_local=True,  # print the result in your notebook\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "every-banana",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}