diff --git a/federated_learning/FedAvg_FedProx_MNIST_iid_and_noniid.ipynb b/federated_learning/FedAvg_FedProx_MNIST_iid_and_noniid.ipynb
index 4d8e868fced82577703d2bb704922701c083ef9d..5784a5f1645997aadcabf235b90f8cc0736cc2fb 100644
--- a/federated_learning/FedAvg_FedProx_MNIST_iid_and_noniid.ipynb
+++ b/federated_learning/FedAvg_FedProx_MNIST_iid_and_noniid.ipynb
@@ -51,7 +51,106 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to ./data/MNIST/raw/train-images-idx3-ubyte.gz\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4389e5027739448da6070543043193fc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Extracting ./data/MNIST/raw/train-images-idx3-ubyte.gz to ./data/MNIST/raw\n",
+      "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to ./data/MNIST/raw/train-labels-idx1-ubyte.gz\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1112dcadabae4116988d0b1ffd382601",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Extracting ./data/MNIST/raw/train-labels-idx1-ubyte.gz to ./data/MNIST/raw\n",
+      "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to ./data/MNIST/raw/t10k-images-idx3-ubyte.gz\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "068a093f7eb548dd817a15e59fffb7ed",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Extracting ./data/MNIST/raw/t10k-images-idx3-ubyte.gz to ./data/MNIST/raw\n",
+      "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to ./data/MNIST/raw/t10k-labels-idx1-ubyte.gz\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "cd877fec7d0740d486872b0802d4297a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Extracting ./data/MNIST/raw/t10k-labels-idx1-ubyte.gz to ./data/MNIST/raw\n",
+      "Processing...\n",
+      "Done!\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "from create_MNIST_datasets import get_MNIST, plot_samples\n",
     "mnist_iid_train_dls, mnist_iid_test_dls = get_MNIST(\"iid\",\n",
@@ -73,7 +172,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 288x288 with 20 Axes>"
       ]
@@ -85,7 +184,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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t0vLYIG2PL82MTSwYQRAcQxSMIAiOIQpGEATHEAUjCIJjiIIRBMExUptFCgtnz55l5cqVAAwaNAiAzZs3YxhWYLp48eK88847ADRp0iQyQgosX76cgQMHAnDXXXcB0KlTJzZu3AjAsWPHAFi8eLF+ji+88ELY5QwF9Tk8fPgwAO+99x6//PILAPfffz8AQ4YMIV++fADUrl07AlLGDmLBCILgGIZppjjlbvt8/NWrV1mxYgUAc+bMAWD69OlcvXo1xfOKFy8OwE8//QRA1qxZkztUciksbBvb4sWLAWjYsCFXrlyxLv7n50ZZmUl54IEHAOjduzcdOnQAIH36VA3miDy7S5cuAfD888+zYcMGAI4fP57iObVq1QJg0aJFgdzK9mennsN//vMf/ve//wGQJ08eAHbv3k3u3LkDkS8UJA9GEITwEjYLRlko3bp1Y+LEickeV6hQIQDuvfdezp8/D8DevXv1/lOnTgGQM2fO5C4RNRbMF198AcDYsWO1b6/eKBMmTKBx48bBXDYsFox6qy9dupRWrVoBcPHiRdfFU7Fg3FHPr1ixYqkdGvZnN3HiRD777DMA1q1b57W/QYMGnDx5EoA1a9bo7ePGjQOgffv2gdzO9me3detWAB577DGvfSNGjODVV19N8XwVPxs+fDgALVq0oG7duoBfFqc7PscWliDvpk2bePnllwGXi5OUNm3aAOggYsGCBTlw4AAA1apV0wHEaGfXrl16rKtXrwbg1q1b+ot45swZAHbu3BmsggkLX375JQDt2rXzuV99cKtWraq3KZf3m2++8VBGn376KQBvv/024AoQR4Lr168D8MEHHwAwePBgbt68qfer56SC08OHD+eTTz4BPBXMlClTgIAVjO0ol84XRYoUSfX86dOnAzBz5kz975gxYwB46aWXQpZPXCRBEBzDUQtGmW9PP/20dm2So3DhwoBluSjeeustgJiwXr799lvAmrZNTEwEXO5QixYt6NWrF+AyRZ999tkISJk6CxcuBNDyJqVKlSoAjBw50mtf06ZNAejQoYO2WgDef/99wJViUL58efsEDpB3330XsCwXXzRr1gxwWV0XL15k6dKl4RHOJtR0evXq1VM99tChQ17b5s2bB9hjwTiqYObPnw+QqnIZPXo0LVq08Nh26tQpNm3apP9fsmRJADJmzGizlKGzcOFCOnfuDFixixEjRgAuJVKgQAF9bIUKFQDXrFg0ceHCBQYMGABYuUlJee2113Q+Ukp069aN2bNne11n6tSpQOQUzNGjR7UMvihbtqyXy3P9+nV27NjhdezPP/8MwIwZM2jevLm9goZIQkICAPfcc0+qx27evNlrW9GiRW2TRVwkQRAcw1ELRpnTXjf9Mzr93//+F4COHTvq4Jqanfjiiy/YvXu3PkeZ7Hfffbdj8gaKmuXq2rUrd+7cAWDy5MnUr18/2XMyZcoUFtmC4euvv/awGhWvv/46YGVZp0uXLtXrlC5dWrtD7q5SpDh9+jRguT+//vqr137lFk2dOtVrfHny5KFbt26A6+8ArlnRiRMn0rBhQwAyZ85su+zB4O9nbPPmzZw4ccJre6VKlWyTRSwYQRAcw1EL5h//+AcA9evX19PTTZs2pU+fPgDcd999XueoAOkrr7yit5UpU4YGDRo4KWpA3L59G0BbKteuXWPChAmAFdBOiWicmlZv9Y4dO3rta9CgAd27dwcCm15u1KgREB0WjMrjcZ9mVnTs2FEH3pOzzlRuVrZs2QDPfKClS5dy48YNIDIWzP79+722pWRBu/P555/raXtFoUKFbK33c1TBqAemotIpoUw1X0G4SpUqkSNHDnuFCwH1hfvxxx8Ba3ypKRY1rueff95Z4YJAfcEuX76st9WoUQOAWbNmBZW3kly+UyRQrqwvBgwYkKpiUC6UcrW6dOlin3AhcOPGDY/vliqf8fXiBlcOkHrevpR//fr1bVWU4iIJguAYUdGuAdBu0+TJk/U2lbL83nvvRUQmX9y+fVtP7alsz+RM0t9//x2A/v3768xPVd6vyv0jzZw5cxg/frzXduXeBpt1+8MPP3htSy7oHysoFzIxMZGhQ4dGWBrLInEvo1ETJcml+CuZVba8L0qXLm2fgESJglm0aJGXa5Q9e3adWh5N7lFcXJyug1KxGOUqKVTS3ahRowBP1yPaWLZsmUeq/BNPPAHAG2+8EfQ13377bV0m4U4qdW+OcOvWLT3DB9bzA1dpSiCfLXWuPzNp4SBDhgw6Z+XAgQM6NvThhx8CVlKhitGMGjXK4+UdLsRFEgTBMRyxYFShnOoj4v42a9KkiVem4KuvvqqtgSxZsgAwbdo0nxWikcYwDO02qP4b6l+FMlFLlSoFWK7e2LFjPfZFGvW2u3z5skdFtLJggkFZQsuWLfNZZa0suvz582sXzGnGjRvnURCoijRVsWMskzFjRjp16gR4lnaov/O8efN0wbC/2N2hTywYQRAcw7bXqbJaBg8erHuYuvu+itRqWerUqQOknk8SSdQ0tSrmvHPnDmXLlgUsC+3xxx8H4JFHHgFg7ty5uu9Grly5wi2uT1q3bg14pxBMmjQJgBIlSgCB9dRVNTvLly/32K5aOgwbNgyAihUrBipuwCgL7eOPP/bYnlz7iVhF5fjMmDFDZ2ErSzKp9aKmn1WNknsRsaqRU50I7SIkBaME7N+/P59//jkQfCBPuUYpFaNFC08++STg/QCT48aNGxEJcKbErFmzACuR7rvvvtPb1RfQ32QtsIoIwSqG9IX6e4VDsShu3boFwL59+2y7psqDWb9+vW3XDJW8efMC1sSCKmVQL4mMGTPqF98jjzyiC4pVdfiQIUP0dZSCsTuALS6SIAiOEZQFo9opqsbHu3bt8tivMglV4Onq1av069cvxWuqqVxVaj59+vSUGnvHFKrTWzShplyTFo8qE1k1jk4OFZT//vvv9Ztw1apVPo9t27ZtSLIGQ2qfN3+5efOmtoIOHjwIwJIlS/T+/Pnz679lJMmbN6/uvKf6KKVPn96jVYjCV38bp9qHRP4vIwhCmiUoC+arr74CPC0XVQhWv359Xfh34cIFIPmCt4cffhiwEoa2b98OWP1cwQpCKl8ye/bswYgZVfjTHDucqOVHklpXvXv3BlzJg8l13lMLqyUXj1CxgZYtW+oOa+FELZyWFDUZ0b9/f7+uM2bMGHr06JHs/n79+unPfqRR8ZP4+PgUj0utAZydBLWqgErrd88lULM/AwcO1B30VQq6Mi0VqnhMmXRZs2bVmaPuZQGqInfgwIGBpDBHzaoCyo0oXry4DrCp7OQQsKUzvepnUqZMmYBzJSDlVQXy5MmjZ9r69u0byGVte3bq/h999JHH9gwZMgCWawOWAnHv/KZ6FKncmRMnTnDt2jWv6yvFO378+EAUTNjXtHJHzayp7pB//PGH3qdaZ4YwiyTrIgmCEF5sy4NZu3YtYJX5+1qlUWn5cePG6SlQ9yCuCkypbloNGjRg7ty5gDXVqHIrUlgPKepQeUCHDh3iwQcfjLA0nqiciLp163rligSLys4dOHAg1apVs+WawaICz8eOHdNT8oDu3aJcqECm45XV069fP51/Ei3ukT+o76i75aJQvZOjIg+mTJkyXttUvMUXNWvW1ItbJecfKv9RuVqrV6/WZmhCQkJMKRbFggUL9O++/mbRQN++ffWsSNLZQH+oVq2a7l6v3KFoaAuqmsNPmjRJm//B9KjJmDEjNWvWBFzuu90Vx+EiaVGuO6qcR+XN2IW4SIIgOEZQFoxqcqzeytu2bfPYrwqwVOFU7dq1/X6rqULCypUrs3PnTiB6mikHisoXAlfhY7RRoEAB3d9m1qxZuo9LchnVKrdJ5UA99dRTEV2pMTUyZsyoZ7wmTpyoZ5GSQ7VqVUurZMqUSU82xDq+cmIUyXXBCxWxYARBcIygpqmjnKiZplZxp/bt2+smVP/6179CvWxEpzodJmqenUNE9NmdO3cOgH/+85+AtWa86r2s4oUheAs+xyYKxg8+/vhjvXqfWg7WH1TLzwsXLujcIBuKyUTBWKTl8aWZsYmLJAiCY4gFE3v85d6CyZCWx5dmxiYWjCAIjiEKRhAEx0jNRRIEQQgasWAEQXAMUTCCIDiGKBhBEBxDFIwgCI4hCkYQBMcQBSMIgmOIghEEwTFEwQiC4BiiYARBcAxRMIIgOIYoGEEQHEMUjCAIjiEKRhAExxAFIwiCY4iCEQTBMUTBCILgGKJgBEFwDFEwgiA4higYQRAcQxSMIAiOIQpGEATHSJ/K/lhcckAW77JIy2ODtD2+NDM2sWAEQXAMUTCCIDiGKBhBEBxDFIwgCI6RWpBXEIQk1KhRg0aNGgHQtWvXCEsT3URUwezduxeAX3/9laVLlwJw5MgRAAzD0A+xYcOGkRFQENz46aefAFi+fDmNGzeOsDSpc+DAAQYOHAjAm2++ybFjxwB44oknwiaDuEiCIDhGWCyYHTt2sH37dgBmz57Njz/+CMClS5cAuHLlij7WNK0UAMMwmDt3LgDjx4+nefPm4RA1ZHbt2sXkyZM9tm3YsIGrV68CsG7dOsAaX8WKFQFo3LgxvXv3Dq+gQVKgQAEA/TYsW7YsP//8cyRFCht79uyJtAgB0bJlSy3zunXrOHHiBAD33XcfAOXLl+fjjz8GIHv27I7IIBaMIAiOERYLpnbt2hw/flz/391KAciSJQtZs2b1OOfSpUtcvnwZsAJpsWLB9OnTh6+//jrZ/XFxLp2+YcMGAB599FHH5bIL9czUOBITE1m2bBkATz31VMTkCgc3btyItAgBcf78eW1NP/PMMxw+fBiARYsWAdCrVy/27dsHwIoVKwDIkCGDrTJEJMhbtWpVAJo2bQpA3bp1KV68OOAK8nbo0IGFCxcCcPbs2QhIGT7q168faRH8YvHixZw7d85j27lz53j22WcBWL9+PQAPPvhg2GXzl86dOwPw8MMPA9CtWze/z/3qq68ckclu1HM4cOCAx/ZChQoB0L59e8B68T/55JMADB06FID+/fvbKou4SIIgOEZYLJidO3d6uA2tWrXyOmbTpk2A5WIALFmyhIwZMwLwv//9LwxShoYKWKtAWlKKFSsGwP333w+4TFKAqVOn8swzzzgsYegcPXrUp5ugnlP69NGdVjV16lTGjh0LQKVKlYDALBiFaZrazY9Gbt68CcDt27dTPO6BBx5g/vz5ANSqVQuwUkLsdNnD8onImTOnT6WiZla++OILbbpev34dsL6In376KQB16tQJh5hBc/XqVdq0aQO44iruLF68mJIlSwKu8UWzGxEopUuXBiA+Pj7CkqSOiiGFeo08efLYII0zKHcnd+7cqb64ypYtC7j+Lvv377dVwYiLJAiCY4TNpj19+jRgmW8qD2batGkAzJs3z+v4OnXqRL3loli2bBlz5szR/y9cuDBg5fyANUuULl06AB3Jj1WUa3Dnzh3AmnVQ5vVfiWj+bH7zzTeAVdLgL2rCZejQoTqD3g7EghEEwTEctWDUlPOwYcOYOHEiABcvXvTKg/GFsgKimcGDBwPw9ttv622FCxfm+++/B6Bo0aIpnq/G36NHD4cktJeTJ0965cHky5ePJk2aRFIsx7l27RoQe9Zn+fLl/T5W1VZNmDCB3377DbCCwKHiqIIpWLBgivvdI/EqfVkppQEDBpA7d24AOnXq5JCEwaFmioYMGQLArVu3uOeeewAYN25ciopFJQ8CuhBNzWhEO75m88qXLx8TL4NQUM9s165dADz++ONky5YtkiLZjvrMZs6cmSVLlgDQtm3bkK8rLpIgCI4RliCvuytUpEgR3nrrLQBq1qypt2fKlAmwMnjBypqMxiK68+fP66k9Nc1+zz336FL+5KwXFRR1d6cqVKjgpKi207p1a6+iTJURGwusWbNGW82qaNPf88BlcefNm5e77rrLfgEjSJEiRQB47LHHbL2uowpGpfovXbqUevXqAdYAUjIv3d2mzJkzOyleUEyYMEHXVSnF2bt371TjLcq9mDlzprMCOoivVHk1OxjNqCTIhQsX6mcWyAyLmg20I4fGSVatWgW4vkMvvPBCwNewO4lQXCRBEBzDUQtG5Qr4kzNw8OBBwPWWNAb0nwYAABBySURBVAyDdu3aOSdcgKgCskGDBult6g3Rt2/fVM9XFayK7NmzkzdvXvsEdBCVfXz+/HmvPBhVLBfNKPndZ4ECyVZN2gcmWss6VGV0KJaWYRi2WmpiwQiC4BhRU532wQcfePw/Pj4+qmpbVMsI9+57/mZz9u7d2yv2UrhwYdsDak6hCjN3797tlQcTC/gq0OzVqxdgfc5mzZoF+F+smbR3kZA8UaFgZsyYwaRJkzy2vfbaa+TMmTMyAiXh2LFjPt2gunXrpnjejh07ACswrFAB7lGjRtkooZASvoLTmzdv1v/Wrl0b8Mz7SEhIACz36tSpU2GQMnRatGgBwIsvvghYLq2/qNwulWRnF7HzGhIEIeaIiAWjNGv37t0Ba+pWmbGVK1cGXPkw0cC0adPYtm2b/v/UqVMBq9WnL3bv3g3AP//5T8CaJlWtCFVKdjiXjnAClWWt0g+iGRWYTm4Kdvny5fpftb9169bJXm/cuHHky5cPQFs/0YDKJVMMGTLEowg3JQYMGADAH3/8obtL2oFYMIIgOIbfFszq1asByJUrl26eFAgq67Vz5866GFAtfeGOsmqiqTuaWmpEoawPX9N5169fZ+TIkYBndzvVBCiYDmqRZuPGjV7bunTpAhA1cbKUUM293J/X/v37AciRI4dOITh9+rRuIaJiNLdu3fK6XqVKlaK6fkxZV8uXL+fMmTOA9b31hcqWnzJlCmBZ2HZa135/i1W+g2EYvPbaa4C17gpYOQUXL14EYO3atfoc5UqcO3cuxU77DzzwgJ5FUn0pYombN2+yc+dOwFrDSXXiU4wZM0Y3Wo5F1CySu3tx9913R0qcgHHPNn7ooYcAV6lA5syZPVasUIrz0KFDgJWfldQNGjZsmKPyhsobb7wBWFX6H330EWC5QEln/u7cucP7778PuBSp3etziYskCIJj+G3BKBPr3Llz2tpQU63Zs2fXGlCZZOC5/pG7earyR5QlFO3l70nzcVTehArYjh07luHDh3udlz9/fgCaNWsWU3kjSVHPLtprcZJDWcVbtmzRqQWp1bkpt8rdRVLNzaMdZYWNHj1aF9dmyZLFyzoZNmyY/iwrF97uAlwjlcImvVOlyn/22Wfa3VFr5Fy7ds3nh+/ee+/Vv6u8gho1atCgQYNQ5U6JQL4FflV1bdiwQc9ugcvHVXEi1cNGofIQ1AoJNjf49nd8tlSsXbx4URcGule3q144KmHNJmx/dqGyb98+XTGuQgIqXhEEYX12x44d0zOZe/bsIUeOHNbF//zOnz9/Xi9frOKiIRQY+xxb7L5WBUGIevy2YHyhIu3Jlewr7RlmbH8LXrt2Tc9uuWflulO9enXAslqqVasGeOcl2ERY34Jbt27l8ccf99r+V7FgbCaszw5cXfhGjx6tc2LUd75p06a6N1Nys0wBIBaMIAjhJSQLJkpx5C24d+9ewApML1iwAIAqVaoAVjanCliHIRAY1rfgkSNHdIrCb7/9pvsjq8CpstxsQiwYizQzNlEwscdf7kOaDGl5fGlmbOIiCYLgGKJgBEFwDFEwgiA4higYQRAcI7UgryAIQtCIBSMIgmOIghEEwTFEwQiC4BiiYARBcAxRMIIgOIYoGEEQHEMUjCAIjiEKRhAExxAFIwiCY4iCEQTBMUTBCILgGKJgBEFwDFEwgiA4higYQRAcQxSMIAiOIQpGEATHEAUjCIJjiIIRBMExRMEIguAYomAEQXAMUTCCIDhG+lT2x+KSA7L8qEVaHhuk7fGlmbGJBSMIgmOIghEEwTEiqmBmzZrFrFmzMAyDxMREEhMTIymOIAg2IxaMIAiOkVqQ1xGUpfLss8/qbb///jsA8fHxkRBJCBD1DGvUqMHFixcBWLp0KQAlS5aMmFxCdBERBdOsWTOvbZUrV46AJEKg/PbbbwDUrl0bgAMHDqDWN9+5cycQewrm5MmTAKxevZoFCxYAsG/fPgB++uknrl+/DsDzzz8PwDvvvEOhQoUiIGnsIS6SIAiOYai3TzLYPh+fmJjopf0rVarE2rVr7bqF5FJY2D62H374gQYNGgBw7do1vb19+/YAjB49GoD06YM2jMP+7BYvXkzfvn0B2LRpk1/nPPDAA6xatQqAggULBnI7yYMRBEGwi7DHYHr27Om1rXv37uEWQwiAb7/9FoDmzZt7WC4AHTp04KOPPgJCslzCzqlTpwBo27atnmDwRUJCAunSpQPgiy++AKw41KeffgrAwIEDnRU0xgm7i2QYLktKzRgdPnzY1lsEcKxf4zNNk5deegmACRMmkCtXLgDy588PQKlSpShRooTXeSpQOHPmzBSvX6FCBW1yZ8iQITVxwm5mV61aFcDDjZ01axYA//73v8mYMaNdtwqbi7Rr1y4Aypcvz5UrVwDIkiULgwYNAqBr164AWrkAdOvWDbBcwVKlSgGwffv2QG4b0rO7c+cOAJcvX9bblFLPnDkzN2/e9DjO/buWIUMG/XJQx/lDtmzZ/D1UXCRBEMJL2GzaESNGeG179dVXw3X7kDhz5gyffPIJYL0Vzp49C6D/VW/D5HB/k/hiy5Yt3LhxA/DLggkr8+bN88iwVukE9evXB7DTegkrjzzyCGC5PWvWrAEsd6lYsWJexyor//z583rb3r17Abh69SqZM2d2TM6jR4/q3w8dOgS4LEqAp556CoBp06YxY8YMAH755RcA8uTJQ1ycZUN07dpVf9+U9ekPqXg4qRIWFynpzFGlSpUA7Jw5csd2M3vGjBm0bNky2f3ZsmXTSuTKlSv6A6dM0mzZsukP5+3bt73O79OnD++++66/MofFRZo3bx5g5Swpkzp//vz6w/nEE0+EcvnkiMoZwA8//BCAHj166G3KNfn111+57777/L1UwM/uwQcf1PcJN0WLFmX//v3+Hi4ukiAI4SUsLpK7SQeOWS62oyyQIUOG+NxfvHhxABYuXKitlvXr11OuXDnAFQB8+umnKV26NOAyXwGqVasGwIABAxyQPjQuXLgAeAYEn3vuOacsl6hDub89e/ZkypQpHvvi4+N58cUXAQKxXoJCZUdXrVpVfx5VNnWJEiX0czp48KA+J2/evADcf//9HtdSkylnzpzx697btm0LQXILsWAEQXAMRy0YFdh1DxLGUs7LrVu3AE//N3369Dz66KMAfPnll4DLTwZ0piu4puE3b97MkSNHvK7fp08fADJlymSv4Dbg7nvny5cPgL/97W8sXLgQgJw5cwKueFpa4NatW/zxxx8AVK9eHfBMoVBTtmPHjuXpp58Oi0x33303AD///LPO11EW78SJE1m3bh0AvXv31uckJCQArml1hYrzqWe4c+dObam5U7FiRQAdIA4J0zRT+gkJrGCVCZjx8fFmfHx8QOcfPnzYPHz4sDlz5syAbhvAj1+sWLHCLF68uFm8eHFzwIABgchimqZptm7d2jQMw+OnUaNG5pUrV8wrV64Eejlbx5aU+fPnm/PnzzczZcpkZsqUyTQMw2zVqpXZqlUrs0SJEvp5Zs+e3cyePbtZpUoVc/LkyebkyZODvaU7tj+7QOjatavXczIMwyxWrJhZrFgxc9WqVeaqVatCuUXExubOpk2bzE2bNpnlypXz+I4CZvXq1c2zZ8+aZ8+eDfSyPsciLpIgCI7hiIvka579xx9/9Otc5U717NlTuyAAvXr1AmzP+vWLatWqsWfPnoDPU31SNmzY4LXvww8/dDR/IlhOnDgBoFsUgMsNmjt3rp6OV2Nbu3atVzCwdevW4RDVFnbt2sXYsWMBV7GmO23bttXlAAEWNkYd6nOoXKfNmzd7HfPZZ5+RI0cO2+7piIIZOXKkx//j4+NTbSSlcgySnqtIGhGPBVSJQDDKKVKoGIQ7Tz75JGB9AUeNGuWxb9++fXomo3PnzoDVeGrSpEnOChokalasbdu2AMyePdujvipr1qwAvPnmmwC88sorMVVjlRxr167VL+n169eH7b7iIgmC4BzJBWfMEIJNJAkcDR8+PMXjK1Wq5HVO0h8V8A022GTn+FJDBclKlSpllipVyiNgWLNmTbNmzZrBBHcVjo6tbNmyZtmyZT1k3rZtm7lt2zafx0+ZMkU/I3X8/fffb54+fdo8ffq0U2MLanwLFiwwK1asaFasWNFnMLd69erm1q1bza1btwZzeX+I2Ofy5ZdfTvH71bx5c7N58+bmyZMng72FBHkFQQgvtjuXvgK8al4+Kao3r5rLT+684cOHx1Qz8J9++gnwzNpVvP766wBRGeAF6NKlC+DqUgeunrW+qFevHnXr1gXgu+++A+DIkSM0b94cgEWLFjklqt+odgxdu3bVWbCK9OnTM3ToUAA6deoUlTlJ4UB9LvPkyWPrdcMSvRo5cqRHNbVSLO6zREk5fPhwTCmV1KhRowbgWJGgbagEs4ceegiwgriqVKJq1ape1dO5cuVi+PDhAKxcuRKwvtAqxT0a2LhxI4CHclEp/m+++aaHMhXsRVwkQRAcw3YLxtfyIyNHjkx2+lmhrBU1tRvL1svnn3/utU0VoEWra6RQ/VDeeOMNAP7zn/+wePFiAPr166fLG9xNaTW1q8aY1A2JNO7FqgUKFABgyZIlAD47EQr2IRaMIAiOYbsFEx8fr60Q95UbU2L48OE6S1Jl8iYmJvpcoC3amT59ul68yx3V2iFWUMHOuLg43eN1xIgRuvH13LlzAavQUzXAdrdcoslSUxYYoNtmFC1aFLAagKnCTvc2Bqrv8owZM3S3QUW2bNlo06YN4OrLLCRDcvPXpg3z8Sp3pXv37qnmuaifhIQEMyEhwd+cF7/n450Yny9q1arllV9RsGBBMzEx0UxMTLTjFmEd2+TJk83ChQubhQsX9pk74usnd+7c5vbt283t27c7NTa/x/fdd9+ZcXFxZlxcnGkYhlmvXj2zXr16Zps2bcw2bdqYFSpU8Htc7j/58+c38+fPb3700UdOjM92UsuD2bJli7lly5ZQbiF5MIIghBdHp6lVoHbEiBG6D0yzZs288l4SEhL0/lhco3rHjh00atQIwGffl7Zt28ZsoVzr1q1175cmTZroWh73RuamabWQveuuuwCr851yRSLNnDlztHzgWuMpVFRuUEprKglhXFVAKZtYaZcZCOvXr+fAgQNe29WY27VrF26RbOXf//43YCUOqqZFqhnRihUruHTpEmAVOYKrY380kFKSIECOHDkoW7YsAE2bNuWZZ54J6Pqx+uIIF+IiCYLgGLFfhx4FfP311z63v/DCCwAeS7bEMsWKFWPixImRFiMgevfuzfz58wFrxcPatWsD0LhxYwBq1apFkSJFIiZfpFFtNZya5RQLRhAExxALJgTUAupJF6dSFotqaiREjsqVK+vm7YI3Kh/IqbylsKzsGGbCtjrgjh07AChTpozH9lq1agHw/fffh3L55AjLyo4RIipXdrSRiD27ixcv6qpytaZTy5Yttatow5LFsrKjIAjhRSyYEDh+/DgA//jHP3Tf3UKFCunpWoeCh2LBWKTl8Tk6NtXQPX369KRLl86uy/ocmyiY2CMqPqQOIc/OIs2MTVwkQRAcIzULRhAEIWjEghEEwTFEwQiC4BiiYARBcAxRMIIgOIYoGEEQHEMUjCAIjvH/AednpxFLY2k2AAAAAElFTkSuQmCC\n",
       "text/plain": [
        "<Figure size 288x288 with 20 Axes>"
       ]
@@ -97,7 +196,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 288x288 with 20 Axes>"
       ]
@@ -306,29 +405,38 @@
     "**NOTE** FedAvg is a particular case of FedProx with $\\mu=0$. So, we just need to implement the code for FedProx, which we will be used also for FedAvg by setting the parameter *mu=0*"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### EXERCISE\n",
+    "Complete the model aggregation function"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
