--- a
+++ b/Code/All Qiskit, PennyLane QML Nov 23/11a QCNN 2xIter 100% 100% kkawchak.ipynb
@@ -0,0 +1,842 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "58d4191c-2fbe-4ca8-98af-84bfc72bccc7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Time in seconds since beginning of run: 1700673671.093184\n",
+      "Wed Nov 22 17:21:11 2023\n"
+     ]
+    }
+   ],
+   "source": [
+    "import time\n",
+    "seconds = time.time()\n",
+    "print(\"Time in seconds since beginning of run:\", seconds)\n",
+    "local_time = time.ctime(seconds)\n",
+    "print(local_time)\n",
+    "# Qiskit The Quantum Convolution Neural Network\n",
+    "# https://qiskit.org/documentation/machine-learning/tutorials/11_quantum_convolutional_neural_networks.html\n",
+    "# Downloaded 11_qcnn_initial_point.json from https://github.com/Qiskit/qiskit-machine-learning/blob/stable/0.5/docs/tutorials/11_qcnn_initial_point.json\n",
+    "# Right click \"Raw\", \"Save link as\". Inserted .json file into same folder as this .ipynb. Best regards."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "0a99fbd2-2c6e-4c7d-a9d5-ad7383bddce0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from IPython.display import clear_output\n",
+    "from qiskit import QuantumCircuit\n",
+    "from qiskit.algorithms.optimizers import COBYLA\n",
+    "from qiskit.circuit import ParameterVector\n",
+    "from qiskit.circuit.library import ZFeatureMap\n",
+    "from qiskit.quantum_info import SparsePauliOp\n",
+    "from qiskit.utils import algorithm_globals\n",
+    "from qiskit_machine_learning.algorithms.classifiers import NeuralNetworkClassifier\n",
+    "from qiskit_machine_learning.neural_networks import EstimatorQNN\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "algorithm_globals.random_seed = 12345"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "2981b52b-7cd3-48b7-b7ed-d00bee65db30",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1374.24x200.667 with 1 Axes>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# We now define a two qubit unitary as defined in [3]\n",
+    "def conv_circuit(params):\n",
+    "    target = QuantumCircuit(2)\n",
+    "    target.rz(-np.pi / 2, 1)\n",
+    "    target.cx(1, 0)\n",
+    "    target.rz(params[0], 0)\n",
+    "    target.ry(params[1], 1)\n",
+    "    target.cx(0, 1)\n",
+    "    target.ry(params[2], 1)\n",
+    "    target.cx(1, 0)\n",
+    "    target.rz(np.pi / 2, 0) # 2x\n",
+    "    target.barrier(0, 1)\n",
+    "    target.rz(-np.pi / 2, 1)\n",
+    "    target.cx(1, 0)\n",
+    "    target.rz(params[0], 0)\n",
+    "    target.ry(params[1], 1)\n",
+    "    target.cx(0, 1)\n",
+    "    target.ry(params[2], 1)\n",
+    "    target.cx(1, 0)\n",
+    "    target.rz(np.pi / 2, 0)\n",
+    "    return target\n",
+    "\n",
+    "\n",
+    "# Let's draw this circuit and see what it looks like\n",
+    "params = ParameterVector(\"θ\", length=3)\n",
+    "circuit = conv_circuit(params)\n",
+    "circuit.draw(\"mpl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "cc82adbd-cd38-4873-96a9-627c63737559",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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kfevqj8nnq9d7sxwwT9s38oql5duM97D2uH9WapI0KlM6u4fUKsaq6BCqZduC/0LTHD6/sW7fteeYd87moB8AbeA7R45Kq3KNtRWOn+q0vFpatE4a0VtKbmNZeBETSBv4zd8ny+f36cGb/tnw3JGqYt3yRLamTnhCF591gxWhB2RboXHByUwfb5HO7yN5bTCqy+nvfzD8fmMNt+XbjPVbvr2wXV4tPfOhNLKPNDDdPqP1gECRC3ynovqbXCBXKqn87vnyauOm1pGZUkpb6+KLFKd/Fuw6JO05bO45l22VLupnn1FdTm8DgfL7pdwD0vLt0oZ9393sUl4jzX7fyAUGd7XP+woAjXF0oauoqEgTJ05UYWGh7rnnHj300ENq29bI3mbNmqX7779f0dHR8ng8GjRokMXRBm5Vrvl3YPr8xnnHDjT3vKFIS8nUWX3GSJKGZY3TgB6jdNezo/SH+T/Vr278hyRpYM/z9NZvKk7Yr6hsv+6YfbYuG2GfkX2ns3iTtHBt468VlEqvr5Y+3irdOlrq4MCLnE51rE76fKf55/1ylzTxTKl1rPnnDhb9AGgDhh0HpTkfS0ePnfyaX8ZozY+3SD8aJQ1INz28iAqkDfzsymc19f8GavHa13TRmddJkp564w5l9xjV4i9qLN9m/jlLKqXN+6VsG7QVp7//gar3Sf/4TFrdRN6w/YDx6NtF+vH5Uhw3P8FByAUMe4qkPy5tfEYYv4zp0JdtlW4cIeV0Nzu6yHL6Z8GK7eafs7zaWA/srAzzzx0Kp7eBQPh80vwvmm4vOw8Zj5WdpJvPl1q3Mjc+AAgXR9+3N336dOXl5WnatGl64oknGopckjRjxgwNHjxYdXV1ysjIULt27SyMNDhWXOCWpM93WHPe5srOGKExZ92kpevnauPulY1uc6yuRr/+65UakDFK11/8S5MjjIyPtzRd5DrewSPSsx9J5UdPvy1ahg37Gr9oHWnH6qX1e80/bzi4tR9oTEJCgkaOHKmEhASrQzGVG9vAvsPS84tP31/U1ksvfWKMEHKyxtpAu9bJuufqP+npN6epqGy/Pvlqnr7asVT/feXzFkd7ahXVxsgcK3xmUR7aXE56/wP17ZRWTRW5jre1UPrTx1KdMwav4DTIBdyTCxSUSs8tPv2yB3U+6S/LpY15poRlGSd9FlTXSuss+m5m11xAclYbCITff+oi1/F2HJReXGrcWAvnc2suAGdzbKFr8+bNmjt3rlJSUvTYY481us2QIUMkSYMHD254bt68efrBD36g7t27q3Xr1srKytKvfvUrVVRUNHoMs5UflYorT79dJBRX2rcYcsOYB+X1Rukv7/1Po6//Yf5Pday2Wvdd+7K5gUVIaZUxBUWgDldIb6+PXDwIr90mT09xvD1F1p27udzWDzQlIyNDc+bMUUZGhtWhmM5NbcDvN0Zx1AZ40frbBcbNnBLVCo21gaFZY3XBoGs087Ub9dSC23X31XPULqGDhVGe3t7D1q2r4rTPATu+/4HavF9avSvw7bcfMGZwgPORC7gjF5Ck1z83CiKB8MtY+9HpBW+nfBbkF1uXt1mZh4SDU9pAIHYeDG7k3+4iY4QnnM/NuQCcy7GFrtdee00+n0833HCD2rRpfE62+HhjwanjC11PPPGEoqKi9Oijj+qdd97Rbbfdpueee05jx46VrwWs0riv2N3nD1VaSm+NHjxZa3M/0oady0547Y3ls/XZ5kX69ZQ3FRcbwoqsLVAo01t+uVuqOs2dfmgZ8iwsdNm1D5Dc1w80pb6+XhUVFaqvd/hVjEa4qQ3sOSzllwS3T2mVcWHcyZpqA1MnPqH8w7kamjVO5/Qbb2GEgcmzsC8uO2qs+2ZHTnn/AxXKlFYrttv74iUCQy7gjlxgf4kxHVkwKmrsO4NDoJzyWWDl97Kjx4ybZe3KKW0gEMtDyAVWWrBcCszn5lwAzuXYQtfixYslSaNHj25ym7w8Y1z+8YWut956S//85z91ww036IILLtCdd96pp59+WitWrNDy5csjG3QA9pe6+/zNcd3Fv5LX49Vf3v/urp11uUs05+379eBNr6tLcoZ1wYXZpyHcjVtbL63ZE/5YEH5W/h0WlNo76XVTP9CULVu2aOjQodqyZYvVoVjCLW0glM8ByR2jORprA/GxCUpN7qkeXWywGKmsz8esPn9zOOH9D0TZUWlTCNNbFpYZhXI4G7mAS3KBEJceCHU/O3HCZ4HVn8VWn7+5nNAGTqeqxlhPLViHK6TcA+GPBy2L23MBOJPH73fmPXtdu3ZVXl6e1q5dq5ycnJNer6urU2pqqoqKirRjxw717NmzyWNt27ZNffv21auvvqrrrrsu4BgqKysbRpOlpqbK621+XTH7+zPU76Lpjb5291ipXfyp928XJ3m9xmKUR6qb3u7IUenJd09+fvNHf9DG9x8PIuLQxEbH68VpkV1ZtbB4t6bNHqobL3lIl49s/kLDU5/O1LE6629x9kTF6AePBjFPzXG2fvy8Nvz7kTBHhHC7ambTk+efrh9obh8gSW880Fv1tafYOQzM6AOk8PYDVvUBU6ZMCWr7goICvfTSS/rJT36i1NTUgPZ5+eWXgw+smWgDzXP+Lf9Qp96jgt6vrGCLPvj9mAhEFDyz2sC37nnuQp3bb4KuvvDekI9hVhsY9ZO/qUvfxm/mCtfngNT0Z8Gqv01V/tf/DiLi0JjZBsLx/kstpx9I7naWLrpjYUj7fvbqHdq3/l9hjgiRRC7QPE7NBUb86CWd0f97Qe9XWbxX78wcEYGIgkcu0LRzb3xB6QMbH3VkRi7w+dw7tXfN/CAiDg1tIHTtOvfV9+7+KKR9v5h3n3avfi3MESGSnJoLIHIu/eVqtU5MVVVZgf796FBLY/H5fCooKJAk5eTkaO3atSEdJzqcQbUklZXGQlZHjzb+4TJ37lwVFRWpbdu26tGjxymPtWTJEklSv379Qo7n2zerubqfYq2wdvFSUoAzLHi9gW97vIrKSuXnR37187iYyE4VUX2sSg+9fLmG958UliKXJBXs36/q2qqwHKs5omLiQt63sqrKlPcXkRNoPxBqHyBJBQWFqq2J7GKBke4DpPD3A1b1AVVVwZ2zurq64Weg+1rRL9AGmudYoItz/Yd6n7/FfA6Y0QbCzaw2UF3T9FzDZnwOFJeUOCIfjISW0g/4WncPed+SsrIW0w8gMOQCoXNyLlBzLMDFuf6Dz2fN+90YPgeaVn206QqVGblAaak5nxW0gdDVRKWEvO+RI+Utph9AYJyaCyByvp22sr6+vkW9twcOhD6k1LGFri5duqikpERr1qzR8OHDT3itoKBA9913nyRp0KBB8ng8TR4nPz9fDz74oMaOHdvoyLBAhWtEV3yrpt+yQNZLCGY0R1PnT0tLO/2Jmik2+jRD05pp2Yb52lmwXvlF27R0/dyTXv/TvZvUqX23oI6ZesYZLeKuHUk6drRMsfGJQe8X7asy5f1F89QdO6ro2Mb/Rk7XDzS3D/D7fOrUMVnyJwUWbIgi3QdI4e8HrOoDWrcO7stfXFxcw89A97WiX6ANNI+vJsgFur5Rd/Rwi/kcMKMNhJtZbSDG2/SEDOH6HDjVsRLbxDsiH4yEltIPJMQZbcTv95/yu05jWkfVtph+AIEhFwidk3MBHTsS0m61VeQCzWFaLnCKq3lm5AJtE1qRCzShpfQDrb75XxdKLtDKW9Ni+gEExqm5ACInKiqq4afV7+3xI7o6d+4c8nEcO3Xh9OnT9dRTT6lr16768MMP1adPH0nS6tWrddNNN2nnzp2qra3VHXfcoaeffrrRY1RUVOjCCy9UYWGhVq9eHfBQzm8dP3VhRUWFEhISmvePkrEw7J+XnX67pjx8hXHHTmmV9PAbwe//4/OkwcHVf0JSf0xaMjvy5wmn0dOlqFirozDMWy0t3xbcPh6P9D+XSe2b30wRYU/8W8oL7Rp2s/uATu2kX04M7dzBoA8IXLBzam/cuFFXXXWV5s2bp+zs7ID2ycrKCiW0ZqENNM/GfOmPS4Pf77pzpXN6hT2ckNAGmvb2OumDjaHt29zPAUl68DKpQ5vQ9g0GbaB5fv+etLsouH0S46X/uVyKcuxKzs5ELtBytKQ+YPsB6ZkPg9/vyrOl8/uGP55Q0Aaa9sHX0tvrQ9s3HLnA/eOl1KTQ9g0GbaB5nvtI2loY3D4JrYw2EhMVmZgQGU7NBRA5Dy0w1vVNjJd+faW1sYSrhuLYrzAzZsxQhw4dtG/fPmVnZ2vgwIHKzMzUsGHD1LNnT1100UWSpMGDBze6/9GjRzVx4kTt2rVL77//ftBFrkhJT3b3+RGYkZnB7zMgjSKXXVj5d9iVPsD2+vTpoxUrVjTcAAJn6pcqJQfZp7eOlc4MfbYzmMjKz4HWscG3LVhjVAjd/IhMilxuQC7gDr07SV2CnOQjNloaeuqVHdBCWJkLxEQZN0Ci5RsZQjd/bi+KXG5ALgAncuzXmPT0dC1btkzjx49XXFycdu/ereTkZL3wwgt6++23tW2bMdylsUJXbW2trrrqKn3xxRd655131L9/f7PDb1JygnF3hRUSWnFhwy5Sk6RRQRS74mKk8TmRigbh1q2Ddeem0GV/MTExSk5OVkxMjNWhIIK8XumKIVIwk5RMPNO4wIWWz9LPgQ7GKHC0fDndpF6dAt++UzvpPK51uAK5gDt4PEYu4A2izx4/WIpvISNRcGpWfi9Lb89NEXaRnSZlBXHffnKCdGG/yMWDloNcAE7k6I+mfv36adGiRSovL1d5ebk+++wzTZ06VZWVldq9e7e8Xq8GDBhwwj4+n0833HCDPvroI/3rX//SsGHDLIq+cR6PNCTDmnMPyeDChp1ccbY0tOfpt4uPlaZeGPzdfrDOoK5StAW9t9cj5TDaw/b27t2r22+/XXv37rU6FETYwK7S5HMDu8A16UxpeO/Ix4TwaJ8g9exozbmtykMRvOgo6ebzpR4BrEXfqZ3009FSa4tuqIO5yAX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\n",
+      "text/plain": [
+       "<Figure size 2210.55x1204 with 1 Axes>"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def conv_layer(num_qubits, param_prefix):\n",
+    "    qc = QuantumCircuit(num_qubits, name=\"Convolutional Layer\")\n",
+    "    qubits = list(range(num_qubits))\n",
+    "    param_index = 0\n",
+    "    params = ParameterVector(param_prefix, length=num_qubits * 3)\n",
+    "    for q1, q2 in zip(qubits[0::2], qubits[1::2]):\n",
+    "        qc = qc.compose(conv_circuit(params[param_index : (param_index + 3)]), [q1, q2])\n",
+    "        qc.barrier()\n",
+    "        param_index += 3\n",
+    "    for q1, q2 in zip(qubits[1::2], qubits[2::2] + [0]):\n",
+    "        qc = qc.compose(conv_circuit(params[param_index : (param_index + 3)]), [q1, q2])\n",
+    "        qc.barrier()\n",
+    "        param_index += 3\n",
+    "\n",
+    "    qc_inst = qc.to_instruction()\n",
+    "\n",
+    "    qc = QuantumCircuit(num_qubits)\n",
+    "    qc.append(qc_inst, qubits)\n",
+    "    return qc\n",
+    "\n",
+    "\n",
+    "circuit = conv_layer(4, \"θ\")\n",
+    "circuit.decompose().draw(\"mpl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "0731f398-cce1-4d47-8c50-1b9cb79ae599",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 538.128x200.667 with 1 Axes>"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def pool_circuit(params):\n",
+    "    target = QuantumCircuit(2)\n",
+    "    target.rz(-np.pi / 2, 1)\n",
+    "    target.cx(1, 0)\n",
+    "    target.rz(params[0], 0)\n",
+    "    target.ry(params[1], 1)\n",
+    "    target.cx(0, 1)\n",
+    "    target.ry(params[2], 1)\n",
+    "\n",
+    "    return target\n",
+    "\n",
+    "\n",
+    "params = ParameterVector(\"θ\", length=3)\n",
+    "circuit = pool_circuit(params)\n",
+    "circuit.draw(\"mpl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "c1f94f5a-c1ab-4f95-ba88-c40d496065f2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1123.61x367.889 with 1 Axes>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def pool_layer(sources, sinks, param_prefix):\n",
+    "    num_qubits = len(sources) + len(sinks)\n",
+    "    qc = QuantumCircuit(num_qubits, name=\"Pooling Layer\")\n",
+    "    param_index = 0\n",
+    "    params = ParameterVector(param_prefix, length=num_qubits // 2 * 3)\n",
+    "    for source, sink in zip(sources, sinks):\n",
+    "        qc = qc.compose(pool_circuit(params[param_index : (param_index + 3)]), [source, sink])\n",
+    "        qc.barrier()\n",
+    "        param_index += 3\n",
+    "\n",
+    "    qc_inst = qc.to_instruction()\n",
+    "\n",
+    "    qc = QuantumCircuit(num_qubits)\n",
+    "    qc.append(qc_inst, range(num_qubits))\n",
+    "    return qc\n",
+    "\n",
+    "\n",
+    "sources = [0, 1]\n",
+    "sinks = [2, 3]\n",
+    "circuit = pool_layer(sources, sinks, \"θ\")\n",
+    "circuit.decompose().draw(\"mpl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "d6f5c6fd-ae32-453b-b2f8-49f5d5bbeb8f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_dataset(num_images):\n",
+    "    images = []\n",
+    "    labels = []\n",
+    "    hor_array = np.zeros((6, 8))\n",
+    "    ver_array = np.zeros((4, 8))\n",
+    "\n",
+    "    j = 0\n",
+    "    for i in range(0, 7):\n",
+    "        if i != 3:\n",
+    "            hor_array[j][i] = np.pi / 2\n",
+    "            hor_array[j][i + 1] = np.pi / 2\n",
+    "            j += 1\n",
+    "\n",
+    "    j = 0\n",
+    "    for i in range(0, 4):\n",
+    "        ver_array[j][i] = np.pi / 2\n",
+    "        ver_array[j][i + 4] = np.pi / 2\n",
+    "        j += 1\n",
+    "\n",
+    "    for n in range(num_images):\n",
+    "        rng = algorithm_globals.random.integers(0, 2)\n",
+    "        if rng == 0:\n",
+    "            labels.append(-1)\n",
+    "            random_image = algorithm_globals.random.integers(0, 6)\n",
+    "            images.append(np.array(hor_array[random_image]))\n",
+    "        elif rng == 1:\n",
+    "            labels.append(1)\n",
+    "            random_image = algorithm_globals.random.integers(0, 4)\n",
