optical_accelerator/Propagator_QuickDraw.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f0d9d491-74b8-4567-b2ba-79e99ab499ee",
   "metadata": {},
   "source": [
    "# Пример на данных QuickDraw \n",
    "https://github.com/googlecreativelab/quickdraw-dataset  \n",
    "Используется урезанная версия с 16 классами "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c4455b6a-5ed9-4499-98b4-42e18fa1f6d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from torch import flip\n",
    "from torch.nn import Module\n",
    "from torch import nn\n",
    "from torch.nn.functional import conv2d\n",
    "import torch.nn.functional as F\n",
    "from torchvision.transforms.functional import resize, InterpolationMode\n",
    "from einops import rearrange\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import confusion_matrix, accuracy_score\n",
    "\n",
    "import numpy as np\n",
    "import math\n",
    "\n",
    "import tqdm\n",
    "from pprint import pprint, pformat\n",
    "from IPython.display import display, clear_output\n",
    "from pathlib import Path\n",
    "import models\n",
    "import inspect\n",
    "import yaml\n",
    "from PIL import Image\n",
    "\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb1d1521-bade-47f6-a2e8-1d12c857e2f8",
   "metadata": {},
   "source": [
    "### Параметры данных и модели"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b9ce4212-977c-4621-850b-db595cd00ab2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'batch_size': 152,\n",
      " 'class_slots': 16,\n",
      " 'classes': 16,\n",
      " 'dataset_name': 'quickdraw',\n",
      " 'experiment_dir': PosixPath('experiments/OpticalSystemMLP_quickdraw_4_2_16_50_28_2_2_300_5.32e-07_0.001_3.6e-05'),\n",
      " 'image_size': 28,\n",
      " 'kernel_size_pixels': 28,\n",
      " 'layers': 4,\n",
      " 'loss_plot_path': PosixPath('experiments/OpticalSystemMLP_quickdraw_4_2_16_50_28_2_2_300_5.32e-07_0.001_3.6e-05/OpticalSystemMLP_quickdraw_4_2_16_50_28_2_2_300_5.32e-07_0.001_3.6e-05_loss.png'),\n",
      " 'max_passes_through_dataset': 50,\n",
      " 'metric': 0.001,\n",
      " 'mlp_layers': 2,\n",
      " 'model_class': <class 'models.OpticalSystemMLP'>,\n",
      " 'model_path': PosixPath('experiments/OpticalSystemMLP_quickdraw_4_2_16_50_28_2_2_300_5.32e-07_0.001_3.6e-05/OpticalSystemMLP_quickdraw_4_2_16_50_28_2_2_300_5.32e-07_0.001_3.6e-05.pt'),\n",
      " 'name_id': 'OpticalSystemMLP_quickdraw_4_2_16_50_28_2_2_300_5.32e-07_0.001_3.6e-05',\n",
      " 'pixel_size_meters': 3.6e-05,\n",
      " 'propagation_distance': 300,\n",
      " 'resolution_scale_factor': 2,\n",
      " 'test_batch_size': 64,\n",
      " 'test_class_instances': 100,\n",
      " 'test_data_path': './assets/quickdraw16_test.npy',\n",
      " 'tile_size_scale_factor': 2,\n",
      " 'train_class_instances': 8000,\n",
      " 'train_data_path': './assets/quickdraw16_train.npy',\n",
      " 'wavelength': 5.32e-07}\n"
     ]
    }
   ],
   "source": [
    "CONFIG = type('', (), {})() # object for parameters\n",
    "\n",
    "CONFIG.model_class = models.OpticalSystemMLP\n",
    "CONFIG.layers = 4\n",
    "CONFIG.mlp_layers = 2\n",
    "CONFIG.batch_size = 764//5\n",
    "CONFIG.max_passes_through_dataset = 50\n",
    "CONFIG.test_batch_size = 64\n",
    "\n",
    "# свойства входных данных\n",
    "CONFIG.dataset_name = 'quickdraw'\n",
    "CONFIG.classes = 16\n",
    "CONFIG.image_size = 28\n",
    "CONFIG.train_class_instances = 8000\n",
    "CONFIG.test_class_instances = 100\n",
    "CONFIG.train_data_path = './assets/quickdraw16_train.npy'\n",
    "CONFIG.test_data_path = './assets/quickdraw16_test.npy'\n",
    "\n",
    "# свойства модели оптической системы\n",
    "CONFIG.kernel_size_pixels = 28\n",
    "CONFIG.tile_size_scale_factor = 2\n",
    "CONFIG.resolution_scale_factor = 2 \n",
    "CONFIG.class_slots = 16\n",
    "CONFIG.wavelength = 532e-9\n",
    "# CONFIG.refractive_index = 1.5090\n",
    "CONFIG.propagation_distance = 300\n",
    "CONFIG.metric = 1e-3\n",
    "CONFIG.pixel_size_meters = 36e-6\n",
    "\n",
    "CONFIG.name_id = f\"{CONFIG.model_class.__name__}_{CONFIG.dataset_name}_{CONFIG.layers}_{CONFIG.mlp_layers}_{CONFIG.classes}_{CONFIG.max_passes_through_dataset}_{CONFIG.kernel_size_pixels}\" + \\\n",
    "                 f\"_{CONFIG.resolution_scale_factor}_{CONFIG.tile_size_scale_factor}_{CONFIG.propagation_distance}_{CONFIG.wavelength}_{CONFIG.metric}_{CONFIG.pixel_size_meters}\"\n",
    "CONFIG.experiment_dir = Path(f'./experiments/{CONFIG.name_id}/')\n",
    "CONFIG.experiment_dir.mkdir(parents=True, exist_ok=True)\n",
    "CONFIG.model_path = CONFIG.experiment_dir / f\"{CONFIG.name_id}.pt\"\n",
    "CONFIG.loss_plot_path = CONFIG.experiment_dir / f\"{CONFIG.name_id}_loss.png\"\n",
    "\n",
    "yaml.dump(CONFIG, open(CONFIG.experiment_dir / \"config.yaml\", 'w'))\n",
    "\n",