     "def average_models(model, clients_models_hist:list , weights:list):\n",
-    "\n",
-    "\n",
     "    \"\"\"Creates the new model of a given iteration with the models of the other\n",
-    "    clients\"\"\"\n",
+    "    clients\n",
+    "    -model is the current global model\n",
+    "    - clients_models_hist is the list of each client's updated local model\n",
+    "    - weights is the list of each client's weight\"\"\"\n",
     "    \n",
-    "    new_model=deepcopy(model)\n",
-    "    set_to_zero_model_weights(new_model)\n",
-    "\n",
-    "    for k,client_hist in enumerate(clients_models_hist):\n",
+    "    ###SET MODEL'S PARAMETERS TO 0\n",
+    "    \n",
+    "    \n",
+    "    for k, client_hist in enumerate(clients_models_hist):\n",
     "        \n",
-    "        for idx, layer_weights in enumerate(new_model.parameters()):\n",
+    "        for idx, layer_weights in enumerate(model.parameters()):\n",
     "\n",
     "            contribution=client_hist[idx].data*weights[k]\n",
     "            layer_weights.data.add_(contribution)\n",
     "            \n",
-    "    return new_model"
+    "    ###RETURN THE NEW GLOBAL MODEL"
    ]
   },
   {
@@ -456,17 +564,17 @@
      "output_type": "stream",
      "text": [
       "Clients' weights: [0.3333333333333333, 0.3333333333333333, 0.3333333333333333]\n",
-      "====> i: 0 Loss: 2.3077298005421953 Server Test Accuracy: 7.333333333333333\n",
-      "====> i: 1 Loss: 2.2404345671335855 Server Test Accuracy: 19.666666666666664\n",
-      "====> i: 2 Loss: 1.8850175539652505 Server Test Accuracy: 45.33333333333333\n",
-      "====> i: 3 Loss: 1.0085218747456868 Server Test Accuracy: 75.33333333333333\n",
-      "====> i: 4 Loss: 0.6295895576477051 Server Test Accuracy: 79.0\n",
-      "====> i: 5 Loss: 0.5280802349249522 Server Test Accuracy: 79.33333333333333\n",
-      "====> i: 6 Loss: 0.2651289403438568 Server Test Accuracy: 90.33333333333333\n",
-      "====> i: 7 Loss: 0.2068410962820053 Server Test Accuracy: 90.33333333333333\n",
-      "====> i: 8 Loss: 0.18058088421821591 Server Test Accuracy: 91.0\n",
-      "====> i: 9 Loss: 0.15036222835381824 Server Test Accuracy: 90.33333333333333\n",
-      "====> i: 10 Loss: 0.15352871268987656 Server Test Accuracy: 93.0\n"
+      "====> i: 0 Loss: 2.300051132837931 Server Test Accuracy: 9.333333333333332\n",
+      "====> i: 1 Loss: 2.115779399871826 Server Test Accuracy: 43.33333333333333\n",
+      "====> i: 2 Loss: 1.4170910914738972 Server Test Accuracy: 66.33333333333333\n",
+      "====> i: 3 Loss: 0.7694819768269856 Server Test Accuracy: 77.0\n",
+      "====> i: 4 Loss: 0.564457356929779 Server Test Accuracy: 80.33333333333333\n",
+      "====> i: 5 Loss: 0.41685162981351215 Server Test Accuracy: 83.66666666666666\n",
+      "====> i: 6 Loss: 0.2300022691488266 Server Test Accuracy: 91.66666666666666\n",
+      "====> i: 7 Loss: 0.197920819123586 Server Test Accuracy: 89.0\n",
+      "====> i: 8 Loss: 0.13389848669370014 Server Test Accuracy: 91.66666666666666\n",
+      "====> i: 9 Loss: 0.1120482012629509 Server Test Accuracy: 92.33333333333333\n",
+      "====> i: 10 Loss: 0.07799022644758224 Server Test Accuracy: 91.66666666666666\n"
      ]
     }
    ],
@@ -487,7 +595,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -549,17 +657,17 @@
      "output_type": "stream",
      "text": [
       "Clients' weights: [0.3333333333333333, 0.3333333333333333, 0.3333333333333333]\n",
-      "====> i: 0 Loss: 2.3077298005421953 Server Test Accuracy: 7.333333333333333\n",
-      "====> i: 1 Loss: 2.2553473313649492 Server Test Accuracy: 25.666666666666664\n",
-      "====> i: 2 Loss: 2.0728208223978677 Server Test Accuracy: 48.0\n",
-      "====> i: 3 Loss: 1.344037135442098 Server Test Accuracy: 66.33333333333333\n",
-      "====> i: 4 Loss: 0.8007276654243468 Server Test Accuracy: 73.33333333333333\n",
-      "====> i: 5 Loss: 0.6816384394963582 Server Test Accuracy: 74.33333333333333\n",
-      "====> i: 6 Loss: 0.4158744712670644 Server Test Accuracy: 87.0\n",
-      "====> i: 7 Loss: 0.3552906016508738 Server Test Accuracy: 90.33333333333333\n",
-      "====> i: 8 Loss: 0.23262095948060352 Server Test Accuracy: 87.33333333333333\n",
-      "====> i: 9 Loss: 0.16984646519025165 Server Test Accuracy: 92.0\n",
-      "====> i: 10 Loss: 0.15044508377710977 Server Test Accuracy: 91.0\n"
+      "====> i: 0 Loss: 2.3000512917836504 Server Test Accuracy: 9.333333333333332\n",
+      "====> i: 1 Loss: 2.15874703725179 Server Test Accuracy: 29.666666666666664\n",
+      "====> i: 2 Loss: 1.566962440808614 Server Test Accuracy: 60.33333333333333\n",
+      "====> i: 3 Loss: 1.2437344789505005 Server Test Accuracy: 65.0\n",
+      "====> i: 4 Loss: 0.5378359158833821 Server Test Accuracy: 83.33333333333333\n",
+      "====> i: 5 Loss: 0.43191210428873694 Server Test Accuracy: 86.33333333333333\n",
+      "====> i: 6 Loss: 0.35815815130869544 Server Test Accuracy: 87.33333333333333\n",
+      "====> i: 7 Loss: 0.2918719152609507 Server Test Accuracy: 88.33333333333333\n",
+      "====> i: 8 Loss: 0.2190828174352646 Server Test Accuracy: 89.33333333333333\n",
+      "====> i: 9 Loss: 0.17422165473302204 Server Test Accuracy: 88.66666666666666\n",
+      "====> i: 10 Loss: 0.14906058212121326 Server Test Accuracy: 88.66666666666666\n"
      ]
     }
    ],
@@ -580,7 +688,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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YV/b/vQ/+Pg6em28k24ojHe+31Qrr/gz/ngOVR+HSF+CKl7uX3Nvyj4SFf4Q7MmD6LbD3A3h6Kjw5EZ6aDJ89BG6ecO7DcMdOuOELmPUzpyZ3wOhdN+MxefJk1R0VFWVq1++nq72/D1MLVsxR45ePV8t3L1c2m61b+9FOlpmZaXYISimljh07pi677DKVmJiokpOT1aJFi9T+/fvVrFmzVFhYmPL29lYxMTFqzZo133lte+8B2KL60We7P5zn3pxjpfr4PTRUKvXFn5V6dJhSvwtQasX3lDqafvrXlB5U6svHlHpmjvGa3wUYv3/5mLHuuPwdSv1zprH+reuVqi1xfPy1JUqt/Z1SL12s1PqnlarIcdiuu/PZNm1O1ilTpqjuTopQVVlO/lOLiGw5wM/GzGNr034WJizkwRkP4uvh66RIXVtWVhZjx441O4xeae89iMhWpdQUM+Jp77PtqufZ4RoqIP0Z2PgvaKyCUQthzj0Q280O4oojkHm8rdv+bzE01WjvzngD/MKNNvQxix3+FpytO5/tft0Gf6rAoBDkto8o+MdC/p31OY+Ov4p3jn7CwcqD/G3e30gITDA7RE3TeqK+HNL/CRv/DU3VRnv4nLshekLnr21PcALMvN14VOZ+OwQx43UYfyWc9wfwCXboW+iPBlSCBwgIDEFu/Zjcp87j3p2vMmzKL1hW9zFXfnglj817jBnRM8wOUdO0rqorgw3/MG4gaq41Okrn3G1caTtKUBxMvxmm30x1fSP+Pl59UlvH2mrjWEUDPWkj8XATYoN73yox4BI8gH9QKHLrGo49dS5XbnmMsGl/5JnG9/n71r/rBK9pA0V9OTw716j1Mu57MPsXMDTZKYeqbWrhjx9l8crGHKIDvVk4LorFaZFMjAvGYnFcsm9usfFNdikf7yrgk8wiKuutPdrPyIghrL1rbq/jGZAJHmBIUBhyyxoKnj6Pc9J/xfq0H/BB+RdUNFYQ7O36X700bUCz2eCdG6C2CK7/L8RPddqh1u0v4b53dpFf1cCVZ8ZRUtPEy+lHWfbNYYYGeHH+uCjOHxfJlIQQ3HqQ7ButrXx9oJSPdhewNrOImsYW/L3cOSd5KNOTQvF06/5gRX9vx6TmAZvgAfyCI5Bb11D81LlcvO9tVseEsrFwIwsTFpodmqZpp/P1Y3BwrTHu3EnJvareysMfZvLW1jySwv1Y+dMZTIo3Lv5qGq38b28xH+0q4LVNOby4/ghhQ7xYOG4oi8ZFcebwENxPk5gbra2s21/CR7sK+CyrmNqmFgK83TkvJZJFqZHMHBGGl7ubU95XdwzoBA/gGzSU8Fv+i+Ufc/C1QXp+uk7wmtafHf7SuGt03KUw5XqnHGJtZhG/fncXZXXN3HJWErfNH4m3x7cJ19/bg4smxHDRhBjqmlr4fF8xH+8qZOXWY7ycnkOonyfn2pP1tMRQPNws1De38MU+I6n/b28x9c2tBPt6sCQtivNTo5ieGIqne/+6tWjAJ3gAn+BICmMWMbXhA9YfW292OFoPFBYWcuedd7J582a8vLxISEjggQce4I477qC6uho3Nzd+/etfc8UVV5gd6oDlzHO8IbuMrUfLWZAcyaihQzruxKwphLd/BKEjjEJeDu7sLK9r5oFVe1i1M58xkf4su+4MxsUEnvY1fl7uLEmLZklaNA3NrazbX8wHGfms2p3Bm5n/xW9IKaGBjRSV+dHUEE6gWwwXTRjN4tRopiWe/krfbC6R4AH8x57F9A1v8Xl9AbnVucQFdON2Zc1Uyl7K9tprr+X1118HYMeOHVRVVfHSSy8xcuRI8vPzmTx5Mueddx5BQUEmRzzwOPsc//HjLDLyqvjrJ/tJDPdj0bgozk+NJDkq4Ntk39oCb19vjJa5dhV4DXHo+/toVyH3v7+b6kYrPztnFD+dl9TpFXWLrYW8mjyyq7I5VHnoxM/DtsNYhjXiCyigTHniFt6ML2AFvmgcQs6BRD4pTiIpKInEwESSgpKI9IvEIv0n4btMgk+YOB/L/4we6w0FG3SCH0A6K2ULEB0dTUREBCUlJTrB94Azz3F1o5Xdx6q4ZvowRg315+PdBfzzi4M89flBhoX6cv64KBalRpK69wnk6DdGMa8Ix90wVVzTyP3v7WHNnkLSYgN55dKpjIkMOGkba6uVnJocsiuzT0rmR6qOYLV9O9Ilyi+KxKBEzog840TiTgxKxN/Dn/LGcg5VHTL2UZnNoapDfJn3Je8efPfE633cfU4k+8TARMaGjOWMyDNMK5DoMgney8efVssIwlpqSC9I5/LRl5sd0sDz8b1QuMux+4xMhfMfPe0mXSllu2nTJpqbm0lKcnLtjr5gwnl25jnedKgcm4KF4yKZkRTGD6cNo6y2ibWZRXy0u5D/fHWIfV+9zQuej7M9/CJU8HlMsKleD09USvHu9mM8uDqTBmsrv1w4hmtmRJNXm8PHh785kYSzK7PJqc6hRbUAIAgxQ2JICkpiVswskgKNq/DhgcPx8/Dr8HihPqGE+oRyRuQZJy2vbKw0jlOVfSL5p+ensyp7FQD+Hv7Mi5vHuQnnMj16Ol5uXr16393hMgkeoDpyOjPr3+Hz/I202lpxs5jfi631XkFBAVdffTXLly/HYuk/X39dSW/O8YZDZXi6W06MUAEIHeLF0jPjWXpmPFUF2Xgvu5GjJHF1/veo/ed6ogK9WTgukvPGhRMX4t7tpvjyukYeWvMN2wr2ER1dxZTYej6sOMozr+eemOrTIhbi/eNJDEzk7PizSQxKJDEwkeGBw/Fx9+neAU8jyDuISd6TmDR00knLq5ur2V60nbVH1/K/3P+x+tBq/Dz8mBs7l3OHncvMmJl4u3s7LI72uFSCDxw7n+lfv8r71mr2lu8lJcyc8rcDVidX2s5yulK21dXVLF68mIcffphp06b1cWROYsJ5duY53pBdxqT4oJNGqZzQ0kzgBz8BCwy74S2+8Y3ns6wiVu86yuv7VvBm8Tos7rXdPiYAFvCJgRpxp7QpnlHBozh/+PkkBSaRGJTIsIBhfXq1fKoAzwDmxs1lbtxcrK1WNhVuYu3RtXyW8xkfHf4IH3cf5sTOYcGwBcyOme2UelouleCHTzwL/7WtgNEOrxP8wDB//nzuu+8+nnvuOX7yk58ARinb+vp6HnroIa655houu+wyk6Mc2Jx1jivrm8kqrObOszuYqOKT3xgTW1y+AkKTcLfWUe6xhmyvl3APr2CE/ySiPLpfb8YiwoxhSUyNSybeP77fTwLk4ebBzJiZzIyZyW+m/YYtRVtYe2Qtn+Z8yn+P/BdvN29mxcxiwbAFzI2be9qmou5wqQTv6e1LpccYEporSC9I58epPzY7JK0LRIR3332XO++8k0cffRRvb28SEhKYNm0aX375JWVlZbz44osAvPjii9/pHNQ656xzvPFwOUrB9KTQ767c8y5s+jdMu5maEWfxWsazvJT5ElVNVcyKmcWNaTcyIWLw/Vu6W9yZFjWNaVHTuG/qfWwr3sbao2v59OinfJrzKZ4WT86KP4u/zPlLr2vmuFSCB6iJms7sqjd4o2gbjS2NTm/j0hwjOjqaN9988zvLf/vb35oQjWtyxjnekF2Gt4eF8XGnjDUvPQjv30ZV7GRejYhhxcrzqGmuYW7sXG4afxPjwsb1+JiuxM3ixhmRZ3BG5Bnce+a97CzZySdHPqGptckhBdE6TfAiEge8BEQCNuBZpdQTp2wjwBPAIqAeuE4pta3X0fVAYPJ8pn/+IitsVrYVb9PFxzTNidIPlTFlWMjJt+VbG6h862pWBPrxqk8dtbv+zfy4+dw4/kaSQ51TTMwVWMTCxIiJTIyY6LB9duUKvgX4uVJqm4j4A1tFZK1SKrPNNucDI+2PqcC/7D/7XOL4uYR/pHBTQnpBuk7wmuYkZbVN7C2s4e7zvp3wuqKxgpfeu4pXvaupt3iyIGYmN6bdyOiQ0SZGOnh1muCVUgVAgf33GhHJAmKAtgn+IuAl+3RS6SISJCJR9tf2KU8vb/K9UhjbVEp6fjp0cyIYTdO6ZuPhcgCmJYZS2VjJst3LeD3rZRpbm1noN4yfLHiCkcEjTY5ycOtWG7yIJAATgY2nrIoBcts8z7Mv6/MED1AbPZ15FSt4unyvLh+saU6yIbsMX0830mIDuePzW/nm2NecX9fADb6JJF66GvR9KKbr8h0NIjIEWAncqZSqPnV1Oy/5zkQmInKDiGwRkS0lJSXdi7QbgpPPZlpDIwrFxsJT/xZpmuYIGw6VcUZCCFXN5XyT/w0/ahIerRcSv/+STu79RJcSvIh4YCT3V5RS77SzSR7QtvhLLJB/6kZKqWeVUlOUUlPCw8N7Em+XJI2fRUKjBR/lZjTTaFoXiMjPRGSPiOwWkddExFtEhovIRhE5ICJviIin2XH2B8U1jRwsrmV6UigfH/4Ym7KxpDQfLl0G/kPNDk+z6zTB20fIPA9kKaUe72CzVcA1YpgGVJnR/n6ch6cXR3xSmdDQQnqBTvADQWFhIUuXLiUpKYnk5GQWLVrEunXrmDx5MhMmTCAlJYVnnnnGaccXkRjgdmCKUmoc4AYsBf4E/E0pNRKoAH7ktCCczJHnOP2Q0f4+PTGUDw68x9hmK4lpV0PCLGe+Ba2butIGPxO4GtglIjvsy+4D4gGUUs8AH2EMkTyIMUzy/xwfavfURc/grJLneaRWdPngfu50pWzXr1+Pl5cXtbW1jBs3jgsvvJDo6OhO9thj7oCPiFgBX4w+pPnAD+zrlwMPYIwSG1AcfY43ZJfh7+WOr18ZmZX7ubumFi75aV+8Fa0bujKK5mvab2Nvu40CbnFUUI4QnHIOUWueBnT54P6uK6Vsm5qasNlsTotBKXVMRP4K5AANwCfAVqBSKXsZwm8HD3yHiNwA3AAQHx/vtDh7ytHnOP1QGWcOD2HN4dVYlOL88CkQpkfM9DcudyfrcSPSplO3yosQm4cuH9xFf9r0J/aW73XoPseEjOGXZ/7ytNucrpRtbm4uixcv5uDBg/zlL39x2tW7iARjDPcdDlQCb2Hc33Gq7wweAKN/CXgWYMqUKe1uc5wZ59mR57iwqpHDpXX84Mw4Vu5/m6mNjYSfc1uv4tecw2Vrr3p4eJDtk8aU+iY2FW6i1dZqdkhaD8TFxZGRkcHBgwdZvnw5RUVFzjrUOcBhpVSJUsoKvAPMAIJE5PiFULuDBwa67p7jDYdKAQgJOcax5iqWEABJ8/siVK2bXPYKHqAhZgbzC//FJ0MsunxwF3R2pe0spytle1x0dDQpKSl89dVXXHrppc4IIweYJiK+GE00ZwNbgM+BS4HXgWuB93t7IDPOsyPP8YbsMgJ9PMgseBNvm42zJ/zE4XOrao7hslfwAKHjzmZqQyNgtMNr/dP8+fNpamriueeeO7Fs8+bNrFu3joaGBgAqKir45ptvGD3aObe8K6U2Am8D24BdGP83ngV+CdwlIgeBUIwRZQOOI8+xMf49gP/mf81ZTa34TbrGqbFrPefSCX5E6lTcWv2Ia/XSwyX7seOlbNeuXUtSUhIpKSk88MAD7N+/n6lTpzJ+/Hjmzp3LL37xC1JTU50Wh1Lqd0qpMUqpcUqpq5VSTUqpQ0qpM5VSI5RSlymlmpwWgBM56hznVdSTW97AsJBtVNHKkpg54OmY2uWa47l0E42HuzsHfccztTabVUXbdfngfqyjUrbHJ6fQes8R5/j4+PeS6vcIbm1l+sxfOSw+zfFc+goe7O3wDRU025rZVmxKBWNNcxkbssuI9K1jvTWfhZ6ReIQMNzsk7TRcPsGHp57D5MYm3LDoZhpN66X0Q2XMG/ohTSIsHj9gb+odNFw+wY9ImUK9LYCRLV66Lk0HjPvUBqaBFPtAivVUSilabIr8yjoKLduIUxbSUq40OyytEy6f4D3c3TjoN5EZNZXstZcP1r7l7e1NWVnZgEw+SinKysrw9u7//SqucJ6rm2Gq50a2eSiWRM5ELC6fPgY8l+5kPa4pdgbzj65nWXAkGws3sjBhodkh9RuxsbHk5eXhzPLNzuTt7U1sbKzZYXTKFc7z6oONjA5eyx4RFp95l9khaV0wKBJ8eOo5jNr/CL54kp6frhN8Gx4eHgwfrjvKnAawoFQAACAASURBVG2gn2elFIdeXYcKryTVM4phISPMDknrgkHxHWvk2AmUqWCSmz10R6um9cDh0jqmtq5kr5cni8fqtveBYlAkeA93N7KHTGJWTSnHao+RW53b+Ys0TTth677D2AL24AYsHO2UUhGaEwyKBA/QHDuT+Q1GB6suW6Bp3WPZsYK1/l5MDxtPqE+o2eFoXTRoEnxE2gISrC2EiK9uptG0blCtVobUvkeBuztLdPPMgDJoEvyo0SkUqDDSGi1sLNioywdrWhcVblzJBj8rXnhwVtxZZoejdcOgSfDu7m4cGjKRudWFVDdXO3zCBU1zVS2bn+G/fn7MiJ6Pr4ev2eFo3TBoEjxAc/xs5tVXArodXtO6JH8H+5v2UusmXD72YrOj0bppUCX4yLQFhNlsxFmCdDu8pnWBSv8X7w3xx4sApkVPMzscrZsGVYIfNWoMOWoo4+ta2W4vH6xpWgdqi6nKfJevfHyYEDofd8uguC/SpQyqBO/uZuGw/yTmVx3T5YM1rTNblvGZtzutFsVVKbp5ZiAaVAkeoCV+FjMbq3AXN91Mo2kdaWmCzf/hjcAoLC0RzEuYZHZEWg8MugQfOX4BvkoxUkJ0+WBN68judyhoLCfLs5kRPnMQPan2gDToEvzoESM5rKIZX9OoywdrWnuUgvR/siosHoDFiYtNDkjrqUGX4N3dLBwJmMQ5VUdRKDYWbjQ7JE3rX3I2oAozWOnnT2v9MBYnjzM7Iq2HBl2CB2iNn8Xkplr83Lx1M42mnSr9X+z3D6VAVRLYOpWhAf1/QhWtfYMywUdNWIA7MFYFk16QPiBn2dG0ztQ0Wrv/osoc2PsBHwybAMrCzKizHR+Y1mcGZYIfnZjIARXHxKpajtUeI68mz+yQNM2hPt9XTOoDn/Cb93ZR29TS9Reu/wetCKuay2ipHc3cEQlOi1FzvkGZ4N3dLBwNmMy5VYcBXbZAcz3ph8qwCLy6MYfz/vYl6/Z3YarA0oOwZRlb0i6g3FqOtWoi0xJ1aeCBbFAmeACVMJvR1npivML54NAHZoejaQ6VmV/N2KgA3v7pDHw83bh22SbufmsnVfWnabb57AFw9+bDkAgsypsEnymE+3v1Wcya4w3aBB8zfgFKCfNbIthevJ195fvMDknTHEIpRWZ+NclRAUyKD+bD22dxy1lJvLP9GAv+to61mUXffdHRDZC1msbpt7L22Ne01IxjRlJU3wevOdSgTfCjE+PZxzDOLSzAy82LN/a9YXZImuYQRdVNlNU1kxIdAICXuxt3nzeG92+ZSYifJz95aQu3v7ad8rpm4wVKwSe/Af8o/hczhlprLY0VE5ium2cGvEGb4N0sQm7gZJJr93D+sHP54NAH1DTXmB2WpvXanvwqAFJiAk9aPi4mkFW3zuKuBaP4eHcBCx5fxwcZ+ag978KxLRyecTOPbHuMYI84WusTmaoT/IA3aBM8GO3wnlg533MEDS0NrMpeZXZImtZre/KrARgbFfCddZ7uFm4/eySrb5tFTLAPd726idL37qMoYgw353+Mm7gxtP5mxkQGEuLn2dehaw42qBN87IRzaFVC+IFdjAsdxxv73tBj4rUBLzO/moRQX4Z4dVzed0xkAO/8dAYvpuzEv7WQi918Kaor4fG5T7DrqJsePeMiBnWCH5MQyzrLGURlv8kVIy7mcNVhNhduNjssTeuVPQVVpEQHdrqde1MlU489z93DxlDrVUZ1zuXc/2YNjVYb05N0gncFnSZ4EVkmIsUisruD9fNEpEpEdtgf9zs+TOdwswiNZ97KEFXL8KxDBHoF8vq+180OS9N6rKrBSm55A8nR322e+Y6vHuMxXwtfSB13n3E3vz7rMg6V1GERmDZcJ3hX0JUpWl4EngJeOs02Xymlljgkoj527rkXsHvLGCIylnHhwp/w6r5XKaorYqjfULND07Ruyyow2t87TfDlh3klcwUrQgK5auxVXJNyNQDnjB1KfmUDgb4ezg5V6wOdXsErpb4EyvsgFlO4u1lQ028nShWTkKOwKRsrD6w0OyxN65HjHawpnST4z//7M/4cHMD8qBncPeXuE8vjQnz16BkX4qg2+OkislNEPhaRlI42EpEbRGSLiGwpKenCrdN9ZNz8pRS4x5C85w3OHDqdt/e/jdXWg0JNmmayPflVhPt7EeHfcQXI3Xve5J7GAyR7hfLo/L/jZnHrwwi1vuSIBL8NGKaUGg/8A3ivow2VUs8qpaYopaaEh4c74NCOIRY3ZMZtjCObqJJIShpK+Dznc7PD0vqYiASJyNsisldEskRkuoiEiMhaETlg/xlsdpynk5lffdqr97zqXG7Z/AdCFfxj0Qp83H36MDqtr/U6wSulqpVStfbfPwI8RCSs15H1scjZ11HrHsTcA18Q7hOpO1sHpyeANUqpMcB4IAu4F/hMKTUS+Mz+vF9qtLZysLiW5HbGvwNUNVVxy8fX0mKz8s8x1xMWGN/HEWp9rdcJXkQixT5ho4icad9nWW/32+c8fJCpN3KOZQfhNSlsLtxMdmW22VFpfUREAoA5wPMASqlmpVQlcBGw3L7ZcuBicyLs3IGiWlpsqt0hks2tzdz5vzvIbSjhiSZfEqfeYUKEWl/ryjDJ14ANwGgRyRORH4nITSJyk32TS4HdIrITeBJYqgbo3UJ+M27EavFmYc4B3MVD16cZXBKBEuAFEdkuIv8RET9gqFKqAMD+M6K9F/eH/qUTJQpOaaJRSnH/+vvZUryV35eUMuXsR8CtKwPotIGuK6NorlRKRSmlPJRSsUqp55VSzyilnrGvf0oplaKUGq+UmqaUWu/8sJ3ELxSZ+EN+KOkMaUxmVfYq6q31Zkel