+    "            images.append(np.array(ver_array[random_image]))\n",
+    "\n",
+    "        # Create noise\n",
+    "        for i in range(8):\n",
+    "            if images[-1][i] == 0:\n",
+    "                images[-1][i] = algorithm_globals.random.uniform(0, np.pi / 4)\n",
+    "    return images, labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "3760bf19-7427-428d-8479-95bb7dc1bbf3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "images, labels = generate_dataset(50)\n",
+    "\n",
+    "train_images, test_images, train_labels, test_labels = train_test_split(\n",
+    "    images, labels, test_size=0.3\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "24666f27-d9d7-473a-b905-664797788e1a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1000x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(2, 2, figsize=(10, 6), subplot_kw={\"xticks\": [], \"yticks\": []})\n",
+    "for i in range(4):\n",
+    "    ax[i // 2, i % 2].imshow(\n",
+    "        train_images[i].reshape(2, 4),  # Change back to 2 by 4\n",
+    "        aspect=\"equal\",\n",
+    "    )\n",
+    "plt.subplots_adjust(wspace=0.1, hspace=0.025)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "8809b9b2-2c08-47a6-868f-d3ea8d3a29e2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 454.719x702.333 with 1 Axes>"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "feature_map = ZFeatureMap(8)\n",
+    "feature_map.decompose().draw(\"mpl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "f47015ae-1eb5-41ce-b758-295c7bae8e54",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "feature_map = ZFeatureMap(8)\n",
+    "\n",
+    "ansatz = QuantumCircuit(8, name=\"Ansatz\")\n",
+    "\n",
+    "# First Convolutional Layer\n",
+    "ansatz.compose(conv_layer(8, \"с1\"), list(range(8)), inplace=True)\n",
+    "\n",
+    "# First Pooling Layer\n",
+    "ansatz.compose(pool_layer([0, 1, 2, 3], [4, 5, 6, 7], \"p1\"), list(range(8)), inplace=True)\n",
+    "\n",
+    "# Second Convolutional Layer\n",
+    "ansatz.compose(conv_layer(4, \"c2\"), list(range(4, 8)), inplace=True)\n",
+    "\n",
+    "# Second Pooling Layer\n",
+    "ansatz.compose(pool_layer([0, 1], [2, 3], \"p2\"), list(range(4, 8)), inplace=True)\n",
+    "\n",
+    "# Third Convolutional Layer\n",
+    "ansatz.compose(conv_layer(2, \"c3\"), list(range(6, 8)), inplace=True)\n",
+    "\n",
+    "# Third Pooling Layer\n",
+    "ansatz.compose(pool_layer([0], [1], \"p3\"), list(range(6, 8)), inplace=True)\n",
+    "\n",
+    "# Combining the feature map and ansatz\n",
+    "circuit = QuantumCircuit(8)\n",
+    "circuit.compose(feature_map, range(8), inplace=True)\n",
+    "circuit.compose(ansatz, range(8), inplace=True)\n",
+    "\n",
+    "observable = SparsePauliOp.from_list([(\"Z\" + \"I\" * 7, 1)])\n",
+    "\n",
+    "# we decompose the circuit for the QNN to avoid additional data copying\n",
+    "qnn = EstimatorQNN(\n",
+    "    circuit=circuit.decompose(),\n",
+    "    observables=observable,\n",
+    "    input_params=feature_map.parameters,\n",
+    "    weight_params=ansatz.parameters,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "ef995a89-bb0c-4957-b266-82ce20a50c4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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gmHTu2DO9uh5Yq31j1HDiQcPz4IzfZPR1g3PcgV/IylUr8qcnbs5WLVa/9dLuXfZ79/Z8f/5+li5bnJYtSlPWvnv23PmAOrd91L7n5L5pv8yEB8bklUVz02eXw7Kg4vnc8ehPs22bHfLZdZg5V5e9uh+S9m3LMu7OkVm4eG46bt05cxbMyJ+m35zuZX3y4sKn67Xd96xa9U5+/afv1dl2SJ+T67X/pk2a5uj9Pptf//nd7X726NVf++5d9sunh1ySm+6/JF/4Yf8c1vfUbNduxyxaUp7ZLz+Rx/9xV+7+wYoNem1AcQ3oOSSH9zstD874TZa+tTgH9Doui99cmDse+UlaNGuZL584tl59N5XPfPx7eeLZe/ON64/OiQcNT4etO+exf0zMG/8bDq3PLOEnn/9zVqxcvtrydqUdcvzAL+SwPqfk+rsvyjd+MTSH9Dk5by1fkklP3lL79rAfcOQ+w3LdxFH58/Rfpax99+z9gZnRSTLi5GvztZ8ckpHXHpbBAz6d3XbcO9XVVSlf9EIemfmHDBnw6Xz6qEvW+XUAAADA+hJ0Aetlpw675dqvPpmJfx2XyU/fllsmfT/L3l6atq3bp2fnfTPq9F/myL3PqOl/wkFfSvu2nfI/D12ZX93/nSTJLjv2yyVn317zbfoN8bF9huUXd12Yt5YvqQnYPmhDa9ir+8EZdfqNGT/psvx84qh0aLdTjhv4xfTssm9Gj6t90W/7bXfOyNNuyIQHxmTs776YlaveyZABZ68x6GrWtHkuP+/e3PKn7+XBpybk4b//Lm1abpPD+p6azxz9vWy/TZf1e0P+V5tW2+Tyz92bn08cnT9MuTqrqlamx04D8v3P3pW7H79+g4Oud1atyI33fqvOth077JauO/Sq1/6HHvC5jJ90WVq2KM1h/U6ts89ZR12cnl32ze0Pj83tk3+U5Ssqs02b7dOtbK98aTNcmAY+2i761K+z20775L5pN+a6P45Myxal6bvL4Tnn45eme6c+9e67KXTZfvf81xf/kuvu/Hpuf/jHadGsZQ7Y87h85d9+kk9fvku2quP5Vmsy9dl7MvXZ1W9D2KXj7jl+4Bdy6hGjUp3q3PP49bn2Dxdk27ZlOaLf6Tlqv8/kc1f1qnObpS3b5Yh+p+eeqTfk4/t+ps7gbfttuuSnX30iEx4Yk0dm/iF/nv6rtGjWMh236ZIDex2fw/udtu5vCAAAANRDSXVDPRF7C1BZWZk2bd69jdnSpUtTWlq63ttYtSJ5wHVbYAvx2pLynPH9Lhm637n56injGroc+FCDRiRNW2z4dhzveb/n5j+RL/9435w79PJ88sj/aNBaxv7uS5n42HX51UVz03Gbzg1aSxFtrDECAACANTOjC4CPjD8+em2qqlblmAPPb+hSADaLt99ZVmvmVnV1dX774BVJkn161v85lhtD5bI38ufpv8r+uw8Vcm1m1dVJ1TsNXQVQX02aJ+tx99mNyvjBxtKQn2MAWF+CLgAa3AMzfpNXF/8z//Pgldm358fTs/OAhi4JYLP4wg/7p/+uR6Z7pz5ZvqIyf33mj3n6xck5ot/pDTYWvrjw73n+5Sdz/7RfZtmKpfnUkd9okDq2ZFXvmOUJRdaQszmNH2wsZiUDUCSCLgAa3GW//lRaNGuZvbofmpGnXd/Q5QBsNgf1OjGPzvpj/jT95qyqWpmy9t1zzscvzemDLmywmib/7dbcfP930mHrnfKVf/tpenUb2GC1AAAAwIcRdAHQ4O6/0uMigS3TecddkfOOu6Khy6jl00ddkk8fdUlDlwEAAADrpElDFwAAAAAAAAD1IegCAAAAAACgkARdAAAAAAAAFJKgCwAAAAAAgEISdAEAAAAAAFBIgi4AAAAAAAAKSdAFAAAAAABAIQm6AAAAAAAAKCRBFwAAAAAAAIUk6AIAAAAAAKCQBF0AAAAAAAAUUrOGLmBTq6ioyBVXXJHf/e53mT9/fjp27JiTTz45l112WUaMGJEbbrghV199dYYPH97QpdbL/H89lz9N/1WeeO6+lL82JytWLk+n9rvmsH6n5uRDv5pWLUobukQAYAM53gPvV1VVldsf/nEm/nVcFi6em21KO+awfqfl7I9/13gArJXxAwBojBp10DVjxowMHTo0CxcuTGlpaXr16pUFCxZk7NixmTNnThYtWpQk6d+/f8MWugHumXpD7njkJxnY64R8bO9hadq0eZ6a80BuvOc/85enfpuxX/lrtmreqqHLBAA2gOM98H7X/vFr+f3DY3PwXv+WUw4fmX++Miu/f3hs5rz8ZMac/6c0aeLGHUDdjB8AQGPUaIOuioqKHH/88Vm4cGFGjhyZiy++OG3btk2SXHHFFbnwwgvTrFmzlJSUpG/fvg1cbf0d2ueUfGrQRSlttXXNsuMHfiE7deiRW/78/dz9+PU56eBizlYDAN7leA+8Z+7CmfnDlKtzyF4n5+Kzb6tZXta+e37yhxF58Knf5Mi9z2jACoGPKuMHANBYNdqv6owYMSLz58/P8OHDc9VVV9WEXEkyevTo9OvXLytXrky3bt3Srl27Bqx0w+zeZd9aF73ec0S/05Mkcxf+fXOXBABsZI73wHsemDE+1dXVOfnQr9ZafswB56Vl89b50/RfNUxhwEee8QMAaKwaZdA1a9asTJgwIR06dMjll19eZ58BAwYkSfr167da2+23356DDjoopaWl2XrrrXPwwQdn5syZm7Tmje1fb8xPkmzbZocGrgQA2FQc72HL8+xLU9OkpEl233n/WstbNG+ZXXbsn+demtpAlQEfdcYPAKCxapRB1/jx41NVVZVhw4alTZs2dfZp1erd51h8MOgaO3ZsTjvttBxyyCG54447