843 lines (842 with data), 422.2 kB

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "58d4191c-2fbe-4ca8-98af-84bfc72bccc7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time in seconds since beginning of run: 1680474241.5968611\n",
      "Sun Apr  2 22:24:01 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": 2,
   "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": 3,
   "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": 3,
     "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": 4,
   "id": "cc82adbd-cd38-4873-96a9-627c63737559",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2210.55x1204 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "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": 5,
   "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": 5,
     "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": 6,
   "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": 6,
     "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": 7,
   "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": 8,
   "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": 9,
   "id": "24666f27-d9d7-473a-b905-664797788e1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAx8AAAG7CAYAAACitih0AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAM10lEQVR4nO3av4vkdx3H8c9s5nJXZA4FG5ddoilSKaJiEQttUqUQBNNoIWrlXyD5G/wb0sXOxhQpBfEHCBKwEzEY2cuANsJtivsxO2NxbAoR925y9/zO7ffxaK65GV7c7c57nzuz2O12uwEAAPCMHU09AAAAmAfxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBiue8Dt9vtWK/XY7VajcVi8TQ3AfCM7Xa7cX5+Po6Pj8fR0WH8HspdAXh+Pe5d2Ts+1uv1OD093ffhAByAs7OzcXJyMvWMMYa7AnAdXHVX9o6P1Wo1xhjjtdd+NpbLm/s+DU/g3bffmXoCPFPfffXLU0+Yjc14OH433vvktfwQfHJXvumuVJZ//MvUE2bnw7e+MvWEWXn/+29PPWE27n68HS9/7cMr78re8XH5lvhyeXMsl7f2fRqewO3VYXw0Ap6V5eLG1BPmY/foj0P6eJO70vM91zu65Wu75Gen3lV3xf8IAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJMQHAACQEB8AAEBCfAAAAAnxAQAAJJaf9gnuf/bGuLhx42ls4Qqv/+DHU0+YnX999dbUE2bl5o92U0+YjYsH98Z451dTz2Bi//zJ16eeMDtffOsPU0+Ylx9OPYD/5p0PAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLiAwAASIgPAAAgIT4AAICE+AAAABLLfR+42+3GGGNcPLz31Mbw/72weTj1hNm5uD/1gnm5eLCbesJsXDx49Np9+Vp+CC63bDa+8SoXD6ZeMD+bnVteunu+nXrCbNz9+NG/9VV3ZbHb8/LcuXNnnJ6e7vNQAA7E2dnZODk5mXrGGMNdAbgOrrore8fHdrsd6/V6rFarsVgs9h4IQG+3243z8/NxfHw8jo4O4xO47grA8+tx78re8QEAAPAkDuPXXQAAwLUnPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgIT4AAAAEuIDAABIiA8AACAhPgAAgMRy3wdut9uxXq/HarUai8XiaW4C4Bnb7Xbj/Px8HB8fj6Ojw/g9lLsC8Px63Luyd3ys1+txenq678MBOABnZ2fj5ORk6hljDHcF4Dq46q7sHR+r1WqMMca3X/npWB7d3PdpeAIXf/v71BNm5/zNb0w9YVY+8+sPpp4wG5vtg/Gbf//ik9fyQ3C55R/vf2Hcfukw3o2Bp+17b3xn6gmzsvncS1NPmI3N5v74/Z9+fuVd2Ts+Lt8SXx7dHMsXxEdhsbgx9YTZeeHGraknzMry6MWpJ8zOIX286XLL7ZeOxu2V+OB68jNTbOmO1666K17dAQCAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAICE+AACAhPgAAAAS4gMAAEiIDwAAILH8tE/wy/feHbdXGobr6Y3XX516wqw8+NLLU0+Yjc3m3hi/nXrF//bmt14fy6MXp54xCx+9+crUE2bn8x/9eeoJs7L46wdTT5iNxe7hY/091QAAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAQnwAAAAJ8QEAACTEBwAAkBAfAABAYrnvA3e73RhjjLsfb5/aGDg0m4v7U0+Ylc1m75ckntBm8+hr+/K1/BBcbtlsH0y8ZD4u7t+besLsbHa+vkvb3cOpJ8zGZjz6t77qrix2e16eO3fujNPT030eCsCBODs7GycnJ1PPGGO4KwDXwVV3Ze/42G63Y71ej9VqNRaLxd4DAejtdrtxfn4+jo+Px9HRYXwC110BeH497l3ZOz4AAACexGH8ugsAALj2xAcAAJAQHwAAQEJ8AAAACfEBAAAkxAcAAJAQHwAAQEJ8AAAACfEBAAAkxAcAAJAQHwAAQEJ8AAAAif8AmQlAreXNnIEAAAAASUVORK5CYII=\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": 10,
   "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": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_map = ZFeatureMap(8)\n",
    "feature_map.decompose().draw(\"mpl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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": 12,
   "id": "ef995a89-bb0c-4957-b266-82ce20a50c4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2210.55x1454.83 with 1 Axes>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw(\"mpl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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": 14,
   "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=275),  # Set max iterations here\n",
    "    callback=callback_graph,\n",
    "    initial_point=initial_point,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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": 16,
   "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": 17,
   "id": "c84e02df-35b5-445f-a720-f0730bbd60c8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h3>Version Information</h3><table><tr><th>Qiskit Software</th><th>Version</th></tr><tr><td><code>qiskit-terra</code></td><td>0.23.2</td></tr><tr><td><code>qiskit-aer</code></td><td>0.12.0</td></tr><tr><td><code>qiskit-ibmq-provider</code></td><td>0.20.2</td></tr><tr><td><code>qiskit</code></td><td>0.42.0</td></tr><tr><td><code>qiskit-nature</code></td><td>0.5.2</td></tr><tr><td><code>qiskit-finance</code></td><td>0.3.4</td></tr><tr><td><code>qiskit-optimization</code></td><td>0.5.0</td></tr><tr><td><code>qiskit-machine-learning</code></td><td>0.5.0</td></tr><tr><th>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>31.211322784423828</td></tr><tr><td colspan='2'>Sun Apr 02 22:36:18 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: 1680474978.692769\n",
      "Sun Apr  2 22:36:18 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)"
   ]
  }
 ],
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    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "pygments_lexer": "ipython3",
   "version": "3.10.8"
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