9Q13YBLwL6XURKCObjTH9If+pcyCaoZ4uRMf4nvS8qd2PMWHhz7k9pomFkecASMXmBKf1vcG9Z2s7XGfeQvu2DiruJ46a52uFT945AF5Sqnjs7C/jZHwi0QkCsD+s9ik+Dq1J7+asVH+WCxyYtm7B97l2Yxn+b7vMH5cWgzn/h5ETrMXzZXoBH+qkERIvoC7Wzfi1hzNq1mv6/o0g4BSqhDIFZHR9kVnA5nAKuBa+7JrgfdNCK9TrTZFVkH1Se3v64+t58ENDzIzYhK/3rsJGb8UosabGKXW13SCb4fMuB1/VcuE8iFkVx1ge/F2s0PS+sZtwCsikgFMAB4BHgUWiMgBYIH9eb9ztKyO+ubWE3ew5lTncNe6u0gKSuKvdRY8RGD+b0yOUutruqelPbFTIH4GfyjYxXmtgbyw6xUmDZ1kdlSakymldgBT2ll1dl/H0l3H72A9PkRy7dG11FnreDL5Boa8fDnMugsCY80MUTOBvoLvyMzbibEWMawmmnXHPqO0odTsiDStQ3vyq/FwE0YN9QcgoySDeP94Yr7+B/iGwayfmRyhZgad4Dsy8jwIG8WDrcdQtPLU5lfMjkjTOrQnv4qREf54ultQSpFRmkGaVxgc+Qrm3QveXaguqbkcneA7YrHA9FuZUn2AoIZo3s9eibVV16fR+p8Tk2zb298L6wopbSglLTcDQkfC5OvMDVAzjU7wp5N2BfhFcDvNtFgqeOybfjmAQhvkimtOnmR7Z+lOANLK8+CcB8BNl/4drHSCPx0Pb5h6A5cUbsOz1Z/X975Oo7XV7Kg07STf3sFqDJHMKMnACwujWhSMPNfM0DST6QTfmSk/wt3Dl6vc/Gn12sdjn39tdkSadpLME5NsGx2su0p2kYwnHhFjwV1PnD2Y6QTfGd8QmHg11+RuQ5Qbr2W9QXFNo9lRadoJe/KrGRbqi7+3B9ZWK5llmaTW1UBUmtmhaSbTCb4rpt9MWGsL8z2Hgv8W/vrJLrMj0rQT9rSpAb+vYh/NtmbSaishUif4wU4n+K4IToDki7m6YB/i1sB7Bz48MfelppmputFKTnn9Se3vAOObmnWC13SC77IZtzGppoIkj2C8QtL5/Yd7dI0azXRZp9zBmlGaQbibD0NbbRA5zszQtH5AJ/iuipmEJMzmyooy8DpGet4O1mcPvHlNNNdy6iTbGSUZpCkPJCQRvPzNDE3rB3SC744Zt7Ok9Bh+Fk+8QtL55qAuX6CZa09+NWFDvIgI8KaisYLcmlzSaqshMtXs0LR+QCf47hhxDn5ho7mgSeEekMG2vDyzI9IGucyCbztYd5Uanf+pVUV6BI0G6ATfPRYLzLiNy4pyQFrYU/W1bofXTNPU0sqBopoTJQp2luzEgpDS1AyRuu67phN896VexkivUAJtFqzuRzhapqf008zx7STb9iv4kl2M8grBVyndRKMBOsF3n7sXMvVGJjbU4uOTTcaxKrMj0gaptiUKbMrGrtJdpNrcYchQ8B9qcnRaf6ATfE9Mvo60pmZavCrZclS3w2vmyMyvxs/TjWEhvhyuOkyttZa02io9/l07QSf4nvANIdXHuELaUpRhcjDaYGVMsh2AxSInbnBKKz2qO1i1E3SC76FxkVMQpTham0mrTXe0an3LdmKS7W9vcPJ39yWhuUm3v2sn6ATfQ0PiZ5BkteLluZ/sklqzw9EGmaPl9dQ1t55UoiDVO8L4D62baDQ7neB7Km6qUe/DJ5+duRVmR6MNMsc7WJOjA6i31nOw8iBprRbw9Ifg4SZHp/UXOsH3VOhIUlstWN2srM/Za3Y02iCzJ78ad4swcugQ9pTtwaZspNVUGPVnLPq/tWbQn4SeslgYHzIWgIwSXT5Y61uZ+dWMHOqPl7sbO0uMKfpSi7N184x2Ep3geyExdhZDbDZKG3fT3GIzOxxtEGlbA35XyS6G+UUR1FSrR9BoJ9EJvhcs8VMZ19SEl3c2+4tqzA5HGySKqxsprW0iOSoApRQZpRmkeYUbK/UVvNaGTvC9ETOZtMZmGr0q2JJTZHY02iDRtkRwQV0BpQ2lpLYKWDwgfIzJ0Wn9iU7wveEdQJrPUJTAN7nbzY5GGyQy7bOJjY0OIKPUfoNTdRlEjNGTbGsn0Qm+l1IjpwCwt0x3tGp9Y09+FfEhvgR4e5BRkoGXmxejCvfrCpLad+gE30shw2YTZ7XS2LqLRmur2eFog0DbDtaMkgySA0fgUV+q72DVvkMn+N6KPZO0pmaUT96Jm080zVlqGq0cLasnJToAa6uVrLIs0rzCjJV6BI12Cp3geys0idRWd5rcm/nm8EGzo9FcXFaBMVorJTqQfRX7aLY1k9ZiXzlUT7KtnUwn+N4SYXzIaAA2FuiOVs252pYoOH6DU1p1MYQkgneAmaFp/VCnCV5ElolIsYjs7mC9iMiTInJQRDJEZJLjw+zfRsfNwstmI6dqh9mhaC7OmGTbkwh/L3aV7iLCJ4KhRXt1+7vWrq5cwb8ILDzN+vOBkfbHDcC/eh/WwOIRP53k5mas7KW2qaXzF2haD2XmV5McHYiIUQM+LXQsUnFU3+CktavTBK+U+hIoP80mFwEvKUM6ECQiUY4KcECInkRqk5VGrzJ25JaaHY3moppbbBworiE5KoDyxnJya3JJ9QgxVkbpIZLadzmiDT4GyG3zPM++bPDwGsI4r6G0WhSfH9bNNJpz7C+qwdpqTLK9u9RoMU2z2msg6SYarR2OSPDSzrJ2pzgSkRtEZIuIbCkpKXHAofuPiVHGDU/bCnVHq+Ycx+9gTbF3sLqJG8lVxeAXAf6RJken9UeOSPB5QFyb57FAfnsbKqWeVUpNUUpNCQ8Pd8Ch+4+h8bOJaGmhvG6b2aFovSAibiKyXUQ+sD8fLiIbReSAiLwhIqbVAsjMr8bX042EUD8ySjIYGTwS36I9evy71iFHJPhVwDX20TTTgCqlVIED9jugSLxxw1Oj21Eq65vNDkfruTuArDbP/wT8TSk1EqgAfmRKVBhDJMdGBYAodpfuJi00BUr26g5WrUNdGSb5GrABGC0ieSLyIxG5SURusm/yEXAIOAg8B9zstGj7s+DhpLS6U+/ZwDeHj5gdjdYDIhILLAb+Y38uwHzgbfsmy4GLzYjNmGS7hpToAA5XHabWWkuaZyjYWnT7u9Yh9842UEpd2cl6BdzisIgGKhFSg0dB6xG+OLKVxSmjzI5I676/A/cA/vbnoUClUur42NcOBxCIyA0Yw4SJj493eGA55fXUNrWQEh1ARslWAFKb7WHpETRaB/SdrA6UFj8HN6XYV7LZ7FC0bhKRJUCxUmpr28XtbNruAAJn9y8drwGfHBVIRmkG/p7+JJTngecQPcm21iGd4B3IJ34Go5qtVDXp0sED0EzgQhE5AryO0TTzd4z7Oo5/0+1wAIGz7cmvwt0ijIocYtzgFJaGpWiXUX9GT7KtdUB/MhwpeiJpTVZqPIopqKozOxqtG5RSv1JKxSqlEoClwP+UUlcBnwOX2je7FnjfjPgyC6oZETGEVtXEwcqDpIaNg8LdegSNdlo6wTuSpy9jPMKxutn49IC+incRvwTuEpGDGG3yz5sRhFEDPpA9ZXuwKZsxB6u1To+g0U5LJ3gHmxBl1Fr7Jk+3ww9USqkvlFJL7L8fUkqdqZQaoZS6TCnV1NfxFNc0UlLTdFIFydRm+1BcPYJGOw2d4B0safh8AlpbyStLNzsUzUVktplkO6Mkg2EBwwgqzQaLO0SMNTk6rT/TCd7BJH4qaU3NVNqyMUaQalrvHB9BMzbKn12lu0gLS4OCDAgfC+5eJken9Wc6wTtaYBxjW9yp9qhjv4vV29HMkZlfTVyID3WtpZQ2lJIWlgqFGbqDVeuUTvCOJsIY/ySUwJoDuh1e6709+VWkRAWSUZIBQKpvNNSV6PZ3rVM6wTvBGQlzANiRt97kSLSBrraphSP2SbYzSjPwcvNiVEO9sVKPoNE6oRO8EwQnziOx2UpRjS4drPXOnmPGHKwpMUYHa0poCh7F9tkzI/Uk29rp6QTvDFHjSW2yUmrJp7XVZnY02gC2PbcSgJSYIWSVZZEalmp0sAYngHegucFp/Z5O8M7g4c0ISygNbq2k5+43OxptANueU0FCqC8lTYdptjWTFp4Ghbt084zWJTrBO8nYMKPC32fZG0yORBuolFJsz6lkQlzQiRuc0gKGQ8VhPYJG6xKd4J1kwphz8bHZ2J//ldmhaANUQVUjxTVNTIwPJqMkgwifCCKri42VkbpEsNY5neCdxGvYDMY1NVPYpJtotJ7ZnmO0v0+MDzJucApPM8a/gx4iqXWJTvDOEhjDaKs7Je5V1DbVmx2NNgDtyK3A093C0KAWcmtyv21/9wvXk2xrXaITvBMl+iRgE/j0kJ6IW+u+7TmVpMYEsrdiD8C3I2gi00Dam4tE006mE7wTjY+bBcD67HUmR6INNNZWG7uOVTExLoiM0gzcxI3koBFQkqWbZ7Qu0wneiUaMPZcYawuHSzeZHYo2wOwtqKGpxcaE+CAySjIYFTwK34qjxiTbegSN1kU6wTuRJXo845qsFNhyzQ5FG2C251YAMD4ukN2lu43294LjHax6BI3WNTrBO5O7JwkEU+VmJa+6wOxotAFke04lEf5e1Ks8aq21Rvt7YQZ4+EFIotnhaQOETvBOlhRotJd+sl8XHtO6bkeucYPT+nzjczM1aqq9g1VPsq11nf6kONn4EQvwUIpthz8zOxRtgKioa+ZwaR0T44P56thXjAoeRaRPBBTt1iUKtG7RCd7JopLnMbapmaM1e8wORRsgdtgLjI2Odmd70XbmxM4xyhM01+oOVq1bdIJ3MgmIYkSzO8ekAqvNanY42gCwPbcSi0CdJZMW1cLsmNlQYNSi0UMkte7QCb4PxHnEYbUodhfvMzsUbQDYnlPB6MgANhWtx9/T/9s7WC3uEJFsdnjaAKITfB8YFTENgM+z1pocidbf2WzK3sEawNfHvmZm9EzcLe7GCJrwMXqSba1bdILvA8kpCwltaWVP/jdmh6L1c4dK66hpbCEyvJzShlJmx842VhwvUaBp3aATfB8IGzGFcU1WjjQdNTsUrZ/bnmPc4FTntgtBmBk9E2oKoa5Yt79r3aYTfF9w8yC2NYhit0YqGyvNjkbrx7bnVuLv7c6eio2MCxtHqE+o0f4OegSN1m06wfeRWN8xAGzM3WhyJFp/tiOnknFxbuwq3WWMngE9gkbrMZ3g+8iYYWdjUYr1e9eYHYrWT9U3t7C3sJqQsMMo1Lft74UZEDRMT7KtdZtO8H0kKW0BI5qt7C3PMDsUrZ/KyKvCpqDObTch3iEkh9qHRBZk6OYZrUd0gu8jwRExJDW7ccRWgk3ZzA5H64eMO1ht7K/ewqyYWVjEAo3Vxl2suoKk1gM6wfehSGKotyje2b/S7FC0fmh7TgUxQ4upsVZ/2zyT+b7xM+5M8wLTBiyd4PtQavBspjQ08mD6Q/z6q/uot+q5WjWDUortOZWEhB/CTdyYET0DWq3w5Z8heiIMn2N2iNoA1KUELyILRWSfiBwUkXvbWX+diJSIyA7748eOD3XgS5hxDbfn+3FTRRWrs1ez9N0L2FeuyxdoUFDVSHFNE/Xuu5kQMYEAzwDY8QpU5sC8+/QcrFqPdJrgRcQNeBo4H0gGrhSR9gpivKGUmmB//MfBcbqEkcMTaP2/TzlWfT1/KGimpqaAq1ZfxlubHkcpZXZ4mom251Qi7lUUNx0yhke2NMGXf4WYKTBygdnhaQNUV67gzwQOKqUOKaWagdeBi5wbluuaMjyM2++4lxf9/83Uo7MZ32jloawX+OUr86gt0iWFB6vtORV4BxwAMNrft6+Aqlw4S1+9az3XlQQfA7SdVDTPvuxU3xeRDBF5W0Ti2tuRiNwgIltEZEtJSUkPwnUNkYHevHLjbFpTb2bj4Qc5r34Yn7SUcfnqS9mz6iaoKzU7RK2P7citJCg0m6G+QxnpFwdfPgZx0yBpvtmhaQNYVxJ8e5cPp7YnrAYSlFJpwKfA8vZ2pJR6Vik1RSk1JTw8vHuRuhhvDzf+fGka91x0Ju/l3kxM5fU0evhydfnXvPKfqah1f4bmOrPDHDREJE5EPheRLBHZIyJ32JeHiMhaETlg/xns6GM3t9jYdayMRo+9zI6djWx/CWry9dW71mtdSfB5QNsr8lggv+0GSqkypVST/elzwGTHhOfaRIRrpifw8o+nUliTSsmRXzNmSBqPBvly555/U/WPSbD1RWhtMTvUwaAF+LlSaiwwDbjF3td0L/CZUmok8Jn9uUPtLaymxfMQLaqBOZHT4KvHYNgsPXJG67WuJPjNwEgRGS4insBSYFXbDUQkqs3TC4Esx4Xo+qYlhrLqtlkkhESwfssPmBp4HV8OGcLloT7s/ORu+NcMyPoAdEes0yilCpRS2+y/12B8hmMw+puOfyNdDlzs6GPvyK3Efcg+PCweTM3fC7VFcNav9NW71mudJnilVAtwK/BfjA/9m0qpPSLykIhcaN/sdvvX2p3A7cB1zgrYVcUE+fDWTdO5ZGIsn6aPYSy/Rg0ZynUx0bzg0Yztjavguflw8FOd6J1MRBKAicBGYKhSqgCMPwJARAev6XH/0vacSrwC9jMlfCK+6/8Bw+dCwqxevQdNgy6Og1dKfaSUGqWUSlJK/cG+7H6l1Cr7779SSqUopcYrpc5SSu11ZtCuytvDjccvH89vlySzce8QWnPv5Iyhc3jcu5WbUuewtakU9fL3YdlCOPyV2eG6JBEZAqwE7lRKVXf1db3pX9qSdxDlUcTsVgvUlRht75rmAPpO1n5GRPjRrOG8dP2ZlNe4sWHDYi5LuJ3dzWVcFwDfHzOJtxpyqX/pAlh+AeTo8sOOIiIeGMn9FaXUO/bFRcebIO0/ix15zIq6ZgpbdgAwZ+//jFEz8dMceQhtENMJvp+aOSKMVbfOIjbYjxfWRHNZ2LP8durvsPiG8pC/G+ckJvHn+oPkvLQIXr4U8rebHfKAJiICPA9kKaUeb7NqFXCt/fdrgfcdeVyj/X0v0ZYhDKspNe5a1TQH0Qm+H4sL8eWdn85gSVo0T3x2lCffD+GK6L/xwrkvMiv+bF7z82JxXDQ31e9h3YqFtL72A9A3S/XUTOBqYH6bkhuLgEeBBSJyAFhgf+4wm48W4u6bzbyachh5LsSd4cjda4Ocu9kBaKfn4+nGk0sn8P1JMTz2yX7ufjuDpHA/7lrwM34++Re8k72St/a+wa1e7sTU72DpKwu5JHYegWf9FsJHmR3+gKGU+pr27/kAONtZx/3m2CZwa2FOTSVc9CtnHUYbpPQV/AAgIswbHcGqW2fyzA8nYRHhlle38X/P72O01/dYc+kn/HXuX4mMmsRjoUGcXb+d+99YSNbbP4SybLPD1zpgsyly6zbgbVNMiZsHMZPMDklzMTrBDyAiwsJxUay5cw6PXz6e2qYWrn9xC1c+u4WA1im8uOhlVl64kguTLmRNQACX1+3k2rfP56tXL0Lpzth+J7ukBi+fHUxraMBLj5zRnEAn+AHIzSJ8b1Isn/18Ln+4ZBzHKhq48rl0fvifjdTVhHP/7Ef4dOmX3J16EwV+wdxsPcQVa67h0+dnYdv9DthazX4LGvB51gZqPZo5wy8JovSMTZrj6QQ/gHm4Wbhq6jC+uHsev1k8lqyCai7553p+vHwLx8rgmkm38OGVX/PQmb+mbkg4P3Ov4nsbfsUHz0ygZcPT0FRj9lsY1HL3/wuA+bN127vmHDrBuwBvDzd+PDuRL+85i1+cO4qNh8tY9ORX3Pbado6WNXHJ2KW8v/QL/jTrj0hgHL/ygwv3/IOVz0zA+slvoOqY2W9h8KkvJ8+WRbTVg9jEs8yORnNROsG7ED8vd26dP5Kv75nPT+cm8WlmEec8vo5L/7WelVvzmRO7kJWXfcLfz/o7ASGjeCDIl/NzV/LKsuk0vv0jKNhp9lsYNMrX/YUd3h7E+M0wOxTNhekE74ICfT24Z+EYvvrlWdyzcDTldc38cuUuznj4U37xZgY+1vG8ctF7PHPOM8REjOfRkEDOq05n2euLqXtxEexbAzab2W/DddWWiCfHTwAAC9dJREFUsDXzVVpEmJak587RnEePg3dhYUO8uHneCH46N4ltOZW8vTWXD3YW8M72Y8QG+/D9SbE8PHMZRc2ZPLfz/9u78+io6iuA49+bhCFkJYuBEAIkBEggYQmoUUA4LlTRCiIgGhWtSymnPXU9xaXa2tNjq6curQt4QAGlSgW01AMiRWRLQSFCAFnDJpCwSYiBQELy6x/vIUMcMMDMvMnM/ZzzzrzM+8387vzmzs17b9689yYvh3/JpPpdFM59kMLPEonPvxd6FkJ0stMvJbgUvcrS5mFInYtbcnQNXvmOOHUt0D59+piVK1c60ncoq66pY976cmas2s2y0oMYAwWZiYzonU77NoeY+s1EFu7+ghgj3F1xmLuqThCTfRP0vtc6w2ETOYWtiKwyxvRxou9z5vb3+zCv9uCqNqkcq81l1S/f9W9wqsk7n9zWNfgQ08IVztBeaQztlcaeimpmrdrNjOLdPPrhGqJd4dzY/X7+kH83Sw5O4w1ZwLTEZtxTtoQ7ps4iKjELet8DPe+AqESnX0rTtOwVNoYbKsJP0rW5npZA+Zbugw9haS1b8JtrOvHFYwOZ/mABg/NS+aSkjEen7WfjmmE83PUNurcp4NW4SG7I6sLUaBfH5z8Nf8uGmQ/AziI9N/35qCyDrybxeTtr5WtAu/4OB6SCnRZ4hYhweWYSL47owVdPXcsLt3bneG0dz82sZO+mQh7Pe41OyXm8GP49N3bpzgc5A6nd/Cm8cwO8UQDL34Tqw06/jMC39GUwdcyLcFFXnUa/jAynI1JBTgu8OkN08whGXprO/EcG8JdheeyvPM4z/6qiaud9/K7HK7SNz+DPRzdwU6dsZvV7kFpXFHw6zlqr/2gMbJqrxd6T7/fBqneo6D6CHcdL4Vg22a3jnI5KBTndB688ahYexqjL2nFLfhr/XLGL1xeW8vQHJxjQZSxP9K7kP7ve5tk9nzIpqR1j8p9n8N7NhK/9ENa8Dwi0yoX2V56eYjxe6S50xKTA7e9TdLwMs2oZGdGX4orQ9SvlW1rg1Tk1jwjn3r4Z3HZpOlOKdjJ+USmLNtVyfbdHeSL/ALO2T+LJdW8yMT6TsbdN4LqweMJ2/Q92LoOv34UvJ1hPlNTJKvQd+lm38W2dfWH+JgJZ17Jo0TjMyWgub6PnnlG+pwVeNUqUK4JfDexIYUE7Ji7ZzqQl2/jsm3qG9HiSYfl7mF46kceWPkHH+I6M7jaaG/s9hAuxfh27c5n1hez6j6F4ivWELdtB+772Gn5fSMxsModgXqi6+jqW7FnKyaOd6d0+yelwVAjQ4+DVBfnuaA3jF5UypWgHdfWGEX3SyOuynVml77Hp8CZSWqRwZ9c7Gd55OLGuWOtB9XXWFad2Fp0u+scOWsuax0PrXGidd3q6JBsiml9QfIF4HHzJgRIK5xRSvWcUi8c+QpuWLRyITjV1ehy88rnEaBdPDs7h/n4ZvLZwK+9/uYuZxc25ouPjXJ2wgx11n/DSqpeYUDKBkZ1HUphTSKvoVpDa3ZoKxliHWB7cAruKoKwEytdC8VSoPWZ1EhZhFXn3ot8qt8keg79492JASCCX1PhIp8NRIUALvLooKXGRPDcklwf6Z/LW4m2s3HmYoq2x1NaNIiyyP3XJi3ln3WQmr59KTuxARmQVcm1WD1pGuaxdMpd0PvPSgvV18N12KLcLfvlaKF1of3lri2t7uuDn32Xt7mkCluxZQkRNBvnpaUiQ745SgUELvPKK9MQo/jQ0F4Cak/WUHqhiY3klG8r6s7qslM3Vc1hfv5hvvl7A7xdnE3viOrom9qBrajw5qXH06ZBAanwLCAuH5Cxryh12uoOq/acL/qlpyzzo2jRO1lVxvIKNhzZSXXEdvS5LcDocFSK0wCuvc0WEkZMaR05qHLf0AsgBbmLrwX1MKpnGf/fMpLr+H5ScbE9RcX9qKrsCYbRPiqIgI4krOiZRkJlEa/fdGDEpkHWNNZ1Sc+yC99H7W8vIlvwxfzoPf1BCz/SWToejQoQWeOU3WcmteP7qR3j25Fhml85m8vrJfBvxHulZbYgNa8eRo+HM2St8tMOFmR9JUos4uqSkkJfaivz0VDokJBHjiiGmWQwtIlogriinX9J52VYmSH003dvGOx2KChFa4JXfRUZEMrLLSG7tdCsLdi1gxuYZHKg+QER0FTHNqqC2CoCjQPFxKN4OU7af+RxhEk6sK4bx144nNznX/y/iAnz9bQXZreOIcunHTvmHZppyTHhYOIM6DGJQh0Fn3F9v6jlae5SqmiqOnKhkXfk+vt5dzvryfZQePMiJ+mMQdhxXdB37Djcjtwmcrr6+3rB6VwU/79nG6VBUCNECrwJOmIQR64ol1hVLakwq2UldGN7NWlZXb/hmbyXLtx1i+bZD5LVu72ywjXS05iTXdWvFgM6XOB2KCiFa4FWTEh4m5LWNJ69tPA9clel0OI0WG9mMl0b2dDoMFWL0bEdKKRWktMArpVSQ0gKvlFJBSgu8UkoFKS3wSikVpLTAK6VUkNICr5RSQUoLvFJKBSnHrugkIgeAnWdZnAwc9GM45xIosQRKHBA4sZwrjvbGGEd+NtpEcjtQ4oDAiSVQ4gAv5bZjBf5cRGSlU5dbayhQYgmUOCBwYgmUOM5HoMQcKHFA4MQSKHGA92LRXTRKKRWktMArpVSQCtQC/5bTAbgJlFgCJQ4InFgCJY7zESgxB0ocEDixBEoc4KVYAnIfvFJKqYsXqGvwSimlLpKjBV5ErheRTSKyVUTGeVjeXESm28tXiEgHH8SQLiILRWSDiKwXkd96aDNQRI6IyGp7esbbcbj1tUNE1tr9rPSwXETk7/aYlIhIvo/i6OL2eleLSKWIPNSgjc/GRUTeFpH9IrLO7b5EEZkvIlvs24SzPHa03WaLiIz2VkyNFQh5bfejuf3jPkIrr40xjkxAOFAKZAIuYA3QtUGbscB4e34UMN0HcaQC+fZ8LLDZQxwDgU/8NC47gORzLB8MzAUEKABW+Om9Ksc6/tYv4wJcBeQD69zuewEYZ8+PA/7q4XGJwDb7NsGeT/DHe+c2Vo7ntf3cmts//V4FdV47uQZ/GbDVGLPNGFMDfAAMadBmCDDFnp8BXCMi4s0gjDFlxphie/57YAOQ5s0+vGwIMNVYlgMtRSTVx31eA5QaY8724x2vM8YsBr5rcLd7PkwBhnp46M+A+caY74wxh4H5wPU+C/THAiKvQXO7EYI+r50s8GnAt25/7+bHyfdDG2PMSeAIkOSrgOxN5V7ACg+LrxCRNSIyV0S6+SoGwACficgqEXnQw/LGjJu3jQLeP8syf40LQCtjTBlYxQtI8dDGifE53/79mteguX0WQZ/XTl6T1dMaS8NDehrTxitEJAaYCTxkjKlssLgYazOuSkQGAx8DnXwRB9DXGLNXRFKA+SKy0f6v/0OoHh7js0OhRMQF3Aw84WGxP8elsfw6PhfYv7/fQ83tBkIlr51cg98NpLv93RbYe7Y2IhIBxPPjzZuLJiLNsD4A04wxsxouN8ZUGmOq7Pk5QDMRSfZ2HPbz77Vv9wMfYW3yu2vMuHnTDUCxMWZfwwX+HBfbvlOb7Pbtfg9t/D0+F9K/X/Lafn7Nbc9CIq+dLPBfAZ1EJMP+bzoKmN2gzWzg1LfFw4HPjf2Ng7fY+z4nARuMMS+dpU3rU/tIReQyrHE75M047OeOFpHYU/PAIGBdg2azgbvtIw4KgCOnNu985HbOshnrr3Fx454Po4F/e2gzDxgkIgn20QiD7Pv8JSDyGjS3f0Jo5LUvvik+j2+UB2N9s18KPGXf9xxwsz0fCXwIbAW+BDJ9EEM/rE2dEmC1PQ0GxgBj7Da/BtZjHRGxHLjSR+ORafexxu7v1Ji4xyLA6/aYrQX6+PD9icJK7Hi3+/wyLlgfvjKgFmvt5T6s/dQLgC32baLdtg8w0e2xv7BzZitwbyjmtea25rUxRn/JqpRSwUp/yaqUUkFKC7xSSgUpLfBKKRWktMArpVSQ0gKvlFJBSgu8UkoFKS3wSikVpLTAK6VUkPo/Ka9uokPUkhgAAAAASUVORK5CYII=\n",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -688,140 +796,52 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Federated training with FedAvg"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Clients' weights: [0.29, 0.2733333333333333, 0.43666666666666665]\n",
-      "====> i: 0 Loss: 2.30640879313151 Server Test Accuracy: 5.493723798307226\n",
-      "====> i: 1 Loss: 2.1980189021428425 Server Test Accuracy: 25.296830811393917\n",
-      "====> i: 2 Loss: 1.7439398292700448 Server Test Accuracy: 45.54914137438409\n",
-      "====> i: 3 Loss: 1.227887612779935 Server Test Accuracy: 52.50069193148895\n",
-      "====> i: 4 Loss: 1.0358077690998713 Server Test Accuracy: 69.34269491889722\n",
-      "====> i: 5 Loss: 0.8220566266775131 Server Test Accuracy: 64.55666752776709\n",
-      "====> i: 6 Loss: 0.5739711784323056 Server Test Accuracy: 77.7559790542405\n",
-      "====> i: 7 Loss: 0.5648151334126791 Server Test Accuracy: 78.26422426038592\n",
-      "====> i: 8 Loss: 0.40358308206001914 Server Test Accuracy: 83.93029290297295\n",
-      "====> i: 9 Loss: 0.46662271827459334 Server Test Accuracy: 78.71991250677183\n",
-      "====> i: 10 Loss: 0.33874771108229956 Server Test Accuracy: 81.94775222275786\n",
-      "====> i: 11 Loss: 0.3785162182648977 Server Test Accuracy: 83.32578141474053\n",
-      "====> i: 12 Loss: 0.3105277146647374 Server Test Accuracy: 81.09443695219264\n",
-      "====> i: 13 Loss: 0.3969525445004304 Server Test Accuracy: 75.00452993069837\n",
-      "====> i: 14 Loss: 0.26835320631663007 Server Test Accuracy: 84.14531781725279\n",
-      "====> i: 15 Loss: 0.21986659824848173 Server Test Accuracy: 88.70465340029575\n",
-      "====> i: 16 Loss: 0.21281323460241158 Server Test Accuracy: 86.37012401880318\n",
-      "====> i: 17 Loss: 0.18938758075237275 Server Test Accuracy: 88.0659826681502\n",
-      "====> i: 18 Loss: 0.15882468936343988 Server Test Accuracy: 89.17662254713508\n",
-      "====> i: 19 Loss: 0.16109553222854933 Server Test Accuracy: 89.13432285299524\n",
-      "====> i: 20 Loss: 0.20892317460228998 Server Test Accuracy: 85.58936086685014\n"
-     ]
-    }
-   ],
-   "source": [
-    "n_iter=20\n",
+    "### Federated training with FedAvg\n",
+    "\n",
+    "### EXERCISE\n",
     "\n",