Mn78+AwePDjLli3b5HVvLKuqVuXXf7o0TZs0c9sBAGikHO9hy/TakgVpV9ohLZpttVpbh613yhuVFXln5YoGqAz4qDN+AACNVaN8RtekSZOSJIMGDVpjn/nz3/0G9PuDrjlz5mTUqFH54Q9/mOHD/+85F8ccc8wmqnTTuPaOr+aZeY/ms0MvS5ftd2/ocgCATcDxHrZMb694K83ruEidJC2atXy3zztvpXmzFpuzLKAAjB8AQGPVKIOuefPmJUm6du1aZ/vKlSszZcqUJLWDrhtuuCHNmzfPeeedt9Fr6tGjR5o0Wf8JdC2atcp1w2evc/8b7/lW/jDlmhx7wPn51JEXrff+AIB116Nnj6xYueGzvh3voXGq7xixtjFhqxats2zpq3W2rVi5/N0+zVuv9z6BjWdjnR/Uh/GDjaUhP8cAbJnKysoybdq0eq3bKIOuysrKJFnj7QYnTJiQioqKtG3bNt27d69Z/sgjj2T33XfPr371q3zve9/LSy+9lB49euTb3/52PvWpT21QTeXl5fVar+V6nGTedN8l+fWfv5eP7/eZXPCJn9VrfwDAuitfsCDL33lrg7fjeA+NU33HiLWNCdu12zH/fOWZrFj59mq3H6t44+VsXdrBbAxoYBvr/KA+jB9sLA35OQaA9dUog66ysrIsXrw406dPz8CBA2u1lZeXZ9SoUUmSvn37pqSkpFbbyy+/nIsuuihjxoxJly5dcv311+eMM85Ix44dM3jw4HrX1KlTp3rP6FoXN913SW6+/zsZMuDs/Pspv6j1ugCATaPTjjtutBld68LxHoqlvmPE2saE3bvslyeeuy/P/vPx9Nnl0JrlK95ZnhcWzEifXQ6rV63AxrOxzg/qw/jBxtKQn2MAtkxlZWX1XrdRBl2DBw/OrFmzMmbMmAwZMiQ9e/ZMkkydOjVnnXVWKioqkiT9+/evtV5VVVWWLl2am2++OSeddFKS5GMf+1ieeeaZXHrppRsUdM2ePTulpaXrvd6qFckDY9fe5+b7v5ub7/9OBu9zVr5+2g31CtQAgPU3+7nZaboRvvjseA+NU33HiLWNCUf0Oz3jJ12W303+Ua0L1Xc99vMsf+etHLn3sHpWC2wsG+v8oD6MH2wsDfk5BoD11SiDrtGjR+eWW27JSy+9lN69e2ePPfbI8uXL8/zzz2fo0KHp1q1b7r333lrP50qS9u3bJ0mtQKukpCSDBw/OjTfeuDlfwjr7w5Sf5Kb7Ls722+ycfXoMzqQnb6nVvm3bHTKg55AGqg4A2Bgc74H3dO/UJycc9OX8Yco1ueSXJ2f/PY7JP1+dld8/PDZ9dzk8R+59RkOXCHxEGT8AgMaqUQZdnTt3zuTJkzNq1Kg89NBDmTt3bnr16pVx48blvPPOy6677pokqwVdvXv3zmOPPVbnNpcvX77J666PZ1+amiR59fV/5ooJZ6/W3neXw134AoCCc7wH3u+LJ/woO2zbLXc9dl0enzUx7Uo75KSDv5KzP/5dsz2BtTJ+AACNUUl1dXV1QxexOS1dujTt2rVLSUlJ3nzzzbRu/X8Par3jjjty4okn5rbbbsvJJ5+c5N3bGfbv3z/t27fPgw8+uF77qqysTJs2bWr2u6luXQgANIxBI7LZbl0IFE99xwhjAhTbxjo/qA/jBxtLQ36OAWB9NcoZXWszc+bMVFdXp2fPnrVCriQ5/vjjc+ihh+b888/Pa6+9lp133jm/+MUvMnPmzNx///0NVDEAAAAAAAB12eKCrqeffjrJ6rctTN59Htcdd9yRCy+8MN/4xjeyZMmS9OvXL3fddVeOPPLIzV0qAAAAAAAAayHo+oBtttkm48aNy7hx4zZnWQAAAAAAAKynLe5Jox8WdAEAAAAAAFAMW9yMrkmTJjV0CQAAAAAAAGwEW9yMLgAAAAAAABoHQRcAAAAAAACFtMXduhAAgP+z4p3l+f6vP5l5rzyTrZq3yjZtts+Ik6/NTh12S5KceVm3NG+2VU49fFSOOeBzSZK7H78+v3ngB6muqkr/3Y7MiJN/mmZNm+fpFybnmt9/JS+UP5Xbv7s4bVpts1lqWrhobq6ccE6eX/BkyrbtnnH/PqNmWw1V05PPT8r1d/1Hlr29NCUlJTlgj2Nz7jE/SJMmTbKgYk6+c9Mn8s9Xn8nVX3k8u+3Uv141JcmVEz6TmXOnZKvmrdKyRZt86cQfZfcu+yVJRl57RF5dPC9H7feZnDXk2ylf9GIuvemUrKpalaqqlemyw5752ieuS9vW2zZYTe93xW/Oyf1P/LLm3+ntd5ZlxNUDs+C15/Mfn/pVDt7rpHrXdP3d38iUp3+X5s22StOmzfOZo7+f/Xb/eM1+p8++Pwf2Oj5f/cTPkiRDRpWkW9leaVLSNEky/KSr02eXQzdqTXx0jbz2iLyyeG5+9Y25G33bT815MF//2aB8/bT/zsf3O2ejb39DvPc7eP+V1Q1dCqxmyKiSDBlwdkZ/8saaZWde1i07bNst//XFBxusLgDgo0HQRb2t70WMvz5zZ6678+tZVb0q3cv6ZNTpN6a0ZbuNdmFlfS9gfPemUzJz3iNZtKS81oWvjXUB4/aHx+auv16XlJSkJCU57YjRGTzgzCTJTfddkjse+Un27Dowl37mjg+9eHb5LcPy5Ow/54j+n8yXTvxRvepZ2wW3p+Y8mG/8Ymg6d9w9Pzj/vmzbZvvccPc38+gzd9Rc4Pnkkf+RQf0/mSS57s5RefCpCemx0z75zjm/r1c9L5Y/natv/3JeX/pqmjZplt133j9f+befZKvmrbJw0dyc/YNd0+1/Pyfv/0wsXvpqzv+vPunVdWDNvh+cMSE33/+dvLZkQX5/6ev1qmd9L2C+/z17z9ivPJqtmrfaaBdV1/d37NXF/8zVt3858yueS5OSpjl+4Bdz0iFfaZDfsRfLn84Pxp9Vs27l8tfz1vIl+d13FyVJvv6zQXlhwVM5c8i3c/KhX61XPQ/M+E1+M+kHqapamSQ5ar/P5NTDRyZJ7p16Y356xwXZqUOP/PSCaUmSf/zz8fzkDyPyzsq3s2Ll8nx838/k9EGjkzTMZ3rxm6/kx7/7YhZUPJ+VVe/kuAM/X/NeNMRnem1BQbLpg431+bwve3tpvnPTJzJ7/hNZVbWy1nu0traNeSG/sTnmgPOz/x5DU1JSkt9PuSb/738+V+ui0TeHTah5v8oXvZgb7/1Wrr1gerZtu0O+feOJmfjX63LiwV9On10Ozbh/n5Eho0o2a02tW7bLZ47+XiqXv5Eb7v5mre00VE1tW22bbw77TTptt0tWvLM8o68bnPufuCkf3++c7Nhh14z79xk587JuG1zTwXv9W/79lJ+nadNm+eszd+bSm0+tdXH+Cyf8sOZcZrt2O+aHX344WzVvlST5yR8uyE33X5Ivn/jjBqvpPZOf/l2aNW1ea9lWzVtl3L/PyMhrj9jgmvp0PzRnDv5WtmreKnMWPJV/v/aw/OZbC9KqRWmS5LQjRq12PPrhlyavNqZtzJqKbvmKt3LXY9dl8tO3Zd7CmXnr7TfTtnX79Og8IIf3PS2D9zkzTZtumf/dfP7lGXlk5u9z1L7npKx9t4YuZ5MYee0ReW7+tPzx+0sbuhQ2g/cC2vdr2aI0XTrunsEDPp0TDx6epk2aNlB1Deu99+b8Y6/MqUd8vaHLAYAt1pb5Pw82ivW5iLHs7aX5r/85N//1xYey8/Z75Orbh+fXf7o05x935Ua7sLK+FzCOO/AL+crJP81p39mh1nY21gWMrjv0zo++PCWlrbbOq6+/lC/+cO/06jowO3bYNUly5N7DaoVWa7t4dtEZv85N912Spcter3c9a7vgliSdO+5e68L2aUeMymeHfj9JUvHGyzn3yj2zT4/B2bq0Q84/7sp03aF3Hpn5+3rX07xZyww/6ZrssmPfrKpalctvOSMTHhiTTx91SZKk1VZtV7vQniQ/vvXzOXDP47Lkrddqlh3R//TssfMB+cIP+9e7nmT9LmAmq79n79lYF1XX53esuro6l/zy33L6oP/I4f1OTZIsfvOVJGmQ37HunfrUem+uvn14Skr+7/246gsP5IrfnLNB9XTcuksu/9w9ad+uLJXL3siXfjwgPTsPSL9dj0iS9N91UK3Q6oe3np+zP/7dHNT7hCx5a1HOvWKPHNjruHTdoVeDfKZ/9sd/T9cdeuWSs3+XZSsq89VrDk7vbgdn9y77Nchnem1BweYINtbn8960afOcPujCtG3VPl//2RG1trO2to15Ib+IhowqyRkf+2YemzUxy1dU5qwhF+dj+wxLi+Ytc8Cex9T023PnA3PrQ1etcTuT/3ZrBvY6Ie3blSV593g6ftJlOfHgLzdYTe1at89e3Q/JU3MeXO8aNlVNu+20d83fWzRvmV137J9XFs+tV01nXtYth/U9NTOen5TK5W/k2AM/n9OOGJUkOaj3Cf9XU9cDU/HGy1m1amWdAUOLZlvV/H1V1aosX1GZVi3aNGhNybvHq/GTLstVn38gdz/+i3rVk7x74b17pz6ZNe+vWbpscQb2PjGfP+6qlJSUZP89htb0617WJ6muzhtL/5VW7Uvrvb8t2csVz+c/bzg28//1XPbpMTifPPKitCvtkNeXvponZ/8pV/32M/nnK8/kvOOuaOhSG8ScBTNy8/3fSb9dj1gt6OrT/bBMvGxZmn4g2IUiGNT/U9l/j2NSneq8tmRB7pt2Y66946uZ98rMfO2U6zZ7PTeMfjYl2fAvsgAAxSfo4kM9M/fRXDdxVJa9/Waqq6tzzscvzUF7nbheFzEe/8fd2W3HvbPz9nskSU446Ev5j58flfOPu3K965n3yqxce8dXs2hJeZLk+IO+lOMHfmG9L2Ds03Pweu+7LhVvvJyf/uGCvPSvd0+yD+p9Ys45+tLs0+NjNX2236ZL2rcty7/eeKkm6Hq/9b14tjbvrFyR/77nm5n6j7vTpEnTtG/bKZefd896X3B7/zeYl729NNWpTlV1Vb1q+s0DY/Ln6b9Kk5ImadG8Va78/KR07tijpr1pk6bZvfN+eXHh39e6nbsfvz5l7bune6e+GxRIPDZrYm6675KsXLUiSUm+esq47LnzARvt32B9bYzfsSdn/znNm21VE3IlybZtd1it37rYWL9j71nxzvJMevLXufLzD9Srnsplb+Rnd47MP+b9NU2aNE2PzgPy9dNuyF7dD67pU9pq63TZfo8sXDQ3/Vb/FUuSlJSUpPJ/w+LlKyrTrFmLtG3Vvl41bYzP9AsLnsoJB70bDLRqUZq+uxyWPz1xc80spvWxMT7TawsKNmawsTE+7y2abZW9dzsyCxfNXa82kpKU5GdfezLlr72QL/943/TudvBqF2Fvf/jHGdj7xDVu49XX/5kdtu1a83NZ+2559fV/NmhNG9vGrmnRkoWZ/Ldbc+ln76x3TYvffCU/uWBalrz1Wr74o33Su9vB6d3toNo1Tf5x9t/jmLXOonln5YoMH7t/Xn19Xrp36ptLz7mjwWv6f7eel/OOvSKtW7atdy3vmffKM/nx8EeyctU7+fdrD8sDM8bnyL3PqNXn3mn/nbL2u9T6HNdl9LiPZVXVyuy928dy9tGX1nyxY0v39jvL8q0bjkv5ay/k25++LYf2OblW+ycHXZhnX5qaZ1+a2kAVfrQ1adIkLZq0bOgytnhvLX9zo4w5W5oeO+1Tc5eSJDl+4Bdz7pV75u7Hf5FzPn5pvf//UV/v/wIH9bNy1TupqlqVFs2NSwAUm6CLtVry1qJc/MuT8u2zbk2fXQ5NVVVVli5/fbV+H3YR44MXxXbYtlsWLSlf67d767Jq1cpcfOOJ+fRR38mRe38qSfJGZcVq/db1AsbG8IPxZ2ZAz6Py7U/fmiR5fem/Vusz/bk/5c1li9NzHS9gb8gFvd9Mujzz//VcfvLVJ9Ki2VZ11rOuF9xuf3hs7njkJ6l4fX6+duovsm2b7de7nvum/TIPP31bfvSlh1Paauu8+dbiNP/Af0iWrajM3Y//Ip8devkat1O+6MXc+ejP8v++9Jc8OGPCetfxnvn/ei5XTfhM/utLf8nO2++Rlaveydsr3lqt37r8G5QvmpMv/v/27ju+xvP/4/jrnAwZQoIQm9gjhNh7r1odVtWqGrVbRVtt8aMUbbWKopTaWi1ae89qbaJG7RkjQiJLZPz+SHO+