    "def init_from_config(config):\n",
    "    init_arg_names = list(inspect.signature(CONFIG.model_class).parameters.keys())\n",
    "    return CONFIG.model_class(**{k:CONFIG.__dict__[k] for k in init_arg_names})\n",
    "\n",
    "pprint(CONFIG.__dict__)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32211b41-628a-4376-adf3-e93cc58bc2b4",
   "metadata": {},
   "source": [
    "### Служебные функции"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9aefa1b1-e4da-4e02-b691-7745f9759e5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from utils import imshow, pad_zeros, unpad_zeros, to_class_labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41470dee-088e-4d24-8a1f-4b18636b4dac",
   "metadata": {},
   "source": [
    "### Подготовка данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bb84c1e5-0201-4815-bf88-d5512364e731",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([128000, 1, 28, 28]), torch.Size([1600, 1, 28, 28]))"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data = torch.tensor(np.load(CONFIG.train_data_path), dtype=torch.float32)\n",
    "test_data = torch.tensor(np.load(CONFIG.test_data_path), dtype=torch.float32)\n",
    "train_data = rearrange(train_data, \"b (h w) -> b 1 h w\", h=CONFIG.image_size, w=CONFIG.image_size)\n",
    "test_data = rearrange(test_data, \"b (h w) -> b 1 h w\", h=CONFIG.image_size, w=CONFIG.image_size)\n",
    "train_data.shape, test_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2684aad3-16db-41a9-914b-762151d865a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([128000, 16]), torch.Size([1600, 16]))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_targets = torch.eye(CONFIG.classes).repeat_interleave(repeats=CONFIG.train_class_instances, dim=0)\n",
    "test_targets = torch.eye(CONFIG.classes).repeat_interleave(repeats=CONFIG.test_class_instances, dim=0)\n",
    "\n",
    "train_labels = torch.repeat_interleave(torch.arange(CONFIG.classes), CONFIG.train_class_instances)\n",
    "test_labels = torch.repeat_interleave(torch.arange(CONFIG.classes), CONFIG.test_class_instances)\n",
    "\n",
    "train_targets.shape, test_targets.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "200b86bb-188c-4034-8a98-1bcfb5b92d9e",
   "metadata": {},
   "source": [
    "### Создание экземпляра модели, оптимизатора, функции потерь"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "12c87b56-bdcf-4e9c-a171-b096ff244376",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = init_from_config(CONFIG)\n",
    "\n",
    "# comment to train from scratch\n",
    "if Path(CONFIG.model_path).exists():\n",
    "    model.load_state_dict(torch.load(CONFIG.model_path))\n",
    "    print(\"LOADED from checkpoint.\")\n",
    "    \n",
    "model.eval()\n",
    "model.cuda();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "43dcf5cb-a10a-4f02-811a-1c365e2e1bed",
   "metadata": {},
   "outputs": [],
   "source": [
    "optimizer = torch.optim.AdamW(params=model.parameters(), lr=1e-3, weight_decay=0)\n",
    "\n",
    "def get_lr(optimizer):\n",
    "    return list(optimizer.param_groups)[0]['lr']\n",
    "\n",
    "def set_lr(optimizer, passes_through_dataset):\n",
    "    pass\n",
    "\n",
    "loss_function = torch.nn.CrossEntropyLoss()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6f489d1-0d5d-43ec-bcaf-f01a82c28bf1",
   "metadata": {},
   "source": [
    "### Обучение"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c3851a9d-1867-4c5e-b4ec-3598448a054f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 42105/42105 [2:31:33<00:00,  4.63it/s, loss: 2.135540e+00, acc: 0.92, lr: 1.000000e-03, passes_through_dataset: 49/50]\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# training loop\n",
    "epochs = int(train_data.shape[0]/CONFIG.batch_size*CONFIG.max_passes_through_dataset)\n",
    "ppp = tqdm.trange(epochs)\n",
    "loss_hist = []\n",
    "weight_hist = []\n",
    "acc_hist = []\n",
    "f, (ax1, ax2, ax3)  = plt.subplots(1,3, figsize=(4*3,4))\n",
    "\n",
    "def init_batch_generator(train_data, train_labels, batch_size):\n",
    "    \"\"\"\n",
    "    Возвращает функцию, вызов которой возвращает следующие batch_size\n",
    "    примеров и им соответствуюющих меток из train_data, train_labels.\n",
    "    \n",
    "    Примеры выбираются последовательно, по кругу. Массивы с входными \n",
    "    примерами и метками классов перемешиваются в начале каждого круга.\n",
    "    \"\"\"\n",
    "    def f():\n",
    "        i = 0\n",
    "        rnd_indx = torch.randperm(train_data.shape[0])\n",
    "        train_data_shuffled = train_data[rnd_indx]\n",
    "        train_labels_shuffled = train_labels[rnd_indx]\n",
    "        while True:\n",
    "            if i + batch_size > train_data.shape[0]:\n",
    "                i = 0\n",
    "                rnd_indx = torch.randperm(train_data.shape[0])\n",