-    "model_f, loss_hist_FA_niid, acc_hist_FA_niid = FedProx( model_0, mnist_non_iid_train_dls, \n",
-    "    n_iter, mnist_non_iid_test_dls, epochs=2, lr=0.1, mu=0)"
+    "Train FedAvg for this MNIST non-iid dataset and plot the accuracy and loss evolution during the training"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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01Bq2HCqkqrSIK19cz+fbC7jnrDHceloKd62+k+iAaP48+8+9iuDq9ivA6DL/ArBLSvlPB2PigEIppRRCTEd9UZT2eDb2qCuDbe/A+CUQYPSanXMzfPhr2L8cRix0y2U0dGtJ9xeZmZm8++67A3JtzRCjOl89lncV9OJ6JbxpIWk8suEREn0n8ffPj/D9/hJGxwXz8IUTePGHQ9zw2mbmjYjiD2ek8ujGRxkXOY7759zPRR9fxIs7XuT3U9pZ/ltfg09/z77zP+fWd8qYlBzGwxdNsCvGE5PDeP/G2Vz54nryXrqaGK+DbGn8F/+5dBLnTkrkj6v/SF5tHksXLSXEJ6RXL98VC30Oqi/f/HZhiWcKIW4QQticnhcBWUKIn4D/ApdKd7VC2vIaNNfDjF+1bRt3EQQnwA//dsslNAPL/PnzsVgsPPfcc63bNmzYwMqVKwdwVhpXaWhu4L419/H39X8f6Km0CbodH3pxXTHeJm/unn4/RfXFLHn7L2zLreAv52by6W/ncvG0ZD797VzuWzyWrTkVXPLOfZTUl3LblLsYGT6SszLO4s1db1JSX9J20iNrwNpEyft/IDzAzLNXTsHP7NXl2jZSIwP56BwvzjKtIVEW8OrPx3DupEQ+OfAJnx78lBsm3sAJMSf0+uW7EuXyvZRSSCkntAtL/FxK+bSU8mljzONSykwp5UQp5Uwp5Zpez6g91hbY8BykzoG48W3bvX1g1o3Kr350k1supRk4hBB88MEHfP311wwbNozMzEzuu+8+EhISmDdvHkuWLGH58uUkJSXx5ZdfDvR0Ne0oqivi6mVX896+93hv33u0WFsGdkJVhqBX5ih3SDuK64sJ8orgdy+X0Vg+DZ+IH3jhuiSunJWGd2MlfHQT3o2VXD0nneeuTcA7fA2N5dP5zUslvL0hm6mhl9DY0sj9q/7L6n3FrN5XTO3hjVjwYZbcylvza4gJ9nM+P6uVsFX3tT6dGV5FdlU2D6x9gMkxk7l+/PV9evmenSm6d5n6pp1u50VOvgp8Q+GH/x77eWncTkJCAu+88w4HDhxgx44dfPbZZ4wYMYLVq1dTXFxMfX09ubm5nH766QM9VY1BVkkWl316GYcqD3HOsHOob67nUOWhHp3jlhW38PCGh3t0TG1TLed/dD5fHPqi687qPPXY0gg1BR127S05SmmlHzHBfjy3+F5CfIN5Yvsjyl9+cKXyBuxZhlVaeTLrEcJ9w3hu8b1EBftw53vbue2NozSUT2VF3sdc+fJXXP/CKvwq9vNC8yLqglJI2fj/VL6MwWNbHuPUd0/l7d1v02w1tu94XxmhM9XialPJXu5YdQfeJm8emvcQXibH1r0reLagr3sGQhJhtJ2kEr8QmHYN7PoYSg8c+7lpNMcxXxz6gquXXY23yZtXz3yVa8ddC8CO0h0un6O+uZ7vcr7j9V2v9+iL4LWdr7G/Yj+bCzd33VldAMIQxU5+9EPl+fiIUN799SxOHJbGLZNvYVPhJj49+CmUHVSDjm7kkwOfsKVoC7dOuZUTh6Xy0U1z+eimObx7wyz+u+h2zF4mzjoxiw/OD8ZLSJacewEBZ/4NinfBFpUz8cqOV3h227MAPLDuAS74+AJWHPoS+c19EDcBTv4jAI8deJ8dpTu4f/b9xAfFu/weOMJzBb1oNxxaCdOuBS8Ha7czbgCTt4pL12g0/Y5VWnlsy2PcseoOMiMzefPsNxkZPpLUkFT8vf3ZWbrT5XPtLttNi2zBKq08tfUpl46ptFTyUtZSAFYe3N91QFVem3u2XaTLpiNlNMhyMmOT8fVWgn/BiAsYHzWeRzc+SnXpXnX+3PX8c9M/mRg9kXOHnwuAl0kwMTmMqWkRnD56DBePWsL3BV8QYFFfKNGjZsCYxZAyG1b8jc/2vMsjGx9hYcpCll2wjP+c8h+klNy86nau8bewY/b14BfCmvA4XqrM4qKRF7Ew1T3BHZ4r6OufBS9fmHy14zHBcTDxUtj6emvokEaj6R/qmuq47bvbeHbbs1ww4gKeP+15IvxU5JmXyYsxEWN6ZKFvK94GwPnDz+eLw1+wp2xPt8e8vONlaptrsTZGkludz/6i6radUioLPXm6et5uYfS/3+5EeNUzJy2jdZtJmLh75t2UNZTxRMVPADzeeJQKSwX3zLwHk7Avj9dNuA6zycxTuV9BYAwEx4MQcPrfWGOt5p61f2Fq7FQeOlG5UOanzOf9Bc9wT0UtB/0DuXTLw9yx6g7uDvUjQ3pzx7Q7XH7PusMzBb2+An56E8ZfBIGRzsfOvhmaLeoLQKPR9Av5Nflc+cWVfJvzLXdMu4P7Zt2H2atjU5GxkWPZU7anzV/cDVklWcQHxnPb1NsINgfzxFbnd9ql9aW8suM1mionkB44ES/vKh78fHfbgPpyaLFAeDoExbW6XLKOVrLqoHLpJATHdjhnZmQmF4+6mDep5oOIWN4JDuDShJMZHTHa4Tyi/KO4bMxlfNZYzP74sUrMgSxfH26Ji2NYYyP/nXIHvl6+rceYVz7MJZWVfHbay1w3/jq+zf6WKiF5uKIef29/l94vV/BMQd/6OjTV2V8M7UzUCBh9lhJ0XbRLo3E7W4u2culnl3K05ihPLHiCK8ZeYTfOOjMqk4aWBg5WHnTpvNtLtjMuahyhvqFclXkVK3JWkFWS5XD8C9tfwNLSQGD9mZw2aiR4V/Pt7jx+2G+EEVYZC6LBcRCe2upyefK7/QT51wIQ7d81ofG3435JmNXKn0J9CW+xcpNv91ns14y8lABp5UkflZ5/pOoIN35zIxEB0TxVXEnwqkfbBhftgs0vw9RrCYqfyM2Tb+bzCz7nrcSzGVWRD411rrxdLuF5gm61wvrnIHkmJExy7Zg5v4OGitYFCY1G4x4+2v8R13x5DUHmIF4/83XmJs51OHZspCrC6oofvbS+lKM1R5kQNQGAy8deTrhvOI9teczu+MLaQt7c/RZNlZO5c/48kkNUWn18ZCMPfLaLFqtsyxINSYCwFKg4wv6iar7IKuDETGUtRwd0FfTQ2jJuK6sA4LYGEyEF27udf1h5NldWVvN1fQ6rclfxq69VnszTpz1P9IwbYfv/INcIqf7qHvANhpPvaj0+JiCGEXFGuYvyw91ez1U8T9D3f63qMczoQTxm8nSIn6Tqu2gGJfbK565fv55Zs2aRmZnJhAkTePvttwd6mscNLdYW/rnxn9zzwz1MjpnMG2e9QUZYhtNj0kLSCPAOYEdJ9350myU+LmocAIHmQK4dfy1r8tawsWBjl/FPbX2GZquVJHEuF05JIjZAuU4umx3Krvwq3tuc2xayGBwPYalQeZRnVuzFz9uLCSnqjiLGP6brZMoOck5NLd/M/ReLo6e0CbEz8rZyRWUVIeZgblp+E2UNZTy58EnSQtNg7i3Kt/7l/8G+b2D/N3DiH9oy3W1EZLRe3114nqBveln9Qcac07PjUmdDwTZdhXEQ4qh8bn19Pa+88go7duxg2bJl3HLLLVRUVAz0dIc8NY013LziZl7a8RKXjLqEp059ilDf0G6PMwkTYyLHsLOsewt9e8l2vIRXq1UPcPGoi4n2j+axLY/RPtE8tzqXD/a/T2P5NO47Yx5eJkFsoBL04fHNnJASxj++3ENjeSeXi2xh3U9ZXDY9hTprOWaT2f7rMAQ1NmEKJE2DymyoLnT+AvK3EhwYww2Tfo2PyYd/n/zv1i8nfINh/t2QsxbeuxbC0+y7j8PTO1zfHXicoOeceg8/nvpH8OphF/eEydDcoPxVmkGFo/K5J510EiNGqKKdCQkJxMTEUFyso5lstFhb+OrwV1hlzxshOKKgtoArvriCH47+wN0z7uaemfdgNrn+v5gZmenSwuj2ku0MDxtOgDmgdZu/tz/XTbiOzUWb+THvR/joJsh6n/9segKrVTAtfAlzR6iafzYLvaiuiHvOGkNRtYXde/dAQCR4+yqXC5BiKuK6E9Mprism2j/afsGrsoPgHwH+4ZA0VW072vUuoQN5WyB+EleMvYLVl65mduLsjvtPuAJixipX8ML71Zw64x+mrutGQe95fcZ+5k/rnmZn+VbWjr+yZ9XGEierx7zNED+hfyY31PniLnDBf9gj4sbDGQ85HeJK+dz169fT2NjIsGHD3Dm7Qc032d9w+8rbeWLBE5yYdKJbzvn89ufJqc7h6VOfZmb8zB4fPzZyLJYWCwcqDjAqYpTdMVZpZXvJdk5LPa3LvgtHXMjSrKX8d9M/mbXlaw7Vl7DMsoumirnc9/NZreOCfIIINAdSUFfA1eMiOGt8PCV7j9AUHYsZKPGOIwo4L62Z+FB/iuqL7PrPAeXitbk/4ieq3JbcjSrYwh6NtVCyF8aeB9DhS6kVkxdc+LwqIDj2XAfvFuq6Q9lCt1SNoK6lnNe3/tizAyMywC8UjtrJHtMMavLz87niiit46aWXMJk87iM7YKzNXwu0xXO7g3X565geN71XYg7KQgfnC6PZVdlUN1YzIbqr4eXj5cMNE29gR/keVgT483jNPqTVzOLUnzM8pmOjk9iAWAprlWvkzkWjiaGM/Q1qzHM/NdIiBQvjVUOJ4rpiYgLs+M9BCapN0M3+EJvp3EIv2A7S2n3QRmymqgzrzDCNyICynpVLcIbHWegPn3kJZ3z4LI+s/JD56SeQEOZijKYQyu2SpwW913RjSfcXzsrnVlVVcdZZZ/HAAw8wc2bvRGaosj5/PYDTUL+eUFBbwOGqw1w08qLWbVJKDhTXsHxXEct3F1FR18iJI6JZMCaWqWnhmL06fsGmhKQQaA5kR8kOMvxOYfnuIlbsLkIIOGVUDAvGxHCoQX0BtfqcO7F42GJeWP8ID0U2k+/dBOULuXPJ1C7j4gLjKKxTgp4SGUCNTyWfVqZRtr+EVzfk8SufGCIsqlhXcX2x/S+pZgtU5sLEdgu+SdPgp7dUcUB7tVXytqjH+EmO3krXichQETHNFvtumR7iceZOUmgMw0PH0OK/ixtf39yzRqmJk6FwJzTV998ENW7HWfnc888/nyuvvJIlS5YM4Aw9j/yafLKrs/Hz8mN7yXbcUa16Q8EGACZHT+P7fSXc/8kOTnrkOxb+cxX/74vdVDc0Exvixys/HuGy59Yy+a9f85s3NvPBllzKaxupsTTz1Y4ifFtSeGf7j5z7xA88/u0+fL1N+HiZeOzbfZzz+A/8+csv8MKXg0cDqWvs6mv3NnlzY0sA+d7eBLdY+fWYC4kK6ip27S10WpoIbCqn0iuSa5ZuoK6xBb+YdCg/Qn1zPdWN1fZdLhXZytqOSG/bljgVGmug2EHmat5WCIqFkL7XXlF3BtJu/fbe4HEWOsDCtJM4UPksW/fk8eDnu7jvHBcbLyRMBtmibols6b8aj8dWPveWW27hoYcews/Pj7S0NGbOnMmqVasoLS1l6dKlACxdupRJkyYN6Hw9gfUFyjq/YMQFvLH7DbKrs0kNSe3TOdflryPAK5jLnjhCjeUQPt4m5gyL5PoTM5g/Oqb1brnW0sz3+0tYvquQb3cX8+m2fExC1TxpapEEJ8QgQtfw6MXjmD8qnvBAHwDKahv5bk8R/8h6huq6RG54bSs+3ibiQ/1o75QQ0sqHdTuZGxPC/Poqzllo/y49NjCW4vpimqxNmGsKEUjGjx2DZbOV0zNjCQgeBgdWUFKnEo/sJRW1+q8j2lvo7RZGY8d2PSZ/KyT0vmZ5B9qHLkaP7PPpPFLQ5ybO5emfnubUKRUsXXOYKanhLJ6Y0P2BtoXRo5u1oA8ybOVzO3PvvfcOwGw8n/UF6wn3DW8V9G3F2/ok6FJK1hWsp7E2g4SwAO44fTSzh0cS4NNVIgJ9vTk9M47TM+OwWiXbj1ayfHcRlqYWTh4VQynwx+9XkplW3yrmABGBPpw9MYa/7sjhqimXM3vhDL7dXURxjaXD+WMsRwg9VMtlTYs4sfo9qM4Gui6axwbEIpGU1pcSZyQVTR8/lhtDMrh4ajJkpUB1PkU1RwH7SUV2BT1imFqPy92o2l62x1LTYUG0z7g5Ft0jBX1c5DjCfMOIjD7IlNRM7npvG2PiQxgeE+T8wJAEVcNB+9E1QxgpJWvz1zI9fjrDw4bj7+1PVkkWi4ct7vU5c6pzKKjNp6FiOo8sHs3CsbHdHwSYjEqEE5PDWrcdqVK+8Z2lO1VNlKObVEnbhEnsLttNs7WZiTETmJ0axezhXVoPw9ZdcAhOvODX8MJ7DjMpbaGLBbUFxBlp/95hidwxxqjDEpYKSIpLlevEUVIRviEq3LHtRSm3S66dhVFXF0RdJSBC9XVwk6B7nA8dVOW2OYlz+DF/DY9dNgk/sxc3vr7Jrr+tC4mTdaSLplcIIW4VQuwQQmQJId4UQvgJISKEEF8LIfYZj+EDPc8jVUcoqitietx0vExeZEZmsr2kb+Gma/PWAZDiP4H5ox1Eg7hIcnAyweZglTFaXw6vXQgfqBwD2zzHR413fILcjUpkE6dAQJRjQTeSiwrrCttazwW3u5MPV3csxeWqzK5DCz0ivWskStJUVd+8c32o/K3q0R0LoqCuG5GuQifdgEcKOii3S1lDGWXNB/nPpSewr6iG/3vfhcWfhMlQug8aKo/NRDVDAiFEInAzMFVKOQ7wAi4F7gKWSylHAMuN5wOKzX8+I34GoMRxd9luGlsae33Oj/auxNoUws0nzsFk6nm3+fa0ZoyW7oRV/1CiXrwLKnPZXrKdaP/oVuvaLkc3Kh+1yaSyLB2E9dnOUVhrCLrJ3NHSNpKLiqty8DH52G+83D5ksT2JU5UlbotosZG3VXkB3LEgasONsegeK+hzEuYgEKzOXc3cEVH8fuFIPtyaxxvruzZ/7UCisVjR+Q+h0XSPN+AvhPAGAoA84FzgZWP/y8B5AzO1NtblryM2IJaUYCVY46PH02RtcqmeuD2sVitZpZvwbxnF2RNcWKtygczITPaU76Zp3TOq8QPA/uVklWQxPmq846TBxjooyGpbmAxPc2ihh/iE4O/tryz0qnyV8t8+TyE4HkxmiupUUlGXa7Y0qSgXu4Ju+Ow7x6Pnb3Wfu8VGRIaahxvKlnisoIf7hTM+ejyrj64G4KZThjMjPYLHlu93bqUntFsY1WhcREp5FPgHkA3kA5VSyq+AWCllvjEmH7DrjxBCXC+E2CiE2Nif5Qms0sqGgg3MiJ/RKlA290Vv3S5vbt2A1VTDaRlz8OqjdW5jbORYmqzN7PfzhyUvQXAClfuWcaTqCOOjnbhb8n9SkWqJ7QS9Mteu2AkhVOiizeUS3MlqNnlBaBIllgr7SUWVOWBtti/ogZFqe3s/usUIZXSXu8VGRIaaR2VOn0/lsYIOMC9xHlklWZQ1lGEyCS6akkRBVQM786scHxQQoYre6IVRTQ8wfOPnAulAAhAohLjc1eOllM9KKadKKadGRztIMXcD+8r3UW4pb3W3gHI9RPtH90rQpZS8sOkrAH41zX0NuDMtKnJlx9hFynIevoAsw0/v1H9us4jbW+iyRYm6HWIDYimoLTAEPa7rgPBUilrqiPK3s/hqc+XYE3RoWxi1GZAF2wHpvpBFG7YYeDe4XTxe0CWSH47+AMDJo2IQAr7dVeT8wMTJcFS7XAYT9srnrly5kilTpjBp0iQyMzN5+umn+3MKC4FDUspiKWUT8D4wGygUQsQDGI/dfPj6l3X5ShSnx7WF5QohGBc1rlcZo+sOlZFn2U6YOZ7UsCT3TNJqJWnVPwm2SnaGG1bz8IVsMzUhEK3lAeySu1H5voMMizo8TT06WRhVFnqBinLrTFgqxbLZvoVuL2SxPUlToaYAqlTYY+uCaH+4XMAtJQA8WtDHRI4hwi+i1e0SHezLxKQwvtndzf9UwmSoyoWaAf3f07iIo/K5AGvWrGHr1q2sW7eOhx56iLy8vP6aRjYwUwgRIJQvYwGwC/gYuMoYcxXwUX9NwBXWF6wnNSSVuMCO1uiE6AkcrjpMpaVnwQCPr9iDOfAQJ6fM6n6wq2S9i8jbytiQdHaUG379jJPJ8vUjwzuYIB8n4ce5G9vcLdBmvTqIAokNiKW4rpgWS5VdC70uJJ4akyDax17Z3ENgDlBZn/awzcPmdsnbohZE7d0J9IWgWDWPoW6hm4SJuYlzWZO3hhZrCwALRsfwU04FxdUWxwcmaj/6YMJZ+VxfX5XybbFYsFrdVya2M1LKdcC7wGZgO+p/41ngIeBUIcQ+4FTj+YDQbG1mY+FGZsTN6LLPVhfF1lyiuqGJZ1cdoKi6weH5fsqpYE3ONjA1MDvRTXVymurhm/shfhKZqaewt3wvjS2NSL9QtvsHMM7i5P+2ukAZYkntBD04Hrx8nMait8gWSr28OoYsGpQYPYljpB2pKzuo3LOOFmjjxqlr29xAeVvd724BI3TRPZEuHplY1J55SfP4+MDHbC/ZzqSYScwfE8OjX+9lxZ4ilQ1mj/iJIEzKjz5q0bGd8CDm7+v/zu6y3d0P7AGjI0Zz5/Q7nY5xVj43JyeHs846i/379/PII4+QkOCeKAx7SCn/DPy502YLylofcHaU7qC2qZbp8V2zoDMjMxEItpVsY3bibD7bls+Dn+/mv8v3c8vCEVw1O61LIa3HV+wnMFRZvtPiprlnkj8+oUT5gmcYSy3N1mb2VewjxCeEcmFlQnk+1JZAoB2fts0STmo3F5OXcsE4EHTbnUqhlxcxdkIJi3xVaduoJjshnWUHVU9iR3j7Ki3J3diWITruAsfj+0JEuuPaMT3Aoy10gFnxszAJU6vbZWx8CHEhfs796D6BED1aW+hDgOTkZLZt28b+/ft5+eWXKSzsppPMEMZWXdGe+Ab7BJMemt7qR88uq8PbJJiSGs4Dn+3irP+u5scDpa3jdxdU8fXOQhLijzI8bLj9RcOeUl0I3/8LRp8NaXM7lNJtbTlnscCBFfaPP7pRxZLHdSqr6yR0sTW5yNura5QLUOytbNaYhtqOO6wtHeugOyJxqrLM8zYD0v0RLjYiMtRrNDwRvcXjLfRQ31AmRU9ide5qfnvCbxFCMH9MDB9tOYqluQVfbzvlLUH50fd+oVaoe9Io4zimO0u6v3BWPtdGQkICmZmZrF69mosuusjp2KHKuoJ1jAwfSYRfhN3946NUmK+UkuyyOhLC/Fn6i2l8vbOQv3y6k8ueW8viiQncfeYYnlxxgAAfSWnzbk6Jd9P7+d2DqmvYqX8BIDEokRCfEHaU7MDf2x9fL19GeIeoHpsT7FTPzN2o3Bxmv47bw9Mgd4PdS7YmF3l72fVtF0nl4omuLeu4oyoPWhq7F/SkqbDuKdj6pnru7gVRGxEZaj5VR1sTonqDx1vooNwuu8p2UVKvqqYtGB1DbWML6w+VOT4ocTLUlaqAfY1H46x8bn29KoVcXl7ODz/8wKhR9rvgDHUsLRa2Fm3tEN3SmQnREyhrKCOvNo+c8nqSI/wRQnBaZhzf/P4kfrdgBF/uKGD+o9/x6bY8TptswdJicXpOlyncAZtfgWnXQaTqKiWEimixWehjIsZgHjYfDiyHzush1ha16Nh+QdRGeLrK/K4v77IrzDcMH0wU+gSoXp6dKKkvwVdCcOXRjju6i3CxYUswynpP3QG4e0HUhpuKdA0KQZ+bOBeA749+D8DsYVH4eptY7szt0r4lncajsZXP/frrrxk2bBiZmZncd9997N27lxkzZjBx4kROOukkbr/9dsaPdxLDPITZVrwNS4vFaSch28Lo9uLt5JbVkRze1hrNz+zFraeO5JtbT2L2sCjCA3xIjD+KSZiYGmdHRHvK9/9SgnrSHR02j40cy76Kfewq26USioYvhNpi1dC9PcW7VQ3yJDu+fFvoop2wPiEEscKbAj87beBQPUejhRnR2bBzVdDD01Q9mRZL/7lb2s+jj6GLHu9yARgVPopo/2hW567mvOHn4e/jxdzhUSzfXcifF4+1n0Yck2msUG+GzPOP/aQ1PcJR+dzrrrtuAGbjeazNX4uX8GJKrOPeqyPCR+Dr5cvmwp8orR1HckRXkUuJDOD5q6YipeTqZa8xJmKM/RonPeXoJkg/SSX2tSMzKpNmazPNNKuEomhj/vu/6ei+yO2UUNSe9rHoNkOtHbEtkkKz/UbWxfXFxHgHdr1TLzsIXr4Qkuj8dQmh5rR3Wf+5W0BF6Hj59r+FLoRIFkKsEELsMirR/c7OGCGE+K8QYr8QYpsQouu73geEEMxLmsePeT+2dhOfPyaGnLJ6DhTX2D/I20c1KNY1XTRDgPX568mMzHQaw202mRkTMYYthcr6TQp33L6xvrmebSXbOmSc9hpLtRKizouZKAvdxvio8SphKG4CHPi248DcDeAfbt9iNqomOlwYbWqk0MEyWXFdMdF+EdBQ0bFgX9lB9UXhSo9amxuoP0IWbZhMKtLlGLhcmoHbpJRjgJnATUKIzm08zgBGGD/XA0/1aVZ2mJc4j+qman4q/gmgtcTnN87cLgmTlaD3ceVYoxlIaptqySrJshuu2Jnx0eM5ULUHaLFrodvYUrSFZmuz3Zj2HlOoYt+J6+oOSwhMIMw3jHDfcBKDDGt4+ELIWddRYI9uUv5qe3fbvsGOy+harcQ21FIoG7HKrnkKxfXFRNsqO7Zv81Z+uHt3i43M82D4qeDO5Ct7uKFhdLeCLqXMl1JuNn6vRmXPdb5PORd4RSrWAmG2dGl3MTN+Jt7Cm9W5KnwxPtSfsfEhzsMXEycrv1zJPndOZcjhjn6UA8VgnrurbC7cTLNsdsmaHh81niarBZNvQQcfemfWFazD2+TNpJhJfZ9ggVFDxo6gCyE4LfU0FqUvanONDl+oilEdWqWeW6qhaJd9/7mNiHT7gl5XSmxTI81Iyho6BknUNtVS21RLdKgRNWJzu0jpuGyuPaJGwOXvgp8bXFPOCDcs9D58pnu0KCqESANOANZ12pUItC8VlktX0e8TQT5BTIie0FoLGmDBmBg2Himjos5BHegEvTDaHX5+fpSWlg5KYZRSUlpaip+fX/eDBzHrC9ZjNpmZFD2p27G2wld+QUeJCvJxOG59/nomRE0gwOxY9F2mYBv4R9ivpQLcO+te/m/G/7VtSJ4OPsHKjw5Gvoi0H+FiIzzNfvp/dT6xLeoOvLCuY45CcZ2qehkdPlxtqDAs9JpCaKrr2BjaE4hIh+Z6lTHbS1xeFBVCBAHvAbdIKTuXO7TnweqiEEKI61EuGVJSeh5rmR6azoqctqSE+aNjeOzb/azcW8y5k+x8f0SNAJ8g9YGZ9LMeX+94ICkpidzcXPqz5Gt/4ufnR1KSm4pKeSjr8tcxKWYSft7df3ElBiXiTRD+oXkOa45XWirZVbaLX034lXsmWLBdWeeu5nt4mSHjJNj/rbJGban1dhY8WwlPU6GDLU3qeBvV+cQ1G4JeW9ih8FdxvfpMx4SmqS8Qm4XeGuHiaYLeLnSxlw00XBJ0IYQZJeavSynftzMkF2ifh5+Eag7QASnls6j6GEydOrXHJmF8YDxlDWU0NDfg5+3HxKQwIgN9WL6ryL6gm7zUQoa20B1iNptJT/ewD7amlUpLJbvLdnPjpBtdGi+EwKsxDXwc19ZekbMCq7S6Z0G0pRkKd8L0HkYjDV8Auz9V7tDcTaoxc6cImQ6Ep6kOQpU5HV0lVXnEtqhACYcWekCMWli1+dBdDVk81rQX9LQ5vTqFK1EuAngB2CWl/KeDYR8DVxrRLjNRzQHyezUjJ8QHqW+tglp1S2IyCU4ZHcN3e4pobnFQuCnhBGVBNPe+PZdGM1DsKduDRDIxeqJL46WUNNQkUC/yqGnsGgH29u63uW/NfYwIH8GEqK5RKT2mdL+K0bbjP3fKMKM8zv6vlYXuzH8OjsvoVhcQ0SLxFt6qFV07bBZ6dEC0yr6saCfoJm8I7bmXoF8JTVbz6kOkiys+9DnAFcB8IcRW4+dMIcQNQghbebzPgYPAfuA5wDVzoofEBypBz69t+65YMDqGqoZmNh3pmkUGqNu4lkYo2tEfU9Jo+pUj1UqE0kLSXBpfUddEfU0SIFVPT4MmaxMPrH2AB9Y9wOyE2byy6BXMXvZjt3uEkwVRp4SnQtRIlV1aU2g//rzDeFsZ3cMdt1fnYQqMJiYgpouFXlRXhL+3P0HmIAhLVS4X24JoWAp4eVgajpe3mmcfBL3bVySl/B77PvL2YyRwU69n4SI2QbdZ6ABzR0Rh9hJ8u7uIGRmRXQ9q35KuP+NINZp+ILsqG18v39YiVN2RU15HS71aU9hWso3p8dOptFRy28rbWJe/jqszr+aWybfgZXJQA6mnFGxTCXxRI3t+7PCFsPZJ9Xui44QpoK2MbuewvuoCCIknLjCuq8ulvphof6OXaHiqinirK+tZhMuxpo9ldAdF6r+N2IBYBIK82jb3fLCfmRnpkSx31PQiLEV1AtcJRppByJGqIyQHJ2MSrv2r5pTVgzWA+IBkskqyOFh5kJ999jM2F27mr3P+ym1Tb3OfmIOy0GPGdFyodJXhhtvFyxdixzkfazIp67WzhV6VD8EJqrdoZ5dLXXFbFUlbwauKw+pLwZMFvfxwr0MXB5Wgm73MRAdEk1/T0T2/YEwM+4tqOFJa2/UgISBmrKplrNEMMo5UHSEl2HVfb055HQDjo8exPn89l392OTVNNbxw+gucN/w8905OyrYIl96QOge8/VRKvbfjEMtW7JXRrc6D4LjWVnTtw2+L64vbWs+FGdmmRzeDpcqzBd1SpQoL9oJBJeig3C7tXS7QljXqsFhX1AhVPH4Qxlprjl9arC3kVOeQGpLq8jHZZXWEBZiZHDuR6qZqEoISePOsNzkhph/cjdUFUFdiN+XfJcz+cNoDMPdW18bbBN32f9xsUcIXoix0S4ulQwu+oroitSAKbRb6we/UoycLOvTa7eJhqwLdEx8Yz47SjgucqZGBZEQH8v3+Eq6ZaycEL2qUquVQW9zWfFaj8XAK6gposjaREtIDC92osnj+8PMxCRPnDjvXPclDdidoLIh25y5xRk/CHcPTlPVaX65CHG0JOMHxrWsMBXUFhPmFUdtUS31zPTH+xv+7X4iqFXNIZZoPCkFP7nlZ48FnoQcpC71z3YYx8SHsL3JQqCvaWLDRbhfNIOJIlYpw6YmFnmvUQQ8wB3DZ6Mv6T8yhrQRuXB8EvSd0bhjdXtBtjS4MP3pRnbpbjwpo14kpLBUslao9ZR+aSPQrYSlqfr200AefoAfG02Rt6lK3YVhUILnldVia7RTisq3Au6Fnn0ZzrMiuUpmNrvrQrVbJ0fJ6pzVc3EphlhJJv9Bjc73OsejVRnBESDtBNyJdbElFrRY6tFVtDE1S/UI9EW8fNb/jSdAB8mo6JqJmRAdhlXCktK7rQSGJqgSAttA1g4gjVUfw9/ZvW9jrhsLqBhpbrE6rLLqVviyI9gbbwmaroLdZ6FH+UXgJr9b1taJ6ZaG3+tChzSoP9/DM6D6ELg5aQW+fXAQwLFrViT5orz66EG0LoxrNICG7Opvk4GSHNVk6k1Om2vUdE0G31EDpgd4viPYG3yAIjG4T9Ko8FfLoH46XyYso/6hWC72kTrWr7PBlaPtC8FT/uY1RZ0H6ib06dPAtigZ1TS4CSI8OBOBAsZ3QRVALo4e/79e5aTTuJLsqmxHhI1wen1Om7k6TnTS2cBtFOwF5bC106Bi6WJ2vilgZX3i20EVQFrq/tz+B5sC2YweLoM+4vteHDjoLPdgcTKA5sIvLJcjXm9gQX8cdjKJGQFWusiw0Gg+n2dpMbnVujxZEc8rrEAISj4Wgty6IHmtBT4eyw+r36gKVQWrQPrmouK64q6sqbpyKe++ubswgZtAJuhCC+MD4Li4XgIyoIA46stCjjW7x2o+uGQTk1+TTLJt7llRUVk9ssB++3m7MBHVEwXbwC1MLeMeS8DRlmDU3KpdLZ0E3kouK6oqI9o/ueGxIAvxfHqT2c+ehAWTQCTrYTy4CyIgO5GBxjf1mDVFa0DWDB1tRrp5a6MkRx8A6h57XQHcX7cvodrLQ4wLjqG+up7qpmpL6ko4LojbcWfbAAxmUgp4QlNChnouNjOggqhqaKa21Uyo3Il2VptSCrhkE2GLQe5JUlGskFfU71hZVA/