jgw5cSIS7+fj4fGQ+77OfX9yco9zrs99fa5vKmI02NC0cg9a1+hncTzWOscu3z5JVmd3Pl/Ukat3zuDhVog+rb4id3ZPi+JJjXNsz4nfyJ3NM8Vl4mb8PuS/kZbHMRqNCR7Tl2+d5OTlfQx+bWai2/mg/TxGzW/DvI2fEBh8hyGvzzIlbixhrWO6WD4fth1ZQqkC1QgKvcvBfzealcJMLmse04mxVmLDWse7pFzz/+bYyp3dEy/POvhe2GWWwFmydTw3/M8xqc9WxWSlmELCg/h0Xiva1xtOifyVUhxTsyo9MRgMZHXOQa2yr3H47BazpNKWQ4vYefxnvn53V5LbsbO1Z9b7R3kUGcH0VQNZ89csUxnXtIhp3d9zyOlagApFG6Qohic19umKrY0dtjZ2NKr4FofPbjFLdB0+u5WFm8cwsddms5HGT1r88WVyuhUgLCKEb3/tyw9rhjHotRlWiTG9W//3HK7eOUOH+iPiJbnilMhfOd6DG3tPrOLnHZO5cOMoGAx45i5Ph3rDqVHW/N4UN+fO4NdnMuuPofhe3IXBYMSnWGMGtJ1munf/8ef3TF3ZjzHdV5s9LAEQHR1N5/EFyOKUw2w0dXJjSEhicwE9OefWgk2jWbh5DIBZqbe4uYUSm6MrLCKEJVvGsfPYz/gHXiOzoxs+xZvQvdlYs3vw46+PIYYVO7/khv853Fw8aF2jf7zz+eCZTWw4MJczVw8QEOSHnW0mSuSvwpsNR1K+SN2n/t7PKrn7/2xeGw6f3czyz27i7JDFbBtnrh5gwNQqdG0yxmxuvx1Hl7Nq73dc8DtGdHRsefx29YZRp9wbZq+Pm9upkU8XFmwaxfkbRymer5LmdbICZ4cslC5Ynd2+v+J39wJuLrmIiorkl11fsfngT/gFXMDB3plyhevQren/UTi3l9nrLWmbkITOy+ReQ+JcuHGcWWs+4OSlvdjZOVCtVEv6tPqKN0a7x5sT7FmEhj9g+Y6JHP53Mzfunifs4QPcXfNTu9wbvNXoMxzsnQA4d/0I735TkU4NPjZVWHncyLmvcOLibpZ95md6AONukB+LNv8ff59ey70HN8ninINqpVrSvdk4s+/wcdenH4aeYMP+uew8/jMBQX5M6rPVVBVDREQkvTKmdQDyYjt1eR/53Uvg5VkbiH0CMYuT+QiIuE6M51Gq4OqdM0REhps64AGyOucwaxPXgfHJW8uT7MCwhrCHwZy4uIc36gw1LXPN7G7W5qKfL1/+3INP3lqerCeB4zrPeibRQZ6Uv06t4dXag01Ptz0ZjyUdbq/WGsS84Wf4ZsCfLN02nqCQu0m2TyyeltX64uyYFQAXJzez+u2PIiP4fFEHfIo3oZbXqwluIyYmhq9+fpsBr04zzSuSUof+3UylEs1MowttbexMscVJzt+gaN6KLB15je+HHGZ0t5Ws2TeTncd+tjgea51jUVGRHD2/jc6NPmXme0fwKdGUsYvaWxxPapxj6/fPpVmVnhbHEufvU2toV/cDjMbYW9aTx/Sd+9f4bH4bBr82E3fXfIluZ/n2L+jZYgJLRl5hzgf/MG/DSC7fOmlxPNY4pgH6tPqKsIfBvPtNBSYseZPynvWwMVqe2LHWMf08vGj3FAEeO4d/2fEle078xvh31ps6WxKS07UAt+5dNv18M+ASOV0LpGlMqS6FMYWGP+DjOc2oUaYNb9R937ohPVaqacfR5SzcEpu8Se7T9Ha29jSp3IMthxemaUzHzm9n3z+reWt8IVNZ0d5fl+Pc9SNWj+nY+Z18+XMPxvb4g/w5k36wIKdb7DHtaO9M6+r98L242yrxZAS7fGMf7nqlau9kv+b3P2cw+qdXeRAWQOfGn9G50ac8CIt9+GHtX/Gv9/5B1/ng+3rkdC1Ar1cm08D7Tfac+I2Jy7qa2tTz7oidbSa2HFoQ7/VHzm3FP/A6TSp1S3EMKVWr7Gum96ZTg48Z0XEhIzoupGW1Pom+JjLqER/90JRl27+gaL6K9G09hfoVOrHz+M8MnFqVO/evxXvNmr9msnjz/1HfuxO9W31Ftiy5mbNuBNuOLDFrt+ngfB6EBtDYpyv9237H67Xf4+rtUwyf3RDfC6l/XCd3/y2q9uLhozC2H1kabxvr98/FaDDSrPLbpmXzNnzC54s74pTJhe5Nx9KzxRdksndi7MJ2rN47Pd42zl47yOif2lIyfxXebT2FhhU7p84v/JKJiYnhuv85ALL8951hwtLOzF33ITmy5qP3K5NpWa0vR89vZ9C06vGu7Za0tURyriEA1+6c5b3va3Pqyj7a1hpE1yZjuB9yh4/mNEvxvpOKaf3fcyiWrxKdG31Kn1ZfUzRvRX7eMYnRP/3vO0PRvBUols+HzYd+Iio6ynwbgdc5+O9G6nl3NPUt3L53hf7fVmK37woaVHiTga9Op1HFLuw4uowh02sSEhYYL5YJSzpz8vI+3qgzlD6tviKbS26r/74iIiLPmx6VlmcS14kxuffWJDsxcroW4PC/m00/37p3iWxZclv9aX1LOjCeh8u3TvLJjy0Z2v5Hyhau9dT2cZ1nk3pvSZUOvZR2uBXJU54cWfJy7PwOapd73WrxREY94vNFHcjmkpt+bb5NtF1oeBAX/I7z+aIOQGyC8eGjUIbNashkKz/hn9y/weNPmrq75qN+hU74XtxN3fKWJ5eSkuxzzK0ARfNUoJBHGQAa+XThu5X9iIx6hK0V54Cw9BzzC7jI6ct/Marrr1aL4XH+gTcYMbsRnRt+Yla28UmBIf7sPbGSkW8tA2JHaZQsWI1/Lu2lYK7SVosnucc0xCYQH39C9Jtf+1IoVxmrxRLHGteVnK4FuHH3vOlnqyc2/pPc411SbuOBeXRtMpqbAZfwvbibd1t/A8CKnV+z/ehSJvbeYla6NiG1vV5nyIxadG08GjeXXKz5ayb1vDsm2n7i0q7ULPtqoolfa8RkqecRU9jDYD6a04xKJZrRudEnT41p7rqPyJ41L21rDkhw/aaD8ylfpC5BoQHsPbGSjzvHdgbvPPYz8zZ+wqTeW0zJmcTcuneZrM7uONg7ER0dza7jv+CZu1yaxvTRm4vNfm48zMDs948n+v6u2juNu4HX6dki4cT91sOLaFDhTaKiI9l2ZAmv1X4PgOMXdjFxWRf+r/tqiuQpn2RMcSN1496nHceWUzRPhSRf8zK5dPMETg5Zkj1q/EHoPX5YO5w82Yvw3cC/TZ+hWlV/l3enVGDWmqHULd/e7G9+w/8cn7y13OxzlcFg5I99M7h6+wz5c5bAxcmNaqVb8dfJP3gQeg8XJzdT282HFmBjtKXBf8mMlMSQUp55ylGqYHXW/j0bn+KNkzVKYtPB+fxzaS/t6w4zm9esYrFGfPJjS+au/4gPO5knpW/fv8KPH5wyPdzSrPLbvDW+IKv2fGc2ivG9dj/Ee9iuZfW+vPNlGZZun2B6+CS1JHf/lUs2x901PxsOzKVl9f8lBcMjQtl+dCk+JZqaHmg6e+0wS7Z+TscGH9Gz+XhT21drDWLU/Lb8uP4jGvt0NStNeOnWP0zstdlq5etfVuGPQgkM8ScmJoaAID/TiLpSBaqRz70Yh/7dzM5jP1O3fHtGdl5meiiubvn29PvWh+mrBzGlX2yC05K2lkrONQRg3oaRhIYHMaXfHlNZ9LY1BzBuUQfOXjuU4vcpIbmzebLkk6tm383a1OzP/A2fsnjrOE5f2U/JAlWA2AcJvvm1DwfPbDQrRb7x4Hyio6NoXuUd07JpqwYSFfWI74ccMXvor065dgyaVo1fd08xzRkcJ7OjK5N6b1H1BBERyVA0okuSVLpgDa77nzU9bRcdHU1QaABgWSdG5RLNOHf9MFdunwZin6isVz7xTrG56z5i1d5p8Zbndy+Bg50T2x570i+urJolHRiWWrV3GnPXfRRvuWOmzHh51mHFrq9My+LKql2+dYqRc1sw5I3YL7lPY+o867X5qV+yT1/Zz7BZDRNcV710a1bu/paIyIdm8Vja4fb4SJcb/uc5d+MIBRJJCPgHXuftSSUTjWfNXzNNT5IFh90nKjqKqKhIPl/UERenbLz3xuwkRwY5O2bltzF3WfTxJRZ9fIneLb/Ep3iTJJNcw2Y15PSV/fGWVyrRlIP/bjQdi5FRj0yxWfI3uBvkR3R07JxloeEP+OvkmiQ7wSYu7coe35XxllvtHCvZnDuB1/APvA7A/lPrKJCzVKJJrud1jm3c/yM1y7761Pdzj+9KJi7tmuC66qVb88vOL03vd9wxfTfIj+GzG9K+/gizJ7YTktnRDQd7Z46c22b6nU5f+ZtCucom2D61j2mAoJC7REY9AmJLlPx5YhWtkih/mdrHdFJqe73OvpO/ExB0k5iYmGQlNlLzeJeUi46Oou+UCnz4QxP6t5mKR7ZC3Ll/jVlrhhIcdp8PZtanz9feDJxaNdFt5M7uSbcmYxgyvSbdviiKq7N7kiMV/r12EHfX/KkaU3hEKJ3G5WPswnZcuX2STuPyJXjffp4x/bbnW85c3c8e39/o87U3fb72ZvHW+CWI4pz3O0Y2l8TLqbo6u9PvGx8GTq1Cm5oDTCUCJyzpzKNH4Xw2r41pP4mNwL7gd5xB31Wj91fl6PN1OQKD79C/zdQ0jclSV26dJItT9kTXF8hZiiHTa9L7Ky/KFq5N/f+uVV/90pNHkQ+ZvLyHKaaLfr4JbuPq7dMM+q4afb4uT++vvWLnIGvzjVXizwhCw4NwypT8uY0On91MeEQIbWsNMntQyNkhC21rDSLsYTCHz24xe032LHniPTwUV97yuv9Z07ImPt14FPmQHcf+V9Y67GEwe0+spHKJZqaSXSmJ4Xnac2IlRoORjg3Mr1tVS71CkTze7PtntelzUJymlXqYjeB2sHeiVIFqZu8PYJZkCnsYTFDIXYxGG0oWqMrpK3+nwm9jLrn7tzHa0Kzy25y5esDs3Nx9fAWh4UE0r/y/6gBbjyzGYDDQxKcbgSH+Zv+ql25N6MMHnLy8zywOz9zlleSyggWbRvHGaHfajclJnynl2XjgR6qXbs2Y7qsA2Hsi9vPfmw1Gmn0WLpKnPNVLteLExT2mz/KWtLVUcq4hUdFR7D+9jpL5q5jN/QuYVWyxFjtbe9N3s6ioSB6E3iMwxJ8KxWKPy8fPhwYV3sQxU2Y27J9rWhYTE8PG/T9S2MPLlBALCQvk71NrqFamNfZ2Dmbngke2QuTNXpRD/26KF8trtYcoySUiIhmO7mySJBcnN0Z1W8msP4YS9vABBoOR7s3GUr10KyYs6Uw2Fw8+m/e/mvaT+2wli3P8zgcnBxfeazeH0fPbEhUdSSGPsgzv8FOi+z3vd4xi+XziLbexsWVM99VMWzWQpdvGYzQYaVW9Hy2r9zHrwIjzYaeFidb2Hjn3FS74HQPgnS/LkDdHsUTrtF+5dZLc2RJ+anVEx4VMXzWQd74sg43Rjhpl2tCt6RhmrB5ESHggc9aOYM7aEbH7eWUilUs0jbeNuM6z3Nk8TbX87W0z8d2ghL983rp3KdESfh3qj2DehpH0+6YiNkY7smfNw/ie60wdbuERIezx/Q2AOuXb0bnhyAS388Pa4dwMuIiN0Q4bG1sGtJ1GwVylEmzrH3g90ZJrjX26cDfoBoOn18DGaIuDvTMTe29h74mV7DnxG565y9F3SmyCqEyhmgx6LX6pEUtFRUdx4cYxcmSNX8Yub46ifNB+Hl8sfYuoqEcYjTYMfm0m2bPksehvsNv3V9bs+x4boy1R0ZHUKdeOppV7JNgWYjtV29YaFG+5tc4xR3tnBr82k5FzXwFicHbIysjOyxKN53mcY9HR0Ww6OJ/hHeOXFHrSdf+zOD0xH0Ocvq2nMPP39+j9tRc2RjtK5K/M++1+4KeNn3Hn3hVW7v6WlbtjR0+9WnswzRL4O9gYbfjkrZ/5Yc0woqIjiYx6xGu1hlC6UPUE9/k8junTV/czffUgbIy2OGVy4ZMuP5M9S8JlQ57HMR0eEUqPScV5FPmQkPBAOo3LR6OKXejZYoJZYgOgfJF6T01spObxDtD7q3IEhtwh9GEQncblo3yR+qan3ZNa97J7o+5Qujcba7bM3TUfmyfHWLSdFlV70aJqr6e2ux98hxxZ8yZZKtcaMTnYO7H0k/ilvdIyps4NRyZ6j31SVHQUgcF3qFU24fmOAOpXeNNspEecDRMfJTum6qVbUb10qxcqpic97T2+4Hecd1pMTHS9d9EG9G8bP3n304izCbROWOlC1Zk99Hiy279snByyEPrwQbLb+wVcBKBgAqOW40Yy+929YLY8odFicfeDoND/JU0rl2iGa+acbDm0gFbV+wKxn9HCI0Jo5PO/B2hSEsPzdDPgItmz5DEblRanUK4ynL9xlMBQf7O5dhJ6j1ycspu9PxD7wNq8DSM5+O9GgsPum61L7TLvlu6/WZWeLN46jvX759Lvv+Ty+gNzcc2ck+qPzcN25fYpYmJieHtywg8lAdwLvmX2cz734s/2iwgQO9KoTrl2YDDgYO9MPvfiZmWobwZcxGgwUiCB740FPcqw959V3Ay4iGtmd4vaWio515DA4DuER4QkOEdu/hTMm5scv/85gzX7ZnL51j9Ex5gnrx+E3TP93zFTZup7d2LTwfncD76Da2Z3jp3fgV/ABdMoc4gtOx8dE82G/XPNkmKPS6gfQ+eDiIhkREp0yVOVLliNbwfsjbfc0k6MGmVax5soOiFP61jJn7MEE3vHfyrJkg4MgM97rk1226Q6VXJkzcOobvHLsk3svTmB1gmztPPs2PmddKz/YYLr7Gzt6d1yMr1bTjZbbkmHG8C4t9cku+3xCzvpkEg8AB3rj6Bj/RFmyxpW7Jzi2vhNK3c3m7z7SeeuH6ZG2bbkyJonwfVVS7UwKwERx5K/QduaAxIt5fSkp3WqWuscq1SiCZVKNHlqu+d1jhmNRpZ8cjVZbU9e/tPsS9vjnB2yMLR9/C9u77f7gffb/ZDseCoWb8SM4skrQfI8jukqJZtTpWTy3tPncUw/LVFgrcSGtY73pDqh1UFtXVmd3Zm49C1erT2EFlXfSbKt74XdTFs1ELfMuTAYjLhmdrfofviyxHTD/zxjFrxuKi9rY7Rh+uADVo/JxSkbc9d/xAW/43Rp/Fm6i+nhozAGfVedB2EB2Ns6APBN/z1Wj8nZMSu//zmDK7dPM+T1mRbH9LIp5FEW3wu78Lt7IdnlCy1lNNgkui4m5n/3NhsbWxpUeJPfdn/Ddf9z5M1RlM2HFuDi6GaWGLGGx+d7e1xUVKRV95NcSb1HccIeBvP+93UIjwjhtdpDKOzhhWMmF4wGI0u3T+DofyPdU4ul+8/pmp/KJZqx9fAier0yiVv3LuN7YRft6n5gXqUgJgaDwcDnPddjk8j7UNDDPKmZyS4N53nMQPLmKJYuRsYl9xryPK3Y+TWz1gzFp3gT2tYaRPYsebCzscc/6DqTl3cn5onEV4uqvVn39w9sPrSAdnWHsmH/XOxsM9HIp4upTQyxv0vDim/RxCfhChf2CTwgq/NBREQyIiW6JFW8aB0rz9qBYe1OFUf7zGw5tBC/gAuM7fH7U9tPWNKZ01f+pv5/9fatMerpcbY29jwIvUufr735ovcms6dFEzJ7zTD2nfyd0gVjSxS1rzfMqvEYjTZksneiz9feDOswn6J5vZNsv+PochZvHWea06dE/sqUyF/ZqjG9aJ2q6fkcA/hgZn1uBVwylQmJK3diLZnsHDl/4yj9vq3EjMEHn9pex3TSx3RSXrTjPSlPngsvG0tHbcWx5Hrh5VmbWe8fTXb7lzWmPDmKWBTToo8vWR4QMLrbb8lu+yLGlMnO0aKYEhuZ/zT923wLT5lXMaUxZUS1vV7H98Iu1u2fYzY/UmLiRhNcvvUPFYuZl96+fDu2VPazJMwa+3Tjt93fsPnQAlpU7cXx8ztoUbU39raZrBqDi1M2HvxXbvdxfgHxR4JZOlIqdzZPDp7ZQHDY/Xilhi/fPomTQxayOuWwaJsAR85u5W7QDYa2/zHeiPd5G59eyvxZpWT/Lar25u9Ta/nzn1Wcu34EiB3p9bi8OYpx4MwGcroWSLTihKQNj2yeRMdEc+XWKTzzmM8BGVca3yNbYYvbpoasmd1xsHfm2p0z8dZdTWDZs9pyeCEeboUY33M9RuP/ZhE5cHpDgu1L5K9E0bwV2LB/Ls2r9GS376/ULNPWbARd3uxFMRgMREZFpIsEpIiISGpSoktSRWp2rKTEi9aB0a7eB7Sr90Gy2z85Ubu1lSlUI9kjb4AER4xZU07X/Cz/9Eay29fz7kA97w6pFg+kbqdqSqTncwzgy77bUzEay48JHdMp96Id70l5HueCiEhG17zKO/zx5wxW7PySUvmrUqNsm3ht/r12iNNX/qZ1jX74FG+Mg70zq/Z+R9NKPXByiJ3fKzT8Aav2fodjpsz4FHv6fLaJKZrXG8/c5dh6eBH2tg5Ex0TT+Im5O60RQ1734uzx/RX/wOvkyJoXgIjIh/z+Z/wH0BztMwOY5qF8mppl27L/9DqWbf+Cd1p8YVq+//R6zl0/QsOKb5l1jCeX0fjfqJYnRrAcPLPpuczPlZL9Vy31Ctmz5GHNX7O4cvsUZQrVpEBO8xKFjXy6sGrvd8xb/zGfdl2BjdF89M69B7dMDwvJ81WzbFv+2DeDpdsn8PGbS0xJ34s3T7Dv5O+ULVzLVIrQkrapwcZoQ+WSzdl9fAUnLu41m6fr8Tm4rcVotAGDwTQKC2JHhC7b/kWir2lRpRdTV/Zj2qqBRESG07yK+cNpWZyzU6VkC/b4/sbJy39RumA1s/UxMTEEhvin6vsoIiLyolCiS0RERERERJLFwd6JsW+v4ZMfX2HUT23xKd4En2KNcXHOTmDwHY6d387BfzfSvt5wADI7utLrlUl8t7I/A7+rSpNK3QHYdHA+N/zPMeT1WTg7Zn2mmBr7dGPWmqEs3zGRfO7F43X2WiOGNjUGsOPoMobPbkTLan2JjIpgy6GFZLKPXwKsRP7KseX5tn5OcNg9HOyd8chWmFIFqia47SaVurPp4E8s3z6RWwGX8PKsww3/c/y+bwZumXPxdjJGziWkbOFaZHPxYNaaody8dwn3rPk4f+MoWw4vpLCHFxdv+qZou3Gioh6xeMu4BNfV8notRfu3MdrQrPLbLN4au923m8X/3Uvkr0zXxqNZsHk0fad4U6dcO7JnyUNAkB9nrx9i/+l1rP8i4pl+N0kZn+KNqVu+PTuOLiM49B5VS7fk3oOb/P7ndOxtHejfZmqK2qaWHk3HcejMRj6e24w2NQaQI2s+/j69lsDgO4BlozOPnNtKRGR4vOVZnHPQqnpf6ni9wdz1H/HxnObU8nqN0PAgth1ZkmSVgQYVOzN77TC2Hl6ER7bCVHhiRCrAoNe+573ptRj6fR0a+XSlaJ4KxMRE4xdwgT//WU1jn650bTI62b+HiIhIeqVEl4iIiIiIiCRb3hxF+X7IEdb+NYvdvr+yZNvnhD0MxsUpG8XzVWJYh59o8F/JbYDWNfqRzSU3v+yczKLNYwDwzFOe0d1WUrNs22eOp2HFzsxZN4LQ8CBTgu1JzxpD2cI1GdZhPku3jeeHtcPIkSUvLau/S/H8lRg+y7zzOadbAYa2/5Hl2ycy9bd3iYx6RGOfbokmumxt7JjQayNLtoxjx7Hl7DnxG5kdXKlTrh09mo0jp2t+y96Q/2R2dGXCOxv5Ye1wVu/9jqjoSIrl9eHzt9exfv/cZ050PYqKYP7GTxNclydHUQrmKp2i/Tev+g5Lt43Hwd6ZOuXbJdimS5NRFM9fiZV7prJy9zeER4TgmjknhTzK0u85JEgkcR91WkzRvBXZdHA+s/8YioO9M+U869K96VgK5/ZKcdvUkD9nCb56dxez13zAyj3fYm/rQNVSLRn46nS6TvAkUwLzWyXmwJkNHDgTvwxhfvcStKrel3b1hhFDDBv2z+X71YNxc/GgXvkONKncg3e+LJ3gNp0dslCvfAc2HPiRppV6JJh4y+manxlDDrF8+0T+/Ge1aXSru2t+qpVuRd3y7ZP/hoiIiKRjhpi0monzJRASEkLmzLFlK4KDg3F2drZ4G1ERsF2f00VERF5I9QeBjf2zb0f3e5GMKaXXCF0T5GV2N8iPNz/PT/PKPRnyxqy0DidFrPX5ICV0/Xh2/147RP9vK9Gz+QQ6NvgwTWOZ+ls/1v49m0UfXcLdNd9z3XdaHsciIiKWsrzQt4iIiIiIiIhIKvhj3/dER0fRolrvtA5FXgIPH4WZ/RwTE8PPOyYBULF4yucPtIaQsEC2Hl5ElRLNn3uSS0REJL1R6UIRERERERERSVPbjy7j9r0r/LJjMpWKN6V4Pp+0DkleAn2neONdpAGFc3sRHhHCXyf/wPfibuqV75Bmx+DFmyc4d/0Imw/+RFhEMJ0afJwmcYiIiKQnSnSJiIiIiIiISJoav7gT9rYOlC1cm6Ht56Z1OPKSqFG6DftO/cGWwwuJio7EI1thujcdS4f6I9Ispt3HV7Bw8xhyZM3LwFdnULpQ9TSLRUREJL1QoktERERERERE0tTmyZo+XJ6/Xi0n0avlpLQOw0zXJqPp2mR0WochIiKSrmiOLhEREREREREREREREUmXlOgSERERERERERERERGRdEmJLhEREREREREREREREUmXlOgSERERERERERERERGRdEmJLhEREREREREREREREUmXlOgSERERERERERERERGRdMk2rQMQEREREREREZGMacTsJtx7cBODwYiTgwv920ylaN4KADQeZqCQR1neaTGRqqVaALB4yzg2HpgHQD3vjrzd/HMAdhxdzsLNY7gbdINVY++nOJ6wiBCGz2xARGQ4ANlccjP49Zl4ZCvEzYBLdPuiCIU8vBjWYT5F83rz96m1/LTxMy7dPEHL6u/Sr803pm39umsKv/85HQf7zMx6/2iKY/ILuMjYBW8QFR1FdHQk+XOV4r3XZ+Pi5Max8zv4eE5z8rmX4Ivem3DLnJO56z9mr+9v2NlmwsbGjh7NPqdyiaZWjUlERCQ9UaJLREREREREmLy8B2evHcJgMGJrY0fPFl9QsVhDAN4aXwg720y0qzuMFlXfAWD9/rks2/4FMdHReBdtwKDXZmBrY4fvhd1MWzWQC37HWPl/98js6Jrq8dwMuMTk5d05d+MIHm6FzTp30yKeI+e2MXfdh4Q9DMZgMFC15Cv0bPEFRqORG/7nGbPgda7cPsl3A/dTNK93iuL5cf1I9p38HaPBBoCODT6kvndHAIZ+X4/b9y7TpHIPujT+LMlO9LSI53GTlnVn86GfTH+bh4/CGPRddW7cPceHnRZRs2zbFMWzeu901vw1E6PBhujoSFpU682rtQaZ9nn47GaqlW7FkNdnAv9LuMTFP6Dtd3h51rZaPC+zT7v8bDrv9viuZPLy7sx6/5hp/ZR+u03rj1/YxfajS5k19Dg2RluGTK9JmUI1qFrqFep5d6Bkgar0neL9TPFksnVkYu8tODm4ALGJoRmrB/N/PVYD4JjJxewakjdHMYa2/5Fdx38h7GGw2bZer/MeRfNWYMbqIc8UU/YseZjSfw+Z7BwBmL56MAs2j6Z/m28ByOdewiwmr8K1eavRp2Syc+T8jWO8/30dln16A0d7Z6vFJCIikp4o0SUiIiIiIiK823qKqbP53PUjDJ/VkBWj/TEaYyvej+y83JQE8Qu4yPyNn/L94MO4ueTis/ltWPvXbNrU7I+XZ21mvX+UxsMMzy0eJ4cs9Gg2jpDwQH5cP9JsO2kRj4ujGyM7LyN3dk8iHoUzfHYjNh9aQNPK3cmTowiz3j/KW+MLPVM87esNM4108Q+8Ts/JpahYrBFZnXMA0Lf1FFNSJqlO9LSIJ85u39+wtbEzW5bJzpFZ7x9l6Pf1nimeRhXfok3N/gCEhAfR66uyeBWubRpJ1L7eMF6rPcTsNY8nXKwdT0bXeJiBNxuO5O9TawmPCKFL41E0rNgZwOw9DQkPBBI/F3ccXU6jil1wtHcGoFnlt9l+ZClVS71iUTw3Ay7Rd4o3zau8w6F/NxEdE0W/1t9SsXgjjEajKckVExNDaHgQBkPiMeVzLw7A3hMrLYrhScfO72DaygEUzVuRc9cPY2ebiffbzaVoXm/sbTOZ2kVFRxEeEYKjfeZEt1WlZHPT/wt7eEFMDIHBd3DM5vxMMYqIiKRXSnSJiIiIiIi8RE5e2sfstcMIe/iAmJgYujcdS42ybRLojE7c7uMrqF66NdmyeADQslpflm4bb0osPO94sjhlo2zhWhw7v8Pi/adGPHHJFAB7OweK5PHm1r1LKYrn8q1TfP/7EAKC/ABoVaMfrar3NYsn7GEwMcQQHROd4DYs7URP7XgA7j24xdJt4/myz3bW75+TolggNqk2Y/Vgrt45gwEDNcq0oXuzsTg7ZjW1CY8IISrqUYr3IcljwMDM947gd/cC/b+tRJlCNfHIVgiAiUu7cuz8dgA+77ku0W3cuX+FsoVrmX7O5VaIHUeXpSiekPBACuQqRZ9WX3Ly8l+Mmteanz48b0pyDZ/ViIs3fXF1dmdCr40p2oelLt36h3fbfMuITgvYeexnxi/uyNxhpzAYDDyKjGDA1Crcvn+ZwrnLMbb778na5saD8/DI5kkut4KpHL2IiMiLS4kuERERERGRl0RQaACjfmrLZ11W4OVZm+joaILD75vWz1n3IbuO/UJw2D0+6/qrabTSk27fv2LWqeqRrRC3719Js3isJTXiCQi6ye7jKxj79hqL44mKimTU/DZ0bTKGBhU6ARAY4m9av3LPVH7/czr+96/xXrs5uGXOmei2UtqJnlrxfL2iF71emWRKOqTUF0vfwqd4Ez7rugKA+8F3TOt2HV/Bgk2juOF/jh7Nx5slIBMyfFZDoqIjqVC0Id2ajTWNKpLkaf5fWdPc2T3x8qyD74VdpkTXiE4LANh08Cd+WDeC8Ukku6zFxmhLk0rdAShdsBrZsuTh3I0jlPOsA8CkPluIjo5mydbPWbL1cwa9NiPVY/JwK2QqeVq3fHumrOjNnftXyelWADtbe2a9f5RHkRFMXzWQNX/NokP94Ulu7/DZrSzcPIaJvTYnOSpNREQko0vdbwkiIiIiIiLywjh1eR/53Uvg5VkbAKPRSBanbKb177T4ggUfneeTt37mh7XDeRQZoXieIZ6Q8CA+ndeK9vWGUyJ/JYvjuXrnDBGR4aakEmAqBQjwaq1BzBt+hm8G/MnSbeMJCrmb6LbiOtF//uwWBdxLsuavWWkWz7q/55DTtQAVijawOIbHhT0M5sTFPbxRZ6hpmWtmd9P/65R7gzkf/MOPw8+w9fAirt4+k+i2Fn98mRlDDvHNgD+5H3KHH9YMe6bYBEgg8dKkUjeOndue6LHh7lqA2/cum36+de8SOV0LWC+kJ8omGo1GWlTtxZbDC622D4viMRjivU92tvY0qdzjqTEdO7+TL3/uwdgef5A/Z4nUDFNEROSFp0SXiIiIiIiImKlYvBFhDx9w8aZvgutzuhbg1mOd0DGhZQAAEBlJREFU0TcDrNsZbWk8z1ty4gkNf8DHc5pRo0wb3qj7fqrGUyRPeXJkyZus0o3J7URPzXiOnd/Ovn9W89b4Qqa5wXp/XY5z14+kSjwe2QpRskBV/jqV+Ki6nG6xx6+jvTOtq/fD9+LuVIklI9t4YB4Qez3wvbgbr8K1CQ67j3/gDVObvSdWkcU5Oy6PJZAfV7d8O7YcXkhYRAgRkQ/ZcOBH6nl3THSfw2Y15PSV/Qmui4qOZMuh2OP89JX9BATdoEgebwKCbvIg9J6p3Y5jyynsUc7i3zcxb08qiX/g9QTX3bx3iaPnYks47jq+ArfMuXDPmo9b9y4THhEKQHR0NLuO/4Jn7sRjOn5hFxOXdeH/uq+mSJ7yVotdREQkvVLpQhERERERkZdE6YI1uO5/Ft8Lu81K8zllcuHWvcvkzVEUiO0Uvh98m9zZPBPcTm2v1xkyoxZdG4/GzSUXa/6amWRn9MSlXalZ9lVqeb2aKvFYKrXjCXsYzEdzmlGpRDM6N/rkqfHMXfcR2bPmpW3NAWbL87uXwMHOiW1HlpqVCszqnIPLt05SMFdpAG74n+fcjSMU+O/nJ926d5mszu442DslqxM9teP56M3FZj83HmZg9vvHzeb5etyqvdO4G3idni0mmC13zJQZL886rNj1FZ0afATEli50zexuFs/94DscPbeN2l6vJ7j9B6H3sLPNZHp/dhxbTtE8SZc5lPiio6PoO6UC4REh9G8zFY9shbh17zJjF7bj4aMwjAYjWZ3dGdtjTaJl9soXqUfd8h3o/ZUXAPXKd6Ba6ZYJto2KjuLCjWPkyJovwfXODlm5dPMEfb4uT1R0JB+9uQQnBxeu3D7FN7/2ITo6ihhiyJO9CB++uSjR3+vw2a1MXt6N0PAgYohht+8KBr46gxplWsdrey/4NkGhdxNN5BXKVYZNB+czffUg7Gzs+bjzUgwGAxf8jjNv/UgAYmKiKZq3Iv3bTE00pq9+6cmjyIdMXt7DtOzDTgspnNsr0deIiIhkZEp0iYiIiIiIvCRcnNwY1W0ls/4YStjDBxgMRro3G0uFog2ZtKwboeGBGI22ONg782nXFbg4uSW4ndzZPenWZAxDptcEYjunW1brk+h+/712kLa1BqVaPOERofSYVJxHkQ8JCQ+k07h8NKrYJV5i5HnF89uebzlzdT/hESHs8f0NgDrl29G54cgE25/3O0axfD7xltvY2DKm+2qmrRrI0m3jMRqMtKrej5bV+/DD2uHcDLiIjdEOGxtbBrSdRsFcpRLcvqWd6Kkdj6Wu3DqZaFJxRMeFTF81kHe+LION0Y4aZdrQrekYVu7+Ft+Lu7G1sQdieK32EHyKN05wG1dvn+abX/tgMBiIio6kaN6K9GvzrVVif5m8UXco3ZuNNVuWy60g0wYlPOIqMV0af0aXxp89td2564epUbYtObLmSbRNn1ZfxltWskAVZr6X/NGDFYs1ZOkn15LV9vj5nbxaazCZ7BwTXG802jK840/xllcv3YrqpVslO6afRpxNdlsREZGXgRJdIiIiIiIiL5HSBavx7YC98ZYntCwpLar2okXVXk9tdz/4Djmy5k10jiprxONg75TsjujnEU/nhiMTTWo9KSo6isDgO9Qq+1qC6/PnLMHE3pviLR/3duJl+J5kSSf684jnSZsnxyS5/oLfcd5pMTHBdTmy5mFUt1/jLR/yRvLnICtdqDqzhx5PdnuxHrfMuRj6fV3ebj6BqqVaJNl2x9HlLN46DjeXXACUyF+ZEvkrWzUeo9GGTPZO9Pnam2Ed5lM0r3eS7X/dNYV1f/9A9iyxyba65dtZNR4AWxt7HoTepc/X3nzRexNumXNaFJOIiMjLwBATE5P0J0pJsZCQEDJnzgxAcHAwzs7OFm8jKgK2J/6gnYiIiKSh+oPAxv7Zt6P7vUjGlNJrxIt4Tej/bWUiHoXxau0htKj6TpJtfS/sZtqqgdx7cJN5I/7F2SGL4nnMDf/zjFnwOoEhd/ii1yYKeZSxejyjf3qNK7dPUd+701NHxrxo8Tx8FMag76rzICyA916fTeWSzawez/TVgzlwej3eRRsw5PWZVo/HWp8PUuJFvH5I+pSWx7GIiIillOhKRUp0iYiIZGxKdIlIUjJSoktEkk+JLskIlOgSEZH0xJjWAYiIiIiIiIiIiIiIiIikhBJdIiIiIiIiIiIiIiIiki4p0SUiIiIiIiIiIiIiIiLpkhJdIiIiIiIiIiIiIiIiki4p0SUiIiIiIiIiIiIiIiLpkhJdIiIiIiIiIiIiIiIiki69FIkuf39/hg8fTtGiRXFwcCB//vwMHjyYkJAQevbsicFgYNq0aWkdpoiIiIiIiIiIiIiIiFjANq0DSG1Hjx6lefPm3Lx5E2dnZ0qXLs2NGzeYOnUq58+fJyAgAABvb++0DTSFrt4+w6It/8fZ64e5G3SDqKhH5HQtQJWSLWhXbxjZs+RO6xBFRETkGel+LyKPW7ptAmevH+bstUPcDLhILreCLPr4UlqHJSLpgK4fIiIikhFl6ESXv78/rVq14ubNmwwdOpRRo0bh4uICwKRJkxgxYgS2trYYDAbKlSuXxtGmzJ3AawQE+VGz7Ku4Z82HjdGWizd9Wfv3bLYfW8bM947iljlnWocpIiIiz0D3exF53I/rP8bFKRvF8lYkJOx+WocjIumIrh8iIiKSEWXoRNegQYO4du0aAwYM4MsvvzRbN3z4cJYsWcKxY8coXLgwWbJkSaMon03FYg2pWKxhvOVeheswblF7Nh2YT4f6w9MgMhEREbEW3e9F5HELPjxP7uyeAPT6sixhEcFpHJGIpBe6foiIiEhGlGHn6Dp16hTLly8nR44cTJgwIcE2Pj4+AJQvX960rF69ehgMhgT/9e3b97nEbg253AoCEBx2L40jERERkdSi+73Iyymuk1pExFK6foiIiEhGlGFHdC1dupTo6Gg6d+5M5syZE2zj6OgImCe6ZsyYQVBQkFm7tWvXMm7cOFq2bJl6AT+jiEfhhEUEE/EonMu3TjJn3QgAqpRskcaRiYiIiLXofi8iIiIiIiIiYi7DJrq2bdsGQP369RNtc+3aNcA80VW6dOl47T7//HPc3d1p1qyZlaO0nnX75zB91UDTzx5uhfiw0yK8PGunYVQiIiJiTbrfi4iIiIiIiIiYy7CJrsuXLwNQsGDBBNdHRkayd+9ewDzR9aQ7d+6wYcMG+vXrh61tyt+uYsWKYTRaXinS3taR2QPOPrVdzTJtKeBekrCIYM5dP8K+k78TGOKfklBFREQkmYoVL0ZEZNgzb0f3e5GMKaXXiOReE0TkxWStzwcpoeuHWEtaHsciIvJy8vDw4ODBgyl6bYZNdIWEhAAQFpbwTXn58uX4+/vj4uJC4cKFE93O0qVLiYyMpEuXLs8Uj5+fX4pe52DnlKx27q75cHfNB0DNsm2p7fU6A6ZW5uGjUDo1+ChF+xYREZGk+d24Qfij0Gfeju73IhlTSq8Ryb0miMiLyVqfD1JC1w+xlrQ8jkVERCyVYRNdHh4e3Lt3j8OHD1O9enWzdX5+fgwbNgyAcuXKYTAYEt3OwoULKVWqFJUqVbI4BicnJ4KDg6lVqxa3b99Ocj+Jsbd1tPg1AJ55ylEkbwX++HOGOr5ERERSSe48eaw2oisldL8XebGl9BqR0muCiLwYrPX5ICV0/RBrScvjWEREXk4eHh4pfm2GTXQ1atSIU6dOMXHiRBo3bkzx4sUBOHDgAF26dMHfP7bMj7e3d6LbOH36NAcPHmT8+PEpisFgMODs7MyRI0dS9HqAqAjYPjVlr414FMaD0IAU71tERESSdvbfs9jYP/t2dL8XyZhSeo14lmuCiKQ9a30+SAldP8Ra0vI4FhERsZTlk0alE8OHDyd79uxcvXqVMmXK4OXlRbFixahSpQqenp40aNAASHp+roULF2IwGOjcufPzCttiAUE3E1x+9Nx2Lt08QcmC1Z5zRCIiImJtut+LiIiIiIiIiCQsw47oypcvH7t372bYsGHs3LmTS5cuUbp0aWbNmkWvXr0oUqQIkHiiKyYmhsWLF1OvXj0KFCjwPEO3yNTf3uXuAz+8izYgl2tBIiLDOXvtEDuOLcMxkwt9Wn6V1iGKiIjIM9L9XkQet/nQQm7fuwzA/ZA7REZFsHjLOAByuhWksc+zzS8sIhmXrh8iIiKSEWXYRBdAqVKlWLNmTbzlwcHBXLp0CaPRSNmyZRN87a5du7h8+TKjRo1K7TCfSf0Kndh8aAFbDy3kfsgdDBjI5VaQV6r1oX3dYeR0e3GTdCIiIpI8ut+LyOM27J/L8Qs7zZbN3/gpAOU866qjWkQSpeuHiIiIZEQZOtGVmH/++YeYmBiKFy+Ok5NTgm0WLlyIo6Mjb7zxxnOOzjJ1y7enbvn2aR2GiIiIpCLd70XkcV+9uyOtQxCRdErXDxEREcmIMuwcXUnx9fUFEi9bGB4ezooVK2jbti0uLi7PMzQRERERERERERERERFJppdyRNfTEl0ODg7cv3//OUYkIiIiIiIiIiIiIiIiltKILhEREREREREREREREUmXXsoRXdu2bUvrEEREREREREREREREROQZvZQjukRERERERERERERERCT9U6JLRERERERERERERERE0iUlukRERERERERERERERCRdUqJLRERERERERERERERE0iUlukRERERERERERERERCRdUqJLRERERERERERERERE0iUlukRERERERERERERERCRdUqJLRERERERERERERERE0iUlukRERERERERERERERCRdUqJLRERERERERERERERE0iUlukRERERERERERERERCRdMsTExMSkdRCSuJgYiH6U1lGIiIhIQox2YDA8+3Z0vxfJmFJ6jdA1QSR9s9bng5TQ9UOsJS2PYxEREUsp0SUiIiIiIiIiIiIiIiLpkkoXioiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLqkRJeIiIiIiIiIiIiIiIikS0p0iYiIiIiIiIiIiIiISLr0/w+bhretsEtuAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 2210.55x1454.83 with 1 Axes>"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circuit.draw(\"mpl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "309dfb0a-6292-4a97-b5f7-39548e3bf4f7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def callback_graph(weights, obj_func_eval):\n",