1Yu1ugLXSxYBs01XZoBNGaXFRb0FqY63hjUAp6XGAclZZK6po6higOMxZG7bpdvMxqMURHumgGAdlV2QSaA4n0s1NB1A6NzVbyqxpIOhYRLqUHVKu0gRT0Iz+qx/YWekAcAAcrDqosURfDPYcSg1LQexW6CCrBSFvomkGArSiXqyGLeRX1SHmMIlwGakEUjDK6vpC9pu25gS25aHuJKkmgLfRBQkKQakbbWdATwvzx8TY5jnSJHqUC9lua+nuKGk2fOFJ1pMf+czhGMegF28FkbluXOpaYTCrjs9Co59TO5RIVEIVAkFWSBWDfhz7EGZSC7shC9zIJ0iMDHUe6RI0Ea3PXIvkajQfR1NJEXm1eD4tyHcOkooLtEDPatZK3/YFtYRQ6WOhmk5ko/6jWTk3aQh8k2NJ8O9dFByPSpcSJoAOUaD+6xnPJrcnFKq09Lptr9hLEhfj148wMCrYf2wzRztj86H5hqgRvO2IDYmloaQC0hT5o8DZ5ExsQaz8WPTqQ7LI6GpvtNI3WRbo0g4CeFuUC5XJJDPPHy9THMMKyg7BpqePeAdWFUFs0MP5zGzZBD0nosssW6RJoDuyYJXqcMCgFHVSki6PkoharJLvMTpEu3yAISYKSfcdghprBhhAiTAjxrhBitxBilxBilhAiQgjxtRBin/EY3t/z6FXZ3LI697hb1j0Dn/wOvv6TfVF3Rw30vmIrrhUc12WXbWH0eHS3wCAW9PigeLsul2Ex3UW6jNAuF40j/gMsk1KOBiYCu4C7gOVSyhHAcuN5v5JdnU2wTzBhvmEuH5NTXk9S5xj03nToKtmr6nGv+S98/8+u+wsNQT9WNdDtYbPQgx1b6MejuwUGsaAnBCZQWFdIi7Vj/fOM7op0RY9SFrpuR6dphxAiBDgReAFAStkopawAzgVeNoa9DJzX33M5UnWE1OBUl0MWay3NlNU2dswSzV4LD6W2lZh1lZL9kHkBjF8Cy/8CG57vuL9gO4SmqO4/A0V4Kggvu2UHtIU+SIkLjKNFtlBcX9xhe4ifmaggX+ex6I01qg6ERtNGBlAMvCSE2CKEeF4IEQjESinzAYzHfs9Wya7K7lmEiy1ksb2FXrxbdefJ2+L6hRvroDIbokfDeU/ByEXw2e2w/d22Mce6Bro9fALhyo9gxq+67LIJ+vGYVASDWNAdhS6CjnTR9ApvYDLwlJTyBKCWHrhXhBDXCyE2CiE2FhcXd3+AAywtFvJr83sWg24vZNFSrR6Ld7t+8dL96jFqhMqsXrIUUufAB7+CPcugsVbd3Q60oAOkz1N9RTsRF6j86tpCH2S0JhfZ86MbRbrsYqu6WKwzRjUdyAVypZTrjOfvogS+UAgRD2A8Ftk7WEr5rJRyqpRyanR078UktzoXieyhoNupg94q6D0wXGxZ1Dajx+wPl72pBPx/V8H65xiQGug9IDEokXtn3svZw84e6KkMCINW0J1a6FFBlNc1UW6vSFdgtIpf1Ra6ph1SygIgRwhhS39cAOwEPgauMrZdBXzUn/PoTYRLTnkdAT5eRAS2S/TpjYVesk8tiLZvAOEXAj9/Ty1EfvNntc2DBV0IwcWjLibCr6v1fjwwaAU9wBxAqG+oXUEfFmMU6Spx0I7OtjCq0XTkt8DrQohtwCTgQeAh4FQhxD7gVON5v9Eag97DLNHk8ICOi6iWKvVYvBesdnIy7FGyV3X1MXdKTgqMhCs+UD05/cPbenNqPI5B14KuPc4aXQAcKKplSqqdb+qoEbD3q/6enmaQIaXcCky1s2vBsZrD4arDhPuGE+IT4vIxufbqoNss9KZaVTs83AWLv2Rfm7ulMyEJcO03qu3bsa6BrnGZQWuhg+PkoqRwf8xeggP2LHRQRYVqi6C+vJ9nqNH0jOzqnkW4SCnJsZdUZKlW9f/BNT+61Qql+5Sx44jgWEiY5PLcNMeeQS3oCYEJdhdFvb1MpDor0qUXRjUeSk+rLJbXNVHb2NK1sYWlus3X7YofvTIHmhscW+iaQcGgFvT4wHhqmmqobqzusi8jykmki80K0bXRNR5EfXM9RXVFPewj6qBsrqVa+bqDYl2z0G1rSs4sdI3H062gCyFeFEIUCSGyHOw/WQhRKYTYavz8yf3TtE9ckIo5tR+LHkR2WR3NLXYWhMJSVZF8Hemi8SBsC6K9q4Nux4fuG6zuRot3dX+iUpugawt9MOOKhb4UWNTNmNVSyknGz1/6Pi3XSAh0HIueER1IU4skp7y+64EmL2WJaJeLxoPIru55hEt2mZ0sUYCGKvANUVmfxXu6L3VRsldFsAS41vJO45l0K+hSylVA2TGYS49xFouu29FpBhu9ikEvqyci0IdA33YBa1YrNNos9NFGqYujzk9ki3DRESyDGnf50GcJIX4SQnwhhMh00zm7JdI/ErPJ7EDQbUW6nAh6xRFoaujPKWo0LpNdlU2kX2SP6njnltd17SPaaHzmbYIO3S+MluzV/vMhgDsEfTOQKqWcCDwGfOhooLvqXdgwCZMKXbTjcgkL8CEi0MdJpMtI1cbKVr9CoxlgehrhAmpRNMnegih0FPQiJ4JeXwE1hdp/PgTos6BLKauklDXG758DZiFElIOxbql30R5HyUVgi3RxVKTLCF3UC6MaD6GnMegtVsnRinr7IYugBD0wEgKinFvorUW5tKAPdvos6EKIOGHkHAshphvnLO3reV3FqaBHB9pP/weIHAYIXQJA4xHUNtVSUl/SIwu9sKqBphbpOEvU18g2jRnjPHSxc1EuzaDFlbDFN4EfgVFCiFwhxLVCiBuEEDcYQy4CsoQQPwH/BS6V8th1j4gPiqe4vpgma1OXfRnRQZTUNFJZ33UfZn+VDq37i2o8gN70EV17UNlNKV1cLkYdF5ugR49yHulSshdMZhXOqxnUdFvLRUp5WTf7Hwced9uMekh8YDxWaaWorojEoMQO+zKijCJdxTWckGKnw0rUKB3povEIjlT3LMIl62gld3+QxaTkMKand6pX1N7lAsqPbqlUdVjsNFamZJ+qsOg1qEs7aRjkmaLQLnTRSX9Rx+3oRir/Yac2dhrNseZIpRJ0V3zoRVUNXPfKRsIDzDx75RR8vb06Dugi6LZSFw786DrCZcgwdATdjh89JSIAb5NwHove3AAV2f05RY2mW7Krs4kJiMHf29/puIamFq57ZSOV9U08f9U0YoL9ug7qIuhj1KM992JLE5Qd1P7zIcKgF3Rbyyl7gm72MpESEeBCpIt2u2gGFldCFq1WyW3/+4ltRyv5z6UnMDbBQYndzoIeGAX+EfYt9PIjYG3Wgj5EGPSC7uftR4RfRO8iXWy3mUU7+2l2Go1rZFdld7sg+u/l+/hsWz53LRrNqWNjHQ+0VIE5UJW4AKOpy2j7seg6wmVIMegFHYzQRTs+dFCRLodL62ix2lnhD4iA+Emw9imo88jqBprjgOrGasot5U4t9I+2HuW/y/exZEoS15+Y4XAc0FaYqz3Ro5SF3jnSpVXQh/di5hpPY+gIupPkosZmK0ftFekCOOcxqCuFZS43eNdo3EpJfQkA0QH2k+02Z5fzh3e3MT09gr+dP75jqzl7WKq6CnrMGGiogJpOPa5L9kFQHPiF9nL2Gk9iaAh6kBJ0e+HvrZEujtwu8RNg3u2w7W3Y/Xl/TlOjsUulpRKAMN+wLvuqGpq4/pVNxIX48fTlU/DxduFf1pGFDl396DrCZUgxNAQ9MJ765vrWf4z22GLRDxQ5EHSAebdB7Hj49BbtetEccyosFYB9Qd9TUE1JjYU/nT2WiEAf105oV9BtRbraRbpIaQi69p8PFYaMoIP9SJeIQB9C/c2OY9EBvH3gvCeV6+WLO/trmhqNXWyCHurb1e1RUm0BICHMeThjB+wJelCscqu0b3ZRW6LcMNpCHzIMDUEPUoKeV5vXZZ8QgtFxwezM62q9dzzJBDjxD7D9Hdj1aX9MU6OxizOXS0mNEvSoYBetczAEvVNIoxAqHr29hd66IKoFfagwNATdsNALagvs7p+QFMqugmqa7LWja8+821Rj3U9v1a4XzTGjwlKBt/AmyBzUZV9xtQUhICKgJ4JuZ1EU2iJdbOiQxSHHkBD0cN9w/Lz8HIYujksMpbHZyt7Crs2kO+BlhvOegvoy+PwP/TBTjaYrFZYKQnxD7EavFNc0Ehnog7eXi/+qUtp3uYDyo9eVKlcLqAgXb38ISerD7DWexJAQdCEEcYFxdl0uAOMTlW8y62g3bhdQFvqJd0DWu7DrE3dOU6OxS6Wl0q67BZTLJSrI1/WTNdWpxi1+drJIbZEuRYYfvXSfij83DQkZ0DBEBB1UUSNbT8bOpEUGEuTrzXZXBB1g3u8hboJyvdQes9LumuOUSkul3QVR6IWgd077b0+MraaL4XbRES5DjiEj6Okh6RypOkKLncqJJpMgMyGE7UerXDuZlxnOf1rdmm580c0z1Wg6UmGpcCjoxdUWooJ6uCAKXRdFAYLj1fbiPaqXbvkRLehDjCEj6BlhGVhaLE7dLrvyq7pfGLURm6l8jjnr3DhLjaYrFZYKuy4XKSUlNRaig3tioduaW9ix0IVoWxgtOwBIHeEyxBg6gh6q6lscqjxkd//4JLUwuq/QSYJRZ5KmQu4Gx51eNBo34MiHXtvYQkOT1X0uF2gTdB3hMiQZMoKeHpoOOBb0cT1ZGLWRPF0lXtia6Go0bqa+uR5Li8VpUlGPBL3BiYUOKha9thiy16rnEcN6Ml2NhzNkBD3UN5QIvwgOVh60uz+9pwujAEnT1WPOejfMUKPpirOkouLWpCJ3WuhGCYBdn0JoCvgE2B+nGZQMGUEHZaU7stBNJsHYhJCeCXrUSPANVW4XjaYfcFbHxWahR/fK5eKg+YUtdLEqV/vPhyBDStAzQjM4WHnQbtVFaFsYbXZ1YdRkgqQpWtA1/YbTOi69TfsH8OmadaoulNS2T/vPhxxDStDTQ9OptFRS1mA/bX98YiiWZiv7nFVe7EzSdNXRyNJNlqlG0wucWejFNY29S/v39lMF5+whRJuQawt9yDGkBL27SBfbwmiP3C7J01Tm3dFNfZ6fxvMRQngJIbYIIT41nkcIIb4WQuwzHsPdeb3KBic+9GoLEQE9SPsHx2n/7bElGGkLfcgxJAXd0cJoRlQggT5ePYt0SZyiHrXb5Xjhd0C7GrPcBSyXUo4AlhvP3UZ3LpcexaCDa4IeOw6Eqc2frhkyDClBjw2Mxd/b3+nCaGZCaM8sdP9wiBoFOVrQhzpCiCTgLOD5dpvPBV42fn8ZOM+d16xsrMTf2x8fr64ukh6n/YNrgj71F/DLbyAopmfn1ng8Q0rQTcJEWkiaQ0EH5Xbp0cIoKLeLTjA6Hvg3cAfQ/sMRK6XMBzAe7aqgEOJ6IcRGIcTG4uJily/YfWGuHvjPwX4t9M6Y/dvuPDVDiiEl6OA8dBFgfFIIDU1W9hf3ZGF0miqpW2bflaMZ/AghzgaKpJS9WiyRUj4rpZwqpZwaHW2/2bM9nKX9qzouvbHQuxF0zZBlyAl6RmgGebV51DXV2d1vK6W7PVcnGGk6MAc4RwhxGHgLmC+EeA0oFELEAxiPRe68qKPCXLa0/5770B00t9AcFww5QbeVADhcddj+/qggAnq6MBo9Wlk9uVrQhypSyj9KKZOklGnApcC3UsrLgY+Bq4xhVwEfufO6jlwuvUr7B9d86Johy5AT9O5CF71aS+n2QNBNJkicrCNdjk8eAk4VQuwDTjWeuw1HFnpJb9L+pdQW+nHOkBP0lJAUvISXw9BFUAujO3u6MJo0HQp3gKUHvnfNoERK+Z2U8mzj91Ip5QIp5Qjj0W3NZlusLVRZqhzGoAM9WxRtbgBrsxb045huBV0I8aIQokgIkeVgvxBC/FcIsV8IsU0IMdn903QdHy8fkoKTnC+MJobS0GTlQHGt6ydOnq4SjPI2u2GWGg1UN1YjkfZdLoaF3rNa6N0U5tIMeVyx0JcCi5zsPwMYYfxcDzzV92n1jW4jXXqTMWoL89ILoxo34SypqHdp/90U5tIMeboVdCnlKsDZbea5wCtSsRYIs0UFDBTpoekcrjpMs7XZ7v6M6F4sjAZEQOQIyN3opllqjnecVlqs6U3afze10DVDHnf40BOBnHbPc41tA0ZGaAbN1maO1hy1u9/LJBgb38OFUVBul9z1OsFI4xac1kLvbQw6aEE/jnGHoAs72+wqXm+z6XqKLXTxYEU3C6N5VbRYeyDOSdOgrlQnGGncQmWjEnS31nEBLejHMe4Q9Fwgud3zJMBup+beZtP1lNbQxSrnfvT6phYO9DRjFLTbReMWKhoqAMeC3qu0f9CCfhzjDkH/GLjSiHaZCVTaal8MFME+wUT7Rzu10Mcn9SJjNGYM+ATrBCONW6iwVGASJoJ9OgqwlJKS6sY+uFz0oujxiithi28CPwKjhBC5QohrhRA3CCFuMIZ8DhwE9gPPATf222x7QHpoulMLfVh0EP5mrx4mGHmpBCNnkS7NFtj1CVhbejBbzfFIpaWSUJ9QTKLjv2FtYwv1TS09SyoCvSiqwbu7AVLKy7rZL4Gb3DYjN5Eems7nBz9HSokQXd38XkaP0R5FuoByu3z/L2isBZ/Ajvss1fDWz+HQSrjgOZhwcR9egWao4zBLtDe9REF9/rx8wOznjulpBiFDLlPURnpoOtVN1ZTUlzgcMz4xlB2lOymrr3D9xMnTQbZA3paO22tL4eXFcPh71QLs0MreTVxz3OCwjktv0v5B13HRDF1B766mC0BydCNeSY/z1zUPu35i28Joe7dLRQ68eDoU7YJLX4fhC5WwazROcFQ6t1XQe1ULXQv68cyQFfTW0EUnNV0ONH6BEC2syV/pMAmpCwEREDGsrVBX8R4l5jVFcMUHMOoMSJsH5YeV0Gs0DnDkcimuaQR64XJp0IW5jneGrKDHBsQSaA50aKFXNVaxPPcjZFMYdS1VbCzsQShi8nQl6Lmb4MVFqiDSLz6D1Nlqf9pc9aitdI0THLlciqstKu0/sB+6FWmGNENW0IUQpIekO7TQ/7fnf9Q11zEn5Bak1cxnB750/eRJ06C2GJaeCX4hcM0yiBvftj9mLPhHwOHVfXwVmqFKQ3MDDS0NhPmFddnXq7R/0KVzNUNX0MFxka7GlkZe3/U6s+JnceOsBTTXjOarw9/Q4mqoYcpM9Rg5HK75EiIyOu43mSBtDhzSgq6xj7PCXCW9SfsH7UPXDG1BzwjLoLCukNqmjmVyPzv4GcX1xVw97momJIUS5zWdupYKNhe6WBo3NhOu/Bh+8TkEx9kfk3YiVGZD+ZE+vgrNUMRWxyXUx0GWaHAP3S2gBV0ztAU9PUQtjLa30q3SytIdSxkdMZpZ8bMQQnDFpEVIqzdv7fzM9ZNnnAR+Xf8Z2y4+Tz1qt4vGDk4Lc9VYer4gClrQNUNc0MO6Cvqq3FUcrDzI1ZlXtyYcXTx5GLJuFCuPfotV9qCLkTOiR0NAlF4Y1djFuculF2n/zRZosWhBP84Z0oKeHJyMt/DusDD6UtZLJAQmcFraaa3bgv3MnBB5EhZZztqjbupIJISKdjm0Wpfb1XTBUS30WktzL9P+jSJzOsrluGZIC7rZZCY5JLnVQv+p+Cc2F23mirFXYDaZO4y9ccZipNWL5ze7sal72lyoylUx6RpNO1pdLp2iXNqSinQdF03PGdKCDipj1GahL81aSohPCBeMuKDLuFlpifi3jGFz6Sqkuyzq9BPVo/ajazpRYanA39sfX6+Owm1rDq1roWt6w5AX9PTQdHKqcjhQcYDl2cu5ZNQlBJgDuowTQnBK0gJaTGV8tGudey4eNRICY3T4oqYLDgtz9SXtH7TL5ThnyAt6RmgGzbKZv637G2aTmZ+N+ZnDsTfPOg8pTSz96WP3XNzmRz/8vfajazrgMEu0t2n/2kLXcBwIuq2my4aCDSwetpgo/yiHY5NCo4j2ymR/7RqqG5rcNIF5UJ03MG3rDqyADS8c++tqusVZ6dzepf3bfOjaQj+eOW4EXSC4KvOqbscvHrEIYS7lhfVuCjdMG8B49FWPwDf36bsDD8Sxhd6HtH/QFvpxzpAX9EBzIGkhaSxMXdgq7s64auJZIAXv7f7CPROIHA5Bccfej95sUb1PLVVQ67gmvGZgcFg6ty9p/6AF/Tin245FQ4Gli5baXQi1R6R/JCkB4znUuJHtuRWMTwrr28Vb/ehGPLqd7kn9Qt4WlWgCUHYAgvqvKbemZ1illarGKkJ8urpH+pT2L7zA7O+GGWoGK0PeQgcl0v7ern/Ql4w5Cy/fYp5d+6N7JpA+D2oKoXS/e87nCkfWtP1eeuDYXVfTLdWN1Vil1UFzi15kiUJb2v+xMhg0HslxIeg95ezhpwGCFTnfUGtxsfGFM2x+9EOr+n4uVzmyRjXiEF7KQtd4DI6SikDFofe+joteED3e0YJuhyj/KEaGjscasI0Ptx7t+wkjMiA44djVdbG2QM46dWcQnqotdA/D7Wn/oAtzaQAt6A45f+QZePkV8MT3a2hq6WPBLiGUuB6rePTCHWoxNGW2stLthEw+uvFR7vn+nv6fi6YLjgpz9TrtH3RzCw2gBd0hC1MXAlAi1/HhFjdY6WlzobZI9SDtb7IN33/qLIg0BL3TF8nK3JWszF3Z/3PRdMFR6dxeZ4mCttA1gBZ0h8QFxjEnYQ4BkRt5bMUemvtqpfclHv3gd/DuNdDioj//yBoITYawFOXuaaxRTawNmqxN5FTlUGGpoLyhvOfz0fQJRy6XXtdxAS3oGkALulMuG30ZLaZK8ho38vFPeX07WXiaEtmeCnpdGbx3HWS9B4ddWFSVUgl6yiz1PGKYemy3MJpTnUOzVF8Odptof3gjfHl3z+Y5yBFCJAshVgghdgkhdgghfmdsjxBCfC2E2Gc8hvf1WhWWCkzCRLBPRwHuddo/aEHXAFrQnTI3cS4JgQmExa7n8W/302Ltg/+7t3VdvrgD6svAHADb3+t+fNlB5dpJNQQ90uh32m5h9FBFm4h3aaItJez6FHZ84PochwbNwG1SyjHATOAmIcRY4C5guZRyBLDceN4nKi2VhPiEYBId//16nfYPWtA1gBZ0p3iZvLh41MVYzPs4XHWQT7f10UpPmwd1pbDnc9fG7/oEtv8PTrwDxp6rnjdbnB9jiz9Pma0eQ1PA5N3BQj9UpQTdbDJ3tdArc8FSCVVHoSrftXkOAaSU+VLKzcbv1cAuIBE4F3jZGPYycF5fr+UwS7TGQnhv0v5bmqCpznlLRM1xwXGRKdoXLhhxAU9ufZKAxE089u0wzp6QgJepl8kbmefBuqfh3Wvhqo8hebrjsbWl8OmtEDcB5v1e+dF/ehP2L4fRZzo+LvtHCIiE6FHquZe3cve0i3Q5WHGQ2IBYwnzDugp64Y623/M2Q8hZPX2Vgx4hRBpwArAOiJVS5oMSfSFEjINjrgeuB0hJSXF6fkeFufoUgw7aQu9EU1MTubm5NDQ0DPRUeoWfnx9JSUmYzebuBxtoQe+GcL9wTk87na8OL2f/kQV8vj2fxRMTencyn0C4/D144TR4fQlcswxixtgf+8UfoL4CrvgQvMyQcTL4R0DWu84F3eY/b58xGDEMStsJeuVB0kPTCfMNY3vJ9o7HF2apR+GlasGMPr4EXQgRBLwH3CKlrBIuZl5KKZ8FngWYOnWqU59alaWKmICu3wt9SvsHLeidyM3NJTg4mLS0NFz9O3oKUkpKS0vJzc0lPb37GlQ2tMvFBS4dfSkWax0JiTt47Nt9WPviSw+KgSs+AG9fePUCqMjpOmbnx2oR9KQ7IG6c2uZlVm6XPV9AY639c1flQ/mhtgVRGxEZraGLUkoOVR4iIzSD9NB08mryaGhuZ8EUZimLPm4cHN3U+9fZ3xzdBE/MVDVr3IQQwowS89ellO8bmwuFEPHG/nigyNHxruK4uUUf0v5BC3onGhoaiIyMHHRiDqrhTmRkZI/vLrSgu8D4qPGMjRyLf9Q69hZWs2xHQd9OGJEOl7+vhPm1C5R7xUZtiXK1xE+Eubd2mshFyle6x0ElyGzDf57aSdAjh0FTLVQXUFhXSF1zHRmhGWSEZiCRHKk60ja2cAfEjoPEKUosrX0M1+wvstdB8S4IinXL6YT6r38B2CWl/Ge7XR8DtrrLVwF9bjrrrFuRFnT3MhjF3EZv5u6SoAshFgkh9ggh9gshuqzyCyFOFkJUCiG2Gj9/6vFMPBghBJeOupSihiMkxefz3+V9tNJBWcA/ewsqsuGNJW1d2z+/HRoq4bynlFXenpRZEBwPWe93PR/AkR/BHAhxEztujzAiXcoOtEa1pIemt5YTbvWjN9WrAmKxmUrQLVVQuq9vr7O/yFmnFnxDeun+6soc4ApgfrvP8ZnAQ8CpQoh9wKnG817T2NJIfXO93bT/usaW3segg67l4oEUFBRw6aWXMmzYMMaOHcuZZ57J3r17WbRoEWFhYZx99tluvV63gi6E8AKeAM4AxgKXGeFcnVktpZxk/PzFrbP0ABalLyLEJ4Sk1C3sLqjm612FfT9p6my46CXI24p8+3IqN7+iwgVPvlOJamdMXpB5Puz/WvnXO5P9o1po9eq0NBJpxKKXHmgV74ywDFJDUhGINkEv3g3Sagj6VLXNE90uUipBd7ao3ONTyu+llEJKOaHd5/hzKWWplHKBlHKE8VjWl+s4Sirqc9o/aAvdw5BScv7553PyySdz4MABdu7cyYMPPkhhYSF/+MMfePXVV91+TVcs9OnAfinlQSllI/AWKpTruMLf25/zh5/PnqofSYlu4r/L9yHdUZdl9Jmw+D98VLSeU7Y9TEH8eJhzq+Px4y6ClkbY/WnH7fXlyl2SOrvrMaHJ4OUDZQc5VHmIYHMwkX6R+Hn7kRCU0BaLbotwiR0HUSPAJ7hngv7l3artXX9TmQPV+ZAys/+v5Wa6r+OiF0WHCitWrMBsNnPDDTe0bps0aRLz5s1jwYIFBAe7/+/lSpRLItB+5S4XmGFn3CwhxE9AHnC7lHKHnTGDmktGXcLLO19mwpjdfLpqPFe/tIEzx8excEwskb2xrAzkCZfzyp7naWosY83US7mgs4XdnsTJatEy6z044fK27dnrANl1QRSUZR+eBmUHOGT1JT0svdU/lx6a3mahF+5QCUzhaeqYhEkq0sUVSg/Aj4+rWjXDTnHtmN6SvU49utFCP1Y4quNSXK2yRLUPvX+4/5Md7Myrcus5xyaE8OfFdu6kDbKyspgyZYpbr9kdrljo9jzznU3TzUCqlHIi8Bjwod0TCXG9EGKjEGJjcXFxjybqCSSHJDMncQ47ar7ihpNS2V9Uw53vbWfa377h4qd/5PnVBzlS6iACxQmbizazr1Hdya+tzXY+WAgYdyEcXAk17d7D7DVgMkPSVPvHRWRA6UEOVh4kIzSjdXNGaAaHqw5jlVYV4RIzRok5qHMVZkGTCyvte79Uj4e/d218X8hZBz5BEOP4n8lTcVjHxbDQY3rtQxdq/URzXOOKhZ4LJLd7noSywluRUla1+/1zIcSTQogoKWVJp3Eux+p6KpeNuozffPsbTph+lDsXncbO/Cq+2lHIVzsLeeCzXTzw2S7GxIfwn0snMTLWNYvprd1vEWwOZnr8dNblr0NK6XyFe9yFsPpR2PkhzVN/QV1zHSFHflTWu6MWZBHDqDq0ipLAqA69VdND07G0WMirPkpSQRaMabdIkzgFrM1QsB2Spzl/EXuXqYzU5nrly+9PKz1nrZqbszsZD8Why8Udaf8mHbTmCGeWdH+RmZnJu+++e0yv6conYAMwQgiRLoTwAS5FhXK1IoSIM8K+EEJMN85b2uVMQ4C5iXNJDErk7T1vI4QgMyGUW08dyRe/m8fqO07h3rPHUlxt4dqXN1BW29jt+UrqS/jmyDecO/xcTk4+mbKGMvZVdBNZEpsJ0WMg632e3Pok53ywmOa8LfbdLTYiMzhkUgW52lvorZEuBZtVzZjY8W3HtC6MduN2aaiCIz/AlKvVXcKBb52P7wuWauUaSrbn9fN8nJXO7VXaP+g6Lh7K/PnzsVgsPPfcc63bNmzYwMqV/Ve2uttPj5SyGfgN8CWqvsU7UsodQogbhBA2b/9FQJbhQ/8vcKl0y4qh52Gr77KhYAPr89d32JccEcC1c9N57sopFFZZ+PVrm2hsdh7H/e7ed2mWzVwy6hJmxqtFvrV5a7ufyLgLkdlr+PzAJ5Q2lLHLW9hfELURMYyDRgpxewvdJu6H8jeoDe2ja0LiVael7hZGD3yrLPnMC9RCZX8K+tFNKhInZXAKekVDBX5efvh5+3XYrmLQe2Gdg25u4aEIIfjggw/4+uuvGTZsGJmZmdx3330kJCQwb948lixZwvLly0lKSuLLL790yzVdumeVUn4OfN5p29Ptfn8ceNwtMxoEXDD8At7c/Sa//OqXLBm5hJsn39zhFvqElHAevnACt7y9lT9/nMWD54+360Jptjbzv73/Y1b8LNJC0wBIC0ljXcE6rsy80vkkxl3Avu//ztE6leS0wd+P8c6s1shhHDKbMQsvEoMSWzeH+4UT5hvGwdLdakNsp4jUxMndC/q+r1RhqOQZMGw+LL8fqgsgOM75cb0hex0gIKkbF5CHUtlY6biOS2/852AIuo5B90QSEhJ45513umxfvboXfRFcQDvdekGYXxgfnPMBPx/zc97d9y7nfHgOHx/4uEMY43knJHLjycN4c30OL685bPc83+V8R1FdEZeOvrR124z4GWws2EiTtcn5JCKH8W1cBkJCNF5sDI0C/zDH40OSOOTjS6pXIN6mjt/j6aHpHKrNg5Ak8O9U7jtpqiobUOcg/NpqVQuiw09VPu3hC9T2/gpfzFkHMWMHbWVBt6f9g3a5aFrRgt5LgnyCuHP6nbx99tskBydz9/d3c/Wyq9lfvr91zO2njeLUsbH85dOdrNrbNarnrd1vER8Yz0lJJ7Vumxk/k7rmOrJKsrqdw4rAQCZYLJxSXc1mb0mz1UlHI5OJg35+pFu73ilkhGZwuKXGfjJTohF2dXSz/fPmbYa6Ehi5SD2PHQ8BUf3jdrG2QO6GQRmuaKPSUumwdK4WdE1f0YLeR0ZHjOaVM17hvln3caDyAEs+WcI/N/6TxpZGTCbBvy5R0S43vbGZA8U1rccdrDjIuoJ1LBm5BC9bmCAwLW4aAtGtH72gtoCdlhJOqatjWn0dtbKF3WW7HY5vbGkk1yTJaKjrsi89OJkyIamIGt71wPhJgHDsdtm7DISpzTI3mZTb5cC37q8DU7zbaH49+BKKbNiz0Cvrmnqf9g9a0DWtaEF3AyZh4sKRF/LJeZ9wzvBzeGnHS9y84mYsLRaCfL157sqpmL1MXPfyRirrlCvl7T1vYzaZuWDEBR3OFeobytjIsazNdy7oK3KUS2N+6GimGhXZNhY4jkY5UnUEK5BeXdJFaNNRi6WHQqK6HugXAtGjHUe67F0GyTMhIKJt2/AFymov2Ob0NfSYbOM9GUIWekmNhStfXIdJwJTUXna3s1RrH7oG0ILuVsL9wrl/9v3cN+s+1hxdw83f3kxDcwPJEQE8ffkUcsrr+NVrG3ln037e3/cRU6NPpqLGl5IaC03tmlDPiJ/BtuJt1DV1taZtfJv9LWkhaaSffA9RM35DWkgaGwo3OBxvS+/PaKhT3YjakV6vrnPIx4GFmDjFiC7pFLhUeVTFqI88veP2DCMG3d1ul5z1EBgD4a7Xh/YkpJQdBP1IaS0XPbWGPYXVPHPFVKalRTg/gT2sLaoJuLbQNWhB7xcuHHkh98++nx/zfuQ33/6G+uZ6pqdH8Lfzx7P+UBl3f/0KDS21fLNuOAseXcnUB75hxN1fMPPB5Xy3p4iZ8TNpls1sKrTv5qhqrGJjwUbmp8xXjS9O+yvT4qaxuXCzQz+6Lb0/ram5Q/cigITyHHyk5GCLgyzXpCmqdV7FkY7b9xmhVp0FPThW+dLdLuhGQa5BWhK1uqmaFtlCqG8o23IruODJNVTWN/H6L2dy6thelgFuNNx4WtA1aEHvN84fcT4PzH2A9fnr+c3y31DXVMfFU5PZdM9CRo3cRkrQCJ6/+EL+fckk7j8nk9+fOpKwADO/WLqB9btC8DH5OHS7rM5dTbNs5pTktmzMaXHTqGmqYU/ZHrvHHKw8SIJ/DP5SdugvCuBVtJM06cWh6iN2j21dGO1c12XvlxCWolwynRl2inKRWGq67usNNUVG847B6z+vbFBJRQXlJi59di3+Pl68++vZvXe1gK7j4uHYK5+7fv16Zs2aRWZmJhMmTODtt9922/W0oPcj5ww7hwfnPcjGwo3ctPwm6prqOFiTxZHqA1wz/ufMHxPLeSckctXsNG5eMIL3b5zN4gkJ/Ovrw/hbh/Gjg4XRFTkriPSLZEL0hNZtU2NVVufGQvu+7sOVh0kPHwHefqqQVnsKd5DuG8HBioN2jyVmrDqufaRLU72qJzNykX2LefgCsDap2i7uIMdWkGtwJhRBW9r/CyuLSIsM5P1fz2ZYdFDfTqoF3WNxVD63vr6eV155hR07drBs2TJuueUWKioq3HJNLej9zNkZZ/PQvIfYUrSFX3/za5buWEqwOZgz0s/oMjbAx5v/XDqJe84aQ3FxCvsq9rI5t2OxrsaWRlbnrubk5JMxibY/X3RAtPKjF3T1o1ullUOVh1SGaHh6R5dLTTHUFJIenMrRmqNYWixdX4SXWUW7tI90ObRa1W3p7G6xkTwTvP3d53bJXgtevqqT0yBESslrG3YCkBkXz9u/mklMiF83R7mAbm7hsTgqn3vSSScxYsQIQCUexcTE4K5ihYOvutEg5Iz0MzAJE3euupMW2cLlYy4nwBxgd6wQgl/Oy8A/6Fwe2vYlV73xJv9efDULxigf6/qC9dQ11yn/eSemxk1l2aFltFhbOoRC5tfm09DSQEZYhmp2UdKuVkyRqnKcET0eWbaJI1VHGBk+suvEEqfAxhehpUkJ/N5lqrpf6lz7L9rsB2lz4cByF9+lbshZDwknqF6sg5DCKguf7zgAMfDw+TMJ9nO9k7tTdHML1/jiLrWA707ixsMZjhtYuVI+d/369TQ2NjJs2DC3TElb6MeI09NO5x8n/YNR4aP42ZifdTv+0omzCfQOIij8ENe+vJF/frWHhqYWvs3+Fn9vf2bEd3U9TItVfvTd5R3j0W0Loukh6aqMbvkhFR0BrU0t0pPnAG3RMF1InKws8qKdKtpl75fKT252YmUOX6Ba2pU78M27SlMD5G8d1OGKcaF+XHeyKoUQHdCLaBZHaJfLoCU/P58rrriCl156CZObKmVqC/0YsjB1IQtTF7o01svkxYz46ewu28PsyUn899v9/G9TNqQsZ07CXHy9ulqqU+MMP3rBRjIj27I+bb7xVgu9pVGFLoalKEEPiiU1dmLHdnSdMeqslx/5Hj9rM/5VuapVnjOGGXcRB76Fqb9w6XXbJX+rmvMgXhAF8DLXIxAE+7hRfBu0he4STizp/sJZ+dyqqirOOussHnjgAWbOdN/nWlvoHsyM+Bnk1R7lljMieP2XMwgJLaCmuYz1OxJYllXQpQVeTEAMqSGpXRKMDlUdIsw3jAi/CIho6y8KqAYWsZn4e/uTEJTgWNDDUqkLjOTCvS9y74/3qW0jTnP+AqJGqvow3bldussotS2IJg1eCx1UpcVgn+AO7rA+oy10j8VZ+dzzzz+fK6+8kiVLlrj1mlrQPRhbOd11+euYMzyKM2aUYsKET+NYbnhtE+c9uYY1+zv0EGFq7FQ2FW6ixeZSQVnorSVzI4xa6GUHoKUZina31nBJC01zLOhC8FpcKsWyka9rDpMXP777aopCKLfMwVXqWvbY+gb8PRVW/L+uiUs2stepL6KgaOfX83Ac1XHpE1rQPRZH5XNXrVrFqlWrWLp0KZMmTWLSpEls3brVLdfUgu7BpIemE+Mf0xqPviJnBdPip/H17xbx8IUTKK5q4GfPr+OKF9a11omZFjeN6qZq9pS3xaMfqjzU1tQiOB68/bGWHKCpeC+0WFRTaJSP/XCl0Y6uE5WWSpbKSiY1WBBI3opOcO1FDF8AlsqutWCaLfDJ7+DDX6t2cisfgmV/7GqtS2kkFA3ecEUbFZaK/hF0n6C2toEaj8JWPvfAgQPs2LGDzz77jHvvvZempia2bt3a+jNp0iS3XE8LugcjhGBG/AzW56/nYKXqB3pK8il4e5m4eFoy395+MvecNYatORUs+vcqHl62m3ERJwBtdV3KG8opt5S3WuiNVij3S2LNhvX87UXDv2dY6BlhGTS0NFBQW9BlLi9kvUCNbOZPJWXMr6vn3fojTksTtJJ+kire1T58sSIHXlwEm5bCnFvglm0w49ew7in45LdtC7ZglO4tGbQNLdrjqHRun9DNLTTt0ILu4cxMmEm5pZxnfnoGgPnJbeGKfmYvfjkvg29vO5nFExN48rsD/Ozp3UT5JrTGo9tcKCnBaby1PptT/vEdayvDSBMFpDYfokl68WWBimFOD1Gi3znSpbC2kDd2vcHZqacyoqmJyxu9qW6u47NDn3X/AgIikAknsOzgZ+TV5MH+5fDMiSr65ZLX4dT7VRjkov8HJ90JW16Dd6+BZqN93xBIKLLRby4XLegaAy3oHs6MOCVknx/6nDERY4gPiu8yJjrYl39ePIm3r59JoK8XeQWJrM5Zz6GSavaXq8XPu98p4q73txMV7EvmuBNIlIX8LKWCo97J/OqtLB79ag+pwWkAXfzoz2x7hhbZwo1TboXEKZww+kLGRIzhjV1vdFmYtce3CaP5g3clP//gXPa8fanyvV//XceG1ELAKf8Hp/4Vdn4Ib/1MZaPmrFPNLKJG9er98yT6x0LXgq5pQ4ctejixgbGqo1DlIU5JOcXp2BkZkXx28zzu+vIAXxVv4Iwn3yEwaivS35sI31geuHoUp4yKQWw5ALua8M1dQ/KYxVxMEo99u5+d+ZWE+IR2EPTsqmw+2PcBF428iKTgJPjlcgTwswMfce8P97KuYF3r4q096prqeKh6BxmNTdSYmvlFUiKPL/wHkyMdJFLMuVkJ1Ke3wmsXqlZ2SdMHfUf7ppYm6prrtIWu6VcG93/JcYLNSm/vbnGE2cvEH046E4CxGUWY/UpIDEzlk9/MY/7oWNXb1Ba62NyAV9w4/n7hBO4/J5Pv9pRQXxvJznaZpI9vfRyzl5lfTfyV2iAECMEZ6WcQ4RfB67tedzqfp7c9TYGljPtDxvPq6OuIDEni+hW/Y1XuKscHTf0FXPg85KyjrOLQkPCfm4SJdxe/y3nDz3PvibWga9qhBX0QcGXmldwx7Q77Kfl2iAuMIyU4haSEfMJCy5kQO6Jjk2pb6CJA7DiEEFw1O43Xrp1BsyWaHcX7eWdjDlsKdvDFoS+4fMzlRPl3bH7h6+XLRSMvYmXOSnKqcuzOY3/5fl7d8SoXjLiASZf8j4Q5v+flM15hWNgwbv72Zj458Ind45qtzXwZHMwVmbM4KTWJd/x9XHrdnoyXyYtREaOIDexlmVxH6OYWmnZoQR8EJAcnc8XYKzqKcjdMjZvKhoIN5NXktYUs2giOU3VYoEMf0VnDIrlm+nTwquGO99dy+fv34U0gyaYzaGhqoTOXjLoEL+HFm3ve7LJPSskD6x4gyCeIWyff2ro9wi+CF09/kamxU/m/7/+P13a+1rqvqrGKpVlLOfP9M7l95e2U0EJmZCZ/3/2K0/Z6xzXaQvdo7JXPXblyJVOmTGHSpElkZmby9NNPu+162oc+RJkaO5X3970PQHpYpw4/Qigrvepol+SgE+JGwU64ZlEh/zu0G1lxFre+tZd7fQ9y6thYFk+MJyMqCEuzlcZmX6ZEn8T/9rzPuIAlCKsfjS1Wmlskm8u+ZlPhJk6L+Q3vbijDKktZMCaWYdFBBJoDeWLhE9y16i7+vuHv5Nfm09jSyEcHPqK+uZ5pcdO4a/pdnJR0EpWNlSz5eAl/WPkH3jr7LQJtX0QaFaOvwxY9Flv53Kuuuoq33noLgK1bt1JZWcmaNWvw9fWlpqaGcePGcc4555CQ4GJuhxO0oA9RpsVNa/3dFo7YgXEXQH1Zl1rmNmv+wyMvEu0fzUeX3stP2fV8ui2PL7IK+GBLx/Z1Jr9RBKYv53efvkBT+SxjYx2Bw55BNqbw3soEYBcADy/bw+UzU7ll4QjCAnz5x0n/4K9r/8orO1/BbDJzZvqZXD72ckZHtDXMiPCL4KETH+KXX/2Sv679K/9v7v/r0Z3KkKaxBpBa0D0UR+Vz22OxWLC6sZm6FvQhSlxgHMnByeRW55IWmtZ1wLzf2z0uISgBs8lMk7WJGybeQLBvIHNHBDJ3RBR/OXccaw6UUFbbiK+3F77eJnzN03lk+woaArbwrzm34+vtzbM7H+bL7AaePu0hRkWMwttLUGtp5rFv9/PKj4f5YMtRfrdgBFfMSuXPs/7MgpQFjIkc08FPf7C4hmU7Clh3sIyEMH9mR1zGZwdfZ3L0NC4efWE/vWuDDJ327zJ/X/93t7vtRkeM5s7pjgvUOSufm5OTw1lnncX+/ft55JFH3GKdgxb0Ic385PlsLtpstzKjI7xMXgwLG0ZtUy3njzi/wz4fbxMnj4rpckyl15X8cfUfKZdZhIpQlh35kMvHXs6s5PGtY0L8zDx4/niunJXK3z7bxV8+3clra4/wf2eOYcEYVVN9Z14Vy3YU8GVWAXsKlVgNjwliS3Y5VQ2Z+KcM4y8//o2nvmxiYuwoMhNCOWdSArHuaBQxGNHNLQYtycnJbNu2jby8PM477zwuuugiYmP7vmCuBX0I8/upv3cp8aczfz/x75hNZswm15ownJ56Oo9ufJRXd75KeUM50f7R3DTpJrtjR8eF8Mo101mxp4gHPtvFL1/ZyJTUcIqrLWSX1WESMC0tgj8vHstpmXEkhvkjpSS3vJ4fj2TwSNb11IYu5cdDv+PDrXnMGhY5eAR950eQMguCun4p9or6CvWoLfRucWZJ9xfOyufaSEhIIDMzk9WrV3PRRRf1+Zo6ymUIYxKmXpVqzQjNIDk42eXxZi8zF4+6mDV5a9hVtos7pt/hdPFSCMH80bF8ecuJ3Ld4LMXVFjKiA3nogvGsv3shb/9qFr+Yk05imH/r+OSIAC4+IZP/zH+EenGUM05ax6Z7FjI6rv/FTAixSAixRwixXwhxV69OUlsC/7saHh0Nr14AP73VuwbaLc2w72t47zp49Ty1LcjNoZAat+CsfG59fT0A5eXl/PDDD4wa5Z5MaG2ha9zCkpFLeH7b80yNm8ppqd3USTcwe5m4ek46V8+xs2jrgNmJs/nl+F/y/PbnmR43nTMzzuztlF1CCOEFPAGcCuQCG4QQH0spd/boRIFR8OsfYfs7sP1/8MGvwBwAo86ECRerZiBeDu6IpFTVKre9A1nvqWJlfmHquImXQcKkPr1GTf9gK597yy238NBDD+Hn50daWhrnnXcev/3tbxFCIKXk9ttvZ/z48d2f0JVr9uaW3B1MnTpVbtxov0O9ZnCyp2wP8UHxhPj0r0+32drMNV9ew56yPbyz+B1SQ1K7jBFCbJJSTu3rtYQQs4D7pJSnG8//CCCl/H+Ojun2s20rCbztbdjxAdSXg3+4Y0vbUq1CTL18YdQZSsiHLxy0/VWPFbt27WLMmDEDPY0+Ye81OPtsawtd4zZGRRybAlreJm8ePvFh/rzmz5hEv3sNE4H2qbC5QJdaBEKI64HrAVJSUpyfUQjVTi9lJiz6u+rotOtTaKy2P95kVo1CxixWhco0Gge4JOhCiEXAfwAv4Hkp5UOd9gtj/5lAHXC1lHKzm+eq0bQSFxjHM6c+cywuZS/ovcttrZTyWeBZUBa6y2f39lFW96gzej1BjcZGt+ZNOx/iGcBY4DIhxNhOw84ARhg/1wNPuXmeGs1AkQu0XyFOAvIGaC4ajVNcuV+dDuyXUh6UUjYCbwHndhpzLvCKVKwFwoQQXQt3azSDjw3ACCFEuhDCB7gU+HiA56RxkYFaI3QHvZm7K4Juz4eY2IsxGs2gQ0rZDPwG+BJVw+AdKeWOgZ2VxhX8/PwoLS0dlKIupaS0tBQ/v57lWLjiQ3fFh+iSn7FHC0cajYcgpfwc+Hyg56HpGUlJSeTm5lJcXDzQU+kVfn5+JCUl9egYVwTdFR+iS37GXi8caTQaTQ8xm82kp7ue4zAUcMXl4ooP8WPgSqGYCVRKKfPdPFeNRqPROKFbC11K2SyEsPkQvYAXpZQ7hBA3GPufRt2OngnsR4Ut/qL/pqzRaDQae7gUh27Ph2gIue13CdivxqTRaDSaY8KApf4LIYqBIw52RwElx3A6zvCUuXjKPMBz5uJsHqlSyuhjORkbg+Sz7SnzAM+Zi6fMA3r52R4wQXeGEGKjO+pwuANPmYunzAM8Zy6eMo+e4Clz9pR5gOfMxVPmAb2fiy6fq9FoNEMELegajUYzRPBUQX92oCfQDk+Zi6fMAzxnLp4yj57gKXP2lHmA58zFU+YBvZyLR/rQNRqNRtNzPNVC12g0Gk0P8ThBd0v/RvfM47AQYrsQYqsQ4pi2VhJCvCiEKBJCZLXbFiGE+FoIsc94DB/AudwnhDhqvDdbhRD92wdOXTNZCLFCCLFLCLFDCPE7Y/uAvC89xVM+18ZcjvvP9lD9XHuUoLtYe/1YcoqUctIAhDItBRZ12nYXsFxKOQJYbjwfqLkA/Mt4byYZiWf9TTNwm5RyDDATuMn4bAzU++IyHvi5Bv3ZtjcPGOSfa48SdFyrvT7kkVKuAso6bT4XeNn4/WXgvAGcyzFHSplv64IlpaxGlbJNZIDelx6iP9cGnvLZHqqfa08TdE+qqy6Br4QQm4yyvwNNrK3gmfEYM8Dz+Y0QYptx63pM3RxCiDTgBGAdnve+2MOTPtegP9vOGNSfa08TdJfqqh8j5kgpJ6Nuk28SQpw4QPPwRJ4ChgGTgHzg0WN1YSFEEPAecIuUsupYXbePeNLnGvRn2xGD/nPtaYLuMf0bpZR5xmMR8AHqtnkgKbS19TMeiwZqIlLKQilli5TSCjzHMXpvhBBm1If+dSnl+8Zmj3lfnOAxn2vQn21HDIXPtacJukf0bxRCBAohgm2/A6cBWc6P6nc+Bq4yfr8K+GigJiI69os9n2Pw3gghBPACsEtK+c92uzzmfXGCR3yuQX+2nTEkPtdSSo/6QdVV3wscAO4eoDlkAD8ZPzuO9TyAN1G3fE0o6+5aIBK12r3PeIwYwLm8CmwHthkfvPhjMI+5KDfFNmCr8XPmQL0vvZj/gH+ujXnoz7bjeQz6z7XOFNVoNJohgqe5XDQajUbTS7SgazQazRBBC7pGo9EMEbSgazQazRBBC7pGo9EMEbSgazQazRBBC7pGo9EMEbSgazQazRDh/wMGo90a7jTQBAAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "plot_acc_loss(\"FedAvg MNIST non-iid\", loss_hist_FA_niid, acc_hist_FA_niid)"
+    "###RUN FedAvg FOR MNIST NON-IID"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 16,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "### Federated training with FedProx"
+    "###PLOT THE RESULTS"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 16,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Clients' weights: [0.29, 0.2733333333333333, 0.43666666666666665]\n",
-      "====> i: 0 Loss: 2.306407473882039 Server Test Accuracy: 5.493723798307226\n",
-      "====> i: 1 Loss: 2.2260446576277415 Server Test Accuracy: 19.66966966966967\n",
-      "====> i: 2 Loss: 2.0079417979717253 Server Test Accuracy: 40.9804435277454\n",
-      "====> i: 3 Loss: 1.5390093358357746 Server Test Accuracy: 56.72841434796729\n",
-      "====> i: 4 Loss: 1.1283928259213765 Server Test Accuracy: 62.0299323934456\n",
-      "====> i: 5 Loss: 0.9241881344715754 Server Test Accuracy: 71.65633413951318\n",
-      "====> i: 6 Loss: 0.8157852756977081 Server Test Accuracy: 69.72263141443543\n",
-      "====> i: 7 Loss: 0.5624533195296924 Server Test Accuracy: 81.53064466588964\n",
-      "====> i: 8 Loss: 0.5735172559817632 Server Test Accuracy: 78.94570931283508\n",
-      "====> i: 9 Loss: 0.4567745459079743 Server Test Accuracy: 82.46855932473453\n",
-      "====> i: 10 Loss: 0.7236683595180511 Server Test Accuracy: 70.28451639718291\n",
-      "====> i: 11 Loss: 0.3859462860226631 Server Test Accuracy: 81.24697445243842\n",
-      "====> i: 12 Loss: 0.3846401866277058 Server Test Accuracy: 83.71827980611002\n",
-      "====> i: 13 Loss: 0.3171018890539805 Server Test Accuracy: 84.80821733903693\n",
-      "====> i: 14 Loss: 0.26964718714356417 Server Test Accuracy: 86.1797082700221\n",
-      "====> i: 15 Loss: 0.24281563197573025 Server Test Accuracy: 86.45824985066349\n",
-      "====> i: 16 Loss: 0.22772537445028623 Server Test Accuracy: 87.33918610414432\n",
-      "====> i: 17 Loss: 0.2068032720685005 Server Test Accuracy: 87.93555714215005\n",
-      "====> i: 18 Loss: 0.19739950825770694 Server Test Accuracy: 87.09692058280905\n",
-      "====> i: 19 Loss: 0.18340067078669864 Server Test Accuracy: 88.70164158287888\n",
-      "====> i: 20 Loss: 0.17671960825721422 Server Test Accuracy: 88.7253557463537\n"
-     ]
-    }
-   ],
    "source": [
-    "n_iter=20\n",
+    "Interpret the results.\n",
     "\n",
-    "model_f, loss_hist_FP_niid, acc_hist_FP_niid = FedProx( model_0, mnist_non_iid_train_dls, \n",
-    "    n_iter, mnist_non_iid_test_dls, epochs=2, lr=0.1, mu=.3)"
+    "Compare it with FedAvg for MNIST iid"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 17,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
    "source": [
-    "plot_acc_loss(\"FedProx mu=1 MNIST non-iid\", loss_hist_FP_niid, acc_hist_FP_niid)"
+    "### Federated training with FedProx\n",
+    "\n",
+    "\n",
+    "### EXERCISE\n",
+    "\n",
+    "Run FedProx for MNIST non-iid and conclude.\n",
+    "\n",
+    "Look at the impact of the learning rate and the number of epochs on the convergence speed and model performances."
    ]
   },
   {
@@ -1123,7 +1143,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,
diff --git a/federated_learning/federated_mcvae.ipynb b/federated_learning/federated_mcvae.ipynb
index 83fc044a09590d0a0ef2c94e48c5a621063edea6..ea39a21eee8dc2934f2b7156aa457cbe88dd429b 100644
--- a/federated_learning/federated_mcvae.ipynb
+++ b/federated_learning/federated_mcvae.ipynb
@@ -1,581 +1,480 @@
 {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "DaUlM5G0-3Z2"
+   },
+   "source": [
+    "# Federated Variational Autoencoders\n",
+    "We are going to study an example of federated latent variable modeling using federated learning and Variational autoencoders. In this example we will illustrate an iid scenario."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "id": "R4I97nmo-yaj"
+   },
+   "outputs": [],
+   "source": [
+    "import copy\n",
+    "from tqdm.auto import tqdm\n",
+    "\n",
+    "import torch\n",
+    "from torch.utils.data import Subset, DataLoader, random_split\n",
+    "from torchvision import datasets, transforms"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "id": "3TAtgoun-o-I"
+   },
+   "outputs": [],
+   "source": [
+    "N_CENTERS = 4\n",
+    "N_ROUNDS = 10   # Number of iterations between all the centers training and the aggregation process.\n",
+    "\n",
+    "N_EPOCHS = 15   # Number of epochs before aggregating\n",
+    "BATCH_SIZE = 48\n",
+    "LR = 1e-3       # Learning rate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Rwlv7bhp4Pu1"
+   },
+   "source": [
+    "We define a set of functions to distribute our dataset across multiple centers (`split_iid`) and for computing the federated averaging (`federated_averaging`)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "id": "0a2H2aMK_XEJ"
+   },
+   "outputs": [],
+   "source": [
+    "def split_iid(dataset, n_centers):\n",
+    "    \"\"\" Split PyTorch dataset randomly into n_centers \"\"\"\n",
+    "    n_obs_per_center = [len(dataset) // n_centers for _ in range(n_centers)]\n",
+    "    return random_split(dataset, n_obs_per_center)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "id": "BwVx6Cda4uyQ"
+   },
+   "outputs": [],
+   "source": [
+    "def federated_averaging(models, n_obs_per_client):\n",
+    "    assert len(models) > 0, 'An empty list of models was passed.'\n",
+    "    assert len(n_obs_per_client) == len(models), 'List with number of observations must have ' \\\n",
+    "                                                 'the same number of elements that list of models.'\n",
+    "\n",
+    "    # Compute proportions\n",
+    "    n_obs = sum(n_obs_per_client)\n",
+    "    proportions = [n_k / n_obs for n_k in n_obs_per_client]\n",
+    "\n",
+    "    # Empty model parameter dictionary\n",
+    "    avg_params = models[0].state_dict()\n",
+    "    for key, val in avg_params.items():\n",
+    "        avg_params[key] = torch.zeros_like(val)\n",
+    "\n",
+    "    # Compute average\n",
+    "    for model, proportion in zip(models, proportions):\n",
+    "        for key in avg_params.keys():\n",
+    "            avg_params[key] += proportion * model.state_dict()[key]\n",
+    "\n",
+    "    # Copy one of the models and load trained params\n",
+    "    avg_model = copy.deepcopy(models[0])\n",
+    "    avg_model.load_state_dict(avg_params)\n",
+    "\n",
+    "    return avg_model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "rtBeNOs_5TRV"
+   },
+   "source": [
+    "## Federating dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "id": "zQIM1eIs3c3k"
+   },
+   "outputs": [],
+   "source": [
+    "transform = transforms.Compose([transforms.ToTensor(),\n",
+    "                                 transforms.Normalize((0,), (1,))])\n",
+    "dataset = datasets.MNIST('~/data/', train=True, download=True, transform=transform)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "58MA82hi5Wqo"
+   },
+   "source": [
+    "Now, `federated_dataset` is a list of subsets of the main dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
     "colab": {
-      "name": "federated-mcvae.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
+     "base_uri": "https://localhost:8080/"
     },
-    "kernelspec": {
-      "name": "python3",
-      "display_name": "Python 3"
+    "id": "Hmqxw8OtAJpe",