+    "    clear_output(wait=True)\n",
+    "    objective_func_vals.append(obj_func_eval)\n",
+    "    plt.title(\"Objective function value against iteration\")\n",
+    "    plt.xlabel(\"Iteration\")\n",
+    "    plt.ylabel(\"Objective function value\")\n",
+    "    plt.plot(range(len(objective_func_vals)), objective_func_vals)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "48186b5e-a384-4700-9684-388d5bdd68c5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open(\"11_qcnn_initial_point.json\", \"r\") as f:\n",
+    "    initial_point = json.load(f)\n",
+    "\n",
+    "classifier = NeuralNetworkClassifier(\n",
+    "    qnn,\n",
+    "    optimizer=COBYLA(maxiter=550),  # Set max iterations here\n",
+    "    callback=callback_graph,\n",
+    "    initial_point=initial_point,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "6709a12f-5d94-4e3b-8706-390f384c4cf9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy from the train data : 100.0%\n"
+     ]
+    }
+   ],
+   "source": [
+    "x = np.asarray(train_images)\n",
+    "y = np.asarray(train_labels)\n",
+    "\n",
+    "objective_func_vals = []\n",
+    "plt.rcParams[\"figure.figsize\"] = (12, 6)\n",
+    "classifier.fit(x, y)\n",
+    "\n",
+    "# score classifier\n",
+    "print(f\"Accuracy from the train data : {np.round(100 * classifier.score(x, y), 2)}%\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "62c98602-61e9-4b66-800c-c2631a31e530",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy from the test data : 100.0%\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "y_predict = classifier.predict(test_images)\n",
+    "x = np.asarray(test_images)\n",
+    "y = np.asarray(test_labels)\n",
+    "print(f\"Accuracy from the test data : {np.round(100 * classifier.score(x, y), 2)}%\")\n",
+    "\n",
+    "# Let's see some examples in our dataset\n",
+    "fig, ax = plt.subplots(2, 2, figsize=(10, 6), subplot_kw={\"xticks\": [], \"yticks\": []})\n",
+    "for i in range(0, 4):\n",
+    "    ax[i // 2, i % 2].imshow(test_images[i].reshape(2, 4), aspect=\"equal\")\n",
+    "    if y_predict[i] == -1:\n",
+    "        ax[i // 2, i % 2].set_title(\"The QCNN predicts this is a Horizontal Line\")\n",
+    "    if y_predict[i] == +1:\n",
+    "        ax[i // 2, i % 2].set_title(\"The QCNN predicts this is a Vertical Line\")\n",
+    "plt.subplots_adjust(wspace=0.1, hspace=0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "c84e02df-35b5-445f-a720-f0730bbd60c8",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<h3>Version Information</h3><table><tr><th>Software</th><th>Version</th></tr><tr><td><code>qiskit</code></td><td>0.44.1</td></tr><tr><td><code>qiskit-terra</code></td><td>0.25.1</td></tr><tr><td><code>qiskit_machine_learning</code></td><td>0.6.1</td></tr><tr><th colspan='2'>System information</th></tr><tr><td>Python version</td><td>3.10.8</td></tr><tr><td>Python compiler</td><td>GCC 10.4.0</td></tr><tr><td>Python build</td><td>main, Nov 22 2022 08:26:04</td></tr><tr><td>OS</td><td>Linux</td></tr><tr><td>CPUs</td><td>8</td></tr><tr><td>Memory (Gb)</td><td>31.142810821533203</td></tr><tr><td colspan='2'>Wed Nov 22 17:40:01 2023 UTC</td></tr></table>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div style='width: 100%; background-color:#d5d9e0;padding-left: 10px; padding-bottom: 10px; padding-right: 10px; padding-top: 5px'><h3>This code is a part of Qiskit</h3><p>&copy; Copyright IBM 2017, 2023.</p><p>This code is licensed under the Apache License, Version 2.0. You may<br>obtain a copy of this license in the LICENSE.txt file in the root directory<br> of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.<p>Any modifications or derivative works of this code must retain this<br>copyright notice, and modified files need to carry a notice indicating<br>that they have been altered from the originals.</p></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Time in seconds since end of run: 1700674802.0392525\n",
+      "Wed Nov 22 17:40:02 2023\n"
+     ]
+    }
+   ],
+   "source": [
+    "import qiskit.tools.jupyter\n",
+    "\n",
+    "%qiskit_version_table\n",
+    "%qiskit_copyright\n",
+    "seconds = time.time()\n",
+    "print(\"Time in seconds since end of run:\", seconds)\n",
+    "local_time = time.ctime(seconds)\n",
+    "print(local_time)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.8"
+  },
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+       "font_style": null,
+       "font_variant": null,
+       "font_weight": null,
+       "text_color": null,
+       "text_decoration": null
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+     "12ea42aa3019407fa4562bffb468ea39": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
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+       "font_size": null,
+       "text_color": null
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+       "grid_template_areas": "\n                                       \". . . . right \"\n                                        ",
+       "grid_template_columns": "20% 20% 20% 20% 20%",
+       "width": "100%"
+      }
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+     "37c206873f6c4d4e9671419c063faac7": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {
+       "grid_area": "right",
+       "padding": "0px 0px 0px 0px",
+       "width": "70px"
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+     "557c91142aa44753b390f4e3b041776b": {
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+      "model_module_version": "2.0.0",
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+       "style": "IPY_MODEL_f8c95d44beeb4a6ea8a47e2ceba2ce74",
+       "value": "<h5>Status</h5>"
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