+    "outputId": "fd4a61f6-7daa-4247-f3e4-04987e816213"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of centers: 4\n"
+     ]
     }
+   ],
+   "source": [
+    "federated_dataset = split_iid(dataset, n_centers=N_CENTERS)\n",
+    "print('Number of centers:', len(federated_dataset))"
+   ]
   },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "DaUlM5G0-3Z2"
-      },
-      "source": [
-        "# Federated Variational Autoencoders\n",
-        "We are going to study an example of federated latent variable modeling using federated learning and Variational autoencoders. In this example we will illustrate an iid scenario."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "R4I97nmo-yaj"
-      },
-      "source": [
-        "import copy\n",
-        "from tqdm.auto import tqdm\n",
-        "\n",
-        "import torch\n",
-        "from torch.utils.data import Subset, DataLoader, random_split\n",
-        "from torchvision import datasets, transforms"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "3TAtgoun-o-I"
-      },
-      "source": [
-        "N_CENTERS = 4\n",
-        "N_ROUNDS = 10   # Number of iterations between all the centers training and the aggregation process.\n",
-        "\n",
-        "N_EPOCHS = 15   # Number of epochs before aggregating\n",
-        "BATCH_SIZE = 48\n",
-        "LR = 1e-3       # Learning rate"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Rwlv7bhp4Pu1"
-      },
-      "source": [
-        "We define a set of functions to distribute our dataset across multiple centers (`split_iid`) and for computing the federated averaging (`federated_averaging`)."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "0a2H2aMK_XEJ"
-      },
-      "source": [
-        "def split_iid(dataset, n_centers):\n",
-        "    \"\"\" Split PyTorch dataset randomly into n_centers \"\"\"\n",
-        "    n_obs_per_center = [len(dataset) // n_centers for _ in range(n_centers)]\n",
-        "    return random_split(dataset, n_obs_per_center)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "BwVx6Cda4uyQ"
-      },
-      "source": [
-        "def federated_averaging(models, n_obs_per_client):\n",
-        "    assert len(models) > 0, 'An empty list of models was passed.'\n",
-        "    assert len(n_obs_per_client) == len(models), 'List with number of observations must have ' \\\n",
-        "                                                 'the same number of elements that list of models.'\n",
-        "\n",
-        "    # Compute proportions\n",
-        "    n_obs = sum(n_obs_per_client)\n",
-        "    proportions = [n_k / n_obs for n_k in n_obs_per_client]\n",
-        "\n",
-        "    # Empty model parameter dictionary\n",
-        "    avg_params = models[0].state_dict()\n",
-        "    for key, val in avg_params.items():\n",
-        "        avg_params[key] = torch.zeros_like(val)\n",
-        "\n",
-        "    # Compute average\n",
-        "    for model, proportion in zip(models, proportions):\n",
-        "        for key in avg_params.keys():\n",
-        "            avg_params[key] += proportion * model.state_dict()[key]\n",
-        "\n",
-        "    # Copy one of the models and load trained params\n",
-        "    avg_model = copy.deepcopy(models[0])\n",
-        "    avg_model.load_state_dict(avg_params)\n",
-        "\n",
-        "    return avg_model"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "rtBeNOs_5TRV"
-      },
-      "source": [
-        "## Federating dataset"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "zQIM1eIs3c3k"
-      },
-      "source": [
-        "transform = transforms.Compose([transforms.ToTensor(),\n",
-        "                                 transforms.Normalize((0,), (1,))])\n",
-        "dataset = datasets.MNIST('~/data/', train=True, download=True, transform=transform)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "58MA82hi5Wqo"
-      },
-      "source": [
-        "Now, `federated_dataset` is a list of subsets of the main dataset."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "Hmqxw8OtAJpe",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "fd4a61f6-7daa-4247-f3e4-04987e816213"
-      },
-      "source": [
-        "federated_dataset = split_iid(dataset, n_centers=N_CENTERS)\n",
-        "print('Number of centers:', len(federated_dataset))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "text": [
-            "Number of centers: 4\n"
-          ],
-          "name": "stdout"
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "if3uAKOQ8gDA"
-      },
-      "source": [
-        "## Defining and distributing a model: Variational Autoencoder\n",
-        "In this excercise we will use the Multi-channel Variational Autoencoder proposed by _Antelmi et al (ICML 2019)_."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "swxoLLB1HZjZ",
-        "outputId": "8dc3a46e-6d7b-486e-e96b-3d54d3ebcad8"
-      },
-      "source": [
-        "!pip install -q git+https://gitlab.inria.fr/epione_ML/mcvae.git"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "text": [
-            "  Building wheel for mcvae (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
-          ],
-          "name": "stdout"
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "fGYQqSqy8_Oe"
-      },
-      "source": [
-        "from mcvae.models import Mcvae, ThreeLayersVAE, VAE"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "e0DULErY8ly-"
-      },
-      "source": [
-        "First, it is necessary to define a model."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "ugDT7HADNHyx"
-      },
-      "source": [
-        "N_FEATURES = 784  # Number of pixels in MNIST"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "e28GtSTQ9r_t"
-      },
-      "source": [
-        "dummy_data = [torch.zeros(1, N_FEATURES)]  # Dummy data to initialize the input layer size\n",
-        "lat_dim = 3  # Size of the latent space for this autoencoder\n",
-        "vae_class = ThreeLayersVAE  # Architecture of the autoencoder (VAE: Single layer)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "9PTIpaglAnM_"
-      },
-      "source": [
-        "model = Mcvae(data=dummy_data, lat_dim=lat_dim, vaeclass=vae_class)\n",
-        "model.optimizer = torch.optim.Adam(params=model.parameters(), lr=1e-3)\n",
-        "model.init_loss()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "SY57ZUkx-YUc"
-      },
-      "source": [
-        "Now replicate a copy of the models across different centers."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "GiXQtB-eF3Mv"
-      },
-      "source": [
-        "models = [copy.deepcopy(model) for _ in range(N_CENTERS)]\n",
-        "n_obs_per_client = [len(client_data) for client_data in federated_dataset]"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "tah_VnaB-xdo"
-      },
-      "source": [
-        "Train in a federated fashion"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "ydgBCA49KQbO"
-      },
-      "source": [
-        "def get_data(subset, shuffle=True):\n",
-        "    \"\"\" Extracts data from a Subset torch dataset in the form of a tensor\"\"\"\n",
-        "    loader = DataLoader(subset, batch_size=len(subset), shuffle=shuffle)\n",
-        "    return iter(loader).next()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "uL2a10Rg-vE4",
-        "outputId": "62704cff-e036-43d5-eb0c-94c655c3ddd8"
-      },
-      "source": [
-        "init_params = model.state_dict()\n",
-        "for round_i in range(N_ROUNDS):\n",
-        "    for client_dataset, client_model in zip(federated_dataset, models):\n",
-        "        # Load client data in the form of a tensor\n",
-        "        X, y = get_data(client_dataset)\n",
-        "        client_model.data = [X.view(-1, N_FEATURES)]  # Set data attribute in client's model (list wraps the number of channels)\n",
-        "\n",
-        "        # Load client's model parameters and train\n",
-        "        client_model.load_state_dict(init_params)\n",
-        "        client_model.optimize(epochs=N_EPOCHS, data=client_model.data)\n",
-        "        \n",
-        "    # Aggregate models using federated averaging\n",
-        "    trained_model = federated_averaging(models, n_obs_per_client)\n",
-        "    init_params = trained_model.state_dict()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "text": [
-            "====> Epoch:    0/15 (0%)\tLoss: 528.5617\tLL: -528.5566\tKL: 0.0050\tLL/KL: -104751.2169\n",
-            "====> Epoch:   10/15 (67%)\tLoss: 77.4644\tLL: -74.0843\tKL: 3.3801\tLL/KL: -21.9175\n",
-            "====> Epoch:    0/15 (0%)\tLoss: 527.9626\tLL: -527.9576\tKL: 0.0051\tLL/KL: -104216.8695\n",
-            "====> Epoch:   10/15 (67%)\tLoss: 77.4401\tLL: -73.8392\tKL: 3.6009\tLL/KL: -20.5055\n",
-            "====> Epoch:    0/15 (0%)\tLoss: 525.0997\tLL: -525.0947\tKL: 0.0051\tLL/KL: -103884.9293\n",
-            "====> Epoch:   10/15 (67%)\tLoss: 76.7743\tLL: -73.2086\tKL: 3.5656\tLL/KL: -20.5319\n",
-            "====> Epoch:    0/15 (0%)\tLoss: 528.4604\tLL: -528.4553\tKL: 0.0051\tLL/KL: -104527.3463\n",
-            "====> Epoch:   10/15 (67%)\tLoss: 77.8238\tLL: -74.3751\tKL: 3.4487\tLL/KL: -21.5661\n",
-            "====> Epoch:   20/30 (67%)\tLoss: 49.0290\tLL: -37.6401\tKL: 11.3889\tLL/KL: -3.3050\n",
-            "====> Epoch:   20/30 (67%)\tLoss: 48.4610\tLL: -37.1718\tKL: 11.2892\tLL/KL: -3.2927\n",
-            "====> Epoch:   20/30 (67%)\tLoss: 48.2056\tLL: -36.9949\tKL: 11.2106\tLL/KL: -3.3000\n",
-            "====> Epoch:   20/30 (67%)\tLoss: 49.2486\tLL: -37.8945\tKL: 11.3541\tLL/KL: -3.3375\n",
-            "====> Epoch:   30/45 (67%)\tLoss: 15.8485\tLL: -9.6083\tKL: 6.2402\tLL/KL: -1.5397\n",
-            "====> Epoch:   40/45 (89%)\tLoss: -12.3623\tLL: 18.9352\tKL: 6.5729\tLL/KL: 2.8808\n",
-            "====> Epoch:   30/45 (67%)\tLoss: 15.8072\tLL: -9.5787\tKL: 6.2285\tLL/KL: -1.5379\n",
-            "====> Epoch:   40/45 (89%)\tLoss: -12.5916\tLL: 19.1550\tKL: 6.5635\tLL/KL: 2.9184\n",
-            "====> Epoch:   30/45 (67%)\tLoss: 16.1558\tLL: -9.9610\tKL: 6.1948\tLL/KL: -1.6080\n",
-            "====> Epoch:   40/45 (89%)\tLoss: -11.9684\tLL: 18.5574\tKL: 6.5890\tLL/KL: 2.8164\n",
-            "====> Epoch:   30/45 (67%)\tLoss: 16.5887\tLL: -10.3528\tKL: 6.2359\tLL/KL: -1.6602\n",
-            "====> Epoch:   40/45 (89%)\tLoss: -11.1709\tLL: 17.6888\tKL: 6.5179\tLL/KL: 2.7139\n",
-            "====> Epoch:   50/60 (83%)\tLoss: -43.2949\tLL: 51.9390\tKL: 8.6441\tLL/KL: 6.0086\n",
-            "====> Epoch:   50/60 (83%)\tLoss: -43.9839\tLL: 52.5778\tKL: 8.5938\tLL/KL: 6.1181\n",
-            "====> Epoch:   50/60 (83%)\tLoss: -43.4652\tLL: 51.9832\tKL: 8.5180\tLL/KL: 6.1028\n",
-            "====> Epoch:   50/60 (83%)\tLoss: -42.8195\tLL: 51.4198\tKL: 8.6003\tLL/KL: 5.9789\n",
-            "====> Epoch:   60/75 (80%)\tLoss: -63.5757\tLL: 71.6305\tKL: 8.0549\tLL/KL: 8.8928\n",
-            "====> Epoch:   70/75 (93%)\tLoss: -77.9186\tLL: 86.5862\tKL: 8.6676\tLL/KL: 9.9896\n",
-            "====> Epoch:   60/75 (80%)\tLoss: -64.2308\tLL: 72.2830\tKL: 8.0523\tLL/KL: 8.9767\n",
-            "====> Epoch:   70/75 (93%)\tLoss: -79.0930\tLL: 87.7227\tKL: 8.6297\tLL/KL: 10.1652\n",
-            "====> Epoch:   60/75 (80%)\tLoss: -63.4257\tLL: 71.4438\tKL: 8.0180\tLL/KL: 8.9104\n",
-            "====> Epoch:   70/75 (93%)\tLoss: -78.2753\tLL: 87.0201\tKL: 8.7449\tLL/KL: 9.9510\n",
-            "====> Epoch:   60/75 (80%)\tLoss: -63.2790\tLL: 71.3351\tKL: 8.0560\tLL/KL: 8.8549\n",
-            "====> Epoch:   70/75 (93%)\tLoss: -77.4719\tLL: 86.1749\tKL: 8.7030\tLL/KL: 9.9018\n",
-            "====> Epoch:   80/90 (89%)\tLoss: -92.5114\tLL: 100.9692\tKL: 8.4578\tLL/KL: 11.9380\n",
-            "====> Epoch:   80/90 (89%)\tLoss: -92.9820\tLL: 101.3774\tKL: 8.3955\tLL/KL: 12.0753\n",
-            "====> Epoch:   80/90 (89%)\tLoss: -92.5196\tLL: 100.8786\tKL: 8.3591\tLL/KL: 12.0682\n",
-            "====> Epoch:   80/90 (89%)\tLoss: -92.8745\tLL: 101.2884\tKL: 8.4139\tLL/KL: 12.0382\n",
-            "====> Epoch:   90/105 (86%)\tLoss: -106.0539\tLL: 114.7090\tKL: 8.6551\tLL/KL: 13.2534\n",
-            "====> Epoch:  100/105 (95%)\tLoss: -117.9297\tLL: 126.6995\tKL: 8.7698\tLL/KL: 14.4472\n",
-            "====> Epoch:   90/105 (86%)\tLoss: -106.8086\tLL: 115.4679\tKL: 8.6593\tLL/KL: 13.3345\n",
-            "====> Epoch:  100/105 (95%)\tLoss: -118.4944\tLL: 127.2676\tKL: 8.7733\tLL/KL: 14.5063\n",
-            "====> Epoch:   90/105 (86%)\tLoss: -106.5121\tLL: 115.1398\tKL: 8.6277\tLL/KL: 13.3453\n",
-            "====> Epoch:  100/105 (95%)\tLoss: -118.4516\tLL: 127.2390\tKL: 8.7874\tLL/KL: 14.4797\n",
-            "====> Epoch:   90/105 (86%)\tLoss: -106.7659\tLL: 115.4336\tKL: 8.6677\tLL/KL: 13.3177\n",
-            "====> Epoch:  100/105 (95%)\tLoss: -118.5240\tLL: 127.3401\tKL: 8.8160\tLL/KL: 14.4442\n",
-            "====> Epoch:  110/120 (92%)\tLoss: -126.0735\tLL: 134.7997\tKL: 8.7261\tLL/KL: 15.4478\n",
-            "====> Epoch:  110/120 (92%)\tLoss: -128.5597\tLL: 137.4358\tKL: 8.8761\tLL/KL: 15.4838\n",
-            "====> Epoch:  110/120 (92%)\tLoss: -128.5418\tLL: 137.4097\tKL: 8.8679\tLL/KL: 15.4952\n",
-            "====> Epoch:  110/120 (92%)\tLoss: -128.5736\tLL: 137.4403\tKL: 8.8667\tLL/KL: 15.5007\n",
-            "====> Epoch:  120/135 (89%)\tLoss: -136.8414\tLL: 145.7950\tKL: 8.9536\tLL/KL: 16.2834\n",
-            "====> Epoch:  130/135 (96%)\tLoss: -145.7557\tLL: 154.8592\tKL: 9.1035\tLL/KL: 17.0110\n",
-            "====> Epoch:  120/135 (89%)\tLoss: -137.7465\tLL: 146.7102\tKL: 8.9637\tLL/KL: 16.3671\n",
-            "====> Epoch:  130/135 (96%)\tLoss: -147.1581\tLL: 156.2683\tKL: 9.1102\tLL/KL: 17.1531\n",
-            "====> Epoch:  120/135 (89%)\tLoss: -137.8340\tLL: 146.7747\tKL: 8.9407\tLL/KL: 16.4166\n",
-            "====> Epoch:  130/135 (96%)\tLoss: -146.9022\tLL: 155.9727\tKL: 9.0705\tLL/KL: 17.1955\n",
-            "====> Epoch:  120/135 (89%)\tLoss: -137.7606\tLL: 146.7392\tKL: 8.9785\tLL/KL: 16.3433\n",
-            "====> Epoch:  130/135 (96%)\tLoss: -146.8978\tLL: 155.9755\tKL: 9.0777\tLL/KL: 17.1823\n",
-            "====> Epoch:  140/150 (93%)\tLoss: -153.9218\tLL: 163.0297\tKL: 9.1080\tLL/KL: 17.8997\n",
-            "====> Epoch:  140/150 (93%)\tLoss: -154.8601\tLL: 164.0375\tKL: 9.1775\tLL/KL: 17.8740\n",
-            "====> Epoch:  140/150 (93%)\tLoss: -155.0774\tLL: 164.2348\tKL: 9.1574\tLL/KL: 17.9346\n",
-            "====> Epoch:  140/150 (93%)\tLoss: -154.5916\tLL: 163.7941\tKL: 9.2025\tLL/KL: 17.7989\n"
-          ],
-          "name": "stdout"
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "0gz_IRXHOL_L"
-      },
-      "source": [
-        "## Results visualization\n",
-        "Using the final parameters we can evaluate the performance of the model by visualizing the testing set onto the latent space."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "-yNMU8hoPGjV"
-      },
-      "source": [
-        "import numpy as np\n",
-        "import pandas as pd\n",
-        "\n",
-        "import seaborn as sns\n",
-        "import matplotlib.pyplot as plt\n",
-        "\n",
-        "sns.set()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "5CABgW5RFY7c"
-      },
-      "source": [
-        "dataset_test = datasets.MNIST('~/data/', train=False, download=True)\n",
-        "X_test, y_test = [dataset_test.data.view(-1, N_FEATURES).float()], dataset_test.targets"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "7zLZGrUkO50c"
-      },
-      "source": [
-        "Z_test = np.hstack([z.loc.detach().numpy() for z in trained_model.encode(X_test)])"
-      ],
-      "execution_count": null,
-      "outputs": []
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "if3uAKOQ8gDA"
+   },
+   "source": [
+    "## Defining and distributing a model: Variational Autoencoder\n",
+    "In this excercise we will use the Multi-channel Variational Autoencoder proposed by _Antelmi et al (ICML 2019)_."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "ktFhxqWEPEfs",
-        "outputId": "ccc287be-e995-431c-8bb3-f36eed2ba549"
-      },
-      "source": [
-        "col_names = [f'$Z_{i}$' for i in range(Z_test.shape[1])]\n",
-        "latent_df = pd.DataFrame(Z_test, columns=col_names)\n",
-        "latent_df['label'] = y_test\n",
-        "latent_df['label'] = latent_df['label'].astype('category')\n",
-        "latent_df.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>$Z_0$</th>\n",
-              "      <th>$Z_1$</th>\n",
-              "      <th>$Z_2$</th>\n",
-              "      <th>label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>794.841309</td>\n",
-              "      <td>-325.295868</td>\n",
-              "      <td>174.970810</td>\n",
-              "      <td>7</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>-357.250793</td>\n",
-              "      <td>576.667358</td>\n",
-              "      <td>-40.315079</td>\n",
-              "      <td>2</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>-131.488586</td>\n",
-              "      <td>354.551086</td>\n",
-              "      <td>350.653107</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>-160.370346</td>\n",
-              "      <td>-291.653625</td>\n",
-              "      <td>-659.524414</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>160.157776</td>\n",
-              "      <td>-210.283234</td>\n",
-              "      <td>-121.650696</td>\n",
-              "      <td>4</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "        $Z_0$       $Z_1$       $Z_2$ label\n",
-              "0  794.841309 -325.295868  174.970810     7\n",
-              "1 -357.250793  576.667358  -40.315079     2\n",
-              "2 -131.488586  354.551086  350.653107     1\n",
-              "3 -160.370346 -291.653625 -659.524414     0\n",
-              "4  160.157776 -210.283234 -121.650696     4"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          },
-          "execution_count": 107
-        }
-      ]
+    "id": "swxoLLB1HZjZ",
+    "outputId": "8dc3a46e-6d7b-486e-e96b-3d54d3ebcad8"
+   },
+   "outputs": [],
+   "source": [
+    "!pip install -q git+https://gitlab.inria.fr/epione_ML/mcvae.git"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "id": "fGYQqSqy8_Oe"
+   },
+   "outputs": [],
+   "source": [
+    "from mcvae.models import Mcvae, ThreeLayersVAE, VAE"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "e0DULErY8ly-"
+   },
+   "source": [
+    "First, it is necessary to define a model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "id": "ugDT7HADNHyx"
+   },
+   "outputs": [],
+   "source": [
+    "N_FEATURES = 784  # Number of pixels in MNIST"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "id": "e28GtSTQ9r_t"
+   },
+   "outputs": [],
+   "source": [
+    "dummy_data = [torch.zeros(1, N_FEATURES)]  # Dummy data to initialize the input layer size\n",
+    "lat_dim = 3  # Size of the latent space for this autoencoder\n",
+    "vae_class = ThreeLayersVAE  # Architecture of the autoencoder (VAE: Single layer)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "id": "9PTIpaglAnM_"
+   },
+   "outputs": [],
+   "source": [
+    "model = Mcvae(data=dummy_data, lat_dim=lat_dim, vaeclass=vae_class)\n",
+    "model.optimizer = torch.optim.Adam(params=model.parameters(), lr=1e-3)\n",
+    "model.init_loss()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "SY57ZUkx-YUc"
+   },
+   "source": [
+    "Now replicate a copy of the models across different centers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "id": "GiXQtB-eF3Mv"
+   },
+   "outputs": [],
+   "source": [
+    "models = [copy.deepcopy(model) for _ in range(N_CENTERS)]\n",
+    "n_obs_per_client = [len(client_data) for client_data in federated_dataset]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tah_VnaB-xdo"
+   },
+   "source": [
+    "Train in a federated fashion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "id": "ydgBCA49KQbO"
+   },
+   "outputs": [],
+   "source": [
+    "def get_data(subset, shuffle=True):\n",
+    "    \"\"\" Extracts data from a Subset torch dataset in the form of a tensor\"\"\"\n",
+    "    loader = DataLoader(subset, batch_size=len(subset), shuffle=shuffle)\n",
+    "    return iter(loader).next()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "uL2a10Rg-vE4",
+    "outputId": "62704cff-e036-43d5-eb0c-94c655c3ddd8"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "sTzkoPh5Pm4F",
-        "outputId": "b1c70915-2955-455e-d30c-04c75df65ef1"
-      },
-      "source": [
-        "sns.pairplot(latent_df, hue='label', corner=True)\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 586.6x540 with 9 Axes>"
-            ]
-          },
-          "metadata": {
-            "tags": []
-          }
-        }
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "====> Epoch:    0/15 (0%)\tLoss: 549.0060\tLL: -549.0015\tKL: 0.0044\tLL/KL: -123752.7716\n",
+      "====> Epoch:   10/15 (67%)\tLoss: 82.7334\tLL: -78.5644\tKL: 4.1690\tLL/KL: -18.8448\n",
+      "====> Epoch:    0/15 (0%)\tLoss: 551.0641\tLL: -551.0596\tKL: 0.0045\tLL/KL: -123185.0004\n",
+      "====> Epoch:   10/15 (67%)\tLoss: 83.1423\tLL: -78.9854\tKL: 4.1570\tLL/KL: -19.0006\n",
+      "====> Epoch:    0/15 (0%)\tLoss: 553.0543\tLL: -553.0498\tKL: 0.0045\tLL/KL: -123165.6171\n",
+      "====> Epoch:   10/15 (67%)\tLoss: 83.6635\tLL: -79.2979\tKL: 4.3656\tLL/KL: -18.1644\n",
+      "====> Epoch:    0/15 (0%)\tLoss: 551.7684\tLL: -551.7640\tKL: 0.0045\tLL/KL: -123816.6904\n",
+      "====> Epoch:   10/15 (67%)\tLoss: 82.1891\tLL: -77.8627\tKL: 4.3264\tLL/KL: -17.9972\n",
+      "====> Epoch:   20/30 (67%)\tLoss: 52.9532\tLL: -41.7303\tKL: 11.2229\tLL/KL: -3.7183\n",
+      "====> Epoch:   20/30 (67%)\tLoss: 53.4088\tLL: -42.1911\tKL: 11.2177\tLL/KL: -3.7611\n",
+      "====> Epoch:   20/30 (67%)\tLoss: 54.1244\tLL: -43.0145\tKL: 11.1099\tLL/KL: -3.8717\n",
+      "====> Epoch:   20/30 (67%)\tLoss: 52.5903\tLL: -41.4866\tKL: 11.1037\tLL/KL: -3.7363\n",
+      "====> Epoch:   30/45 (67%)\tLoss: 33.8065\tLL: -28.3495\tKL: 5.4571\tLL/KL: -5.1950\n",
+      "====> Epoch:   40/45 (89%)\tLoss: 18.1020\tLL: -13.2426\tKL: 4.8594\tLL/KL: -2.7252\n",
+      "====> Epoch:   30/45 (67%)\tLoss: 34.1739\tLL: -28.6980\tKL: 5.4759\tLL/KL: -5.2408\n",
+      "====> Epoch:   40/45 (89%)\tLoss: 18.5314\tLL: -13.6631\tKL: 4.8683\tLL/KL: -2.8066\n",
+      "====> Epoch:   30/45 (67%)\tLoss: 34.6137\tLL: -29.1391\tKL: 5.4745\tLL/KL: -5.3227\n",
+      "====> Epoch:   40/45 (89%)\tLoss: 19.2687\tLL: -14.3770\tKL: 4.8917\tLL/KL: -2.9391\n",
+      "====> Epoch:   30/45 (67%)\tLoss: 33.2370\tLL: -27.7640\tKL: 5.4730\tLL/KL: -5.0729\n",
+      "====> Epoch:   40/45 (89%)\tLoss: 17.4709\tLL: -12.5999\tKL: 4.8710\tLL/KL: -2.5867\n",
+      "====> Epoch:   50/60 (83%)\tLoss: -5.0630\tLL: 11.4165\tKL: 6.3535\tLL/KL: 1.7969\n",
+      "====> Epoch:   50/60 (83%)\tLoss: -4.9994\tLL: 11.3325\tKL: 6.3331\tLL/KL: 1.7894\n",
+      "====> Epoch:   50/60 (83%)\tLoss: -4.3881\tLL: 10.7360\tKL: 6.3479\tLL/KL: 1.6913\n",
+      "====> Epoch:   50/60 (83%)\tLoss: -6.0503\tLL: 12.3884\tKL: 6.3382\tLL/KL: 1.9546\n",
+      "====> Epoch:   60/75 (80%)\tLoss: -29.5380\tLL: 36.7966\tKL: 7.2586\tLL/KL: 5.0694\n",
+      "====> Epoch:   70/75 (93%)\tLoss: -55.2589\tLL: 63.4622\tKL: 8.2032\tLL/KL: 7.7362\n",
+      "====> Epoch:   60/75 (80%)\tLoss: -29.4960\tLL: 36.7787\tKL: 7.2827\tLL/KL: 5.0501\n",
+      "====> Epoch:   70/75 (93%)\tLoss: -55.1117\tLL: 63.3170\tKL: 8.2053\tLL/KL: 7.7166\n",
+      "====> Epoch:   60/75 (80%)\tLoss: -28.9316\tLL: 36.2149\tKL: 7.2833\tLL/KL: 4.9723\n",
+      "====> Epoch:   70/75 (93%)\tLoss: -54.1728\tLL: 62.3446\tKL: 8.1718\tLL/KL: 7.6292\n",
+      "====> Epoch:   60/75 (80%)\tLoss: -30.7607\tLL: 38.0435\tKL: 7.2829\tLL/KL: 5.2237\n",
+      "====> Epoch:   70/75 (93%)\tLoss: -56.6350\tLL: 64.8457\tKL: 8.2107\tLL/KL: 7.8977\n",
+      "====> Epoch:   80/90 (89%)\tLoss: -72.8661\tLL: 81.1838\tKL: 8.3177\tLL/KL: 9.7603\n",
+      "====> Epoch:   80/90 (89%)\tLoss: -73.5662\tLL: 81.9328\tKL: 8.3665\tLL/KL: 9.7929\n",
+      "====> Epoch:   80/90 (89%)\tLoss: -72.2818\tLL: 80.6926\tKL: 8.4108\tLL/KL: 9.5939\n",
+      "====> Epoch:   80/90 (89%)\tLoss: -74.6665\tLL: 83.0156\tKL: 8.3490\tLL/KL: 9.9431\n",
+      "====> Epoch:   90/105 (86%)\tLoss: -85.3397\tLL: 94.0086\tKL: 8.6689\tLL/KL: 10.8444\n",
+      "====> Epoch:  100/105 (95%)\tLoss: -98.8286\tLL: 107.4869\tKL: 8.6583\tLL/KL: 12.4143\n",
+      "====> Epoch:   90/105 (86%)\tLoss: -85.8566\tLL: 94.5646\tKL: 8.7080\tLL/KL: 10.8595\n",
+      "====> Epoch:  100/105 (95%)\tLoss: -98.9881\tLL: 107.6321\tKL: 8.6441\tLL/KL: 12.4516\n",
+      "====> Epoch:   90/105 (86%)\tLoss: -84.7209\tLL: 93.4080\tKL: 8.6871\tLL/KL: 10.7525\n",
+      "====> Epoch:  100/105 (95%)\tLoss: -97.8231\tLL: 106.4837\tKL: 8.6606\tLL/KL: 12.2952\n",
+      "====> Epoch:   90/105 (86%)\tLoss: -86.8344\tLL: 95.5405\tKL: 8.7061\tLL/KL: 10.9740\n",
+      "====> Epoch:  100/105 (95%)\tLoss: -100.0892\tLL: 108.7154\tKL: 8.6262\tLL/KL: 12.6030\n",
+      "====> Epoch:  110/120 (92%)\tLoss: -112.8582\tLL: 121.6993\tKL: 8.8411\tLL/KL: 13.7653\n",
+      "====> Epoch:  110/120 (92%)\tLoss: -112.9543\tLL: 121.8334\tKL: 8.8791\tLL/KL: 13.7214\n",
+      "====> Epoch:  110/120 (92%)\tLoss: -112.0804\tLL: 120.9473\tKL: 8.8668\tLL/KL: 13.6404\n",
+      "====> Epoch:  110/120 (92%)\tLoss: -114.0907\tLL: 122.8925\tKL: 8.8018\tLL/KL: 13.9622\n",
+      "====> Epoch:  120/135 (89%)\tLoss: -126.3037\tLL: 135.2220\tKL: 8.9182\tLL/KL: 15.1624\n",
+      "====> Epoch:  130/135 (96%)\tLoss: -138.9217\tLL: 147.9530\tKL: 9.0313\tLL/KL: 16.3823\n",
+      "====> Epoch:  120/135 (89%)\tLoss: -126.2420\tLL: 135.1894\tKL: 8.9473\tLL/KL: 15.1095\n",
+      "====> Epoch:  130/135 (96%)\tLoss: -138.2348\tLL: 147.2517\tKL: 9.0168\tLL/KL: 16.3308\n",
+      "====> Epoch:  120/135 (89%)\tLoss: -125.5312\tLL: 134.4658\tKL: 8.9346\tLL/KL: 15.0500\n",
+      "====> Epoch:  130/135 (96%)\tLoss: -137.8430\tLL: 146.8761\tKL: 9.0331\tLL/KL: 16.2597\n",
+      "====> Epoch:  120/135 (89%)\tLoss: -127.3756\tLL: 136.3297\tKL: 8.9540\tLL/KL: 15.2255\n",
+      "====> Epoch:  130/135 (96%)\tLoss: -139.6181\tLL: 148.6477\tKL: 9.0296\tLL/KL: 16.4622\n",
+      "====> Epoch:  140/150 (93%)\tLoss: -149.4960\tLL: 158.6330\tKL: 9.1369\tLL/KL: 17.3618\n",
+      "====> Epoch:  140/150 (93%)\tLoss: -149.3842\tLL: 158.5509\tKL: 9.1666\tLL/KL: 17.2966\n",
+      "====> Epoch:  140/150 (93%)\tLoss: -148.9252\tLL: 158.0730\tKL: 9.1477\tLL/KL: 17.2801\n",
+      "====> Epoch:  140/150 (93%)\tLoss: -150.6223\tLL: 159.7808\tKL: 9.1586\tLL/KL: 17.4460\n"
+     ]
     }
-  ]
+   ],
+   "source": [
+    "init_params = model.state_dict()\n",
+    "for round_i in range(N_ROUNDS):\n",
+    "    for client_dataset, client_model in zip(federated_dataset, models):\n",
+    "        # Load client data in the form of a tensor\n",
+    "        X, y = get_data(client_dataset)\n",
+    "        client_model.data = [X.view(-1, N_FEATURES)]  # Set data attribute in client's model (list wraps the number of channels)\n",
+    "\n",
+    "        # Load client's model parameters and train\n",
+    "        client_model.load_state_dict(init_params)\n",
+    "        client_model.optimize(epochs=N_EPOCHS, data=client_model.data)\n",
+    "        \n",
+    "    # Aggregate models using federated averaging\n",
+    "    trained_model = federated_averaging(models, n_obs_per_client)\n",
+    "    init_params = trained_model.state_dict()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "0gz_IRXHOL_L"
+   },
+   "source": [
+    "## Results visualization\n",
+    "Using the final parameters we can evaluate the performance of the model by visualizing the testing set onto the latent space."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "id": "-yNMU8hoPGjV"
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "sns.set()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "id": "5CABgW5RFY7c"
+   },
+   "outputs": [],
+   "source": [
+    "dataset_test = datasets.MNIST('~/data/', train=False, download=True)\n",
+    "X_test, y_test = [dataset_test.data.view(-1, N_FEATURES).float()], dataset_test.targets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "id": "7zLZGrUkO50c"
+   },
+   "outputs": [],
+   "source": [
+    "Z_test = np.hstack([z.loc.detach().numpy() for z in trained_model.encode(X_test)])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### EXERCISE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### CREATE A PANDA DATAFRAME WITH FEATURES: LATENT COORDINATES + LABEL"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "###PLOT THE LATENT SPACE WITH A PAIRPLOT USING THE CREATED DATAFRAME"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "federated-mcvae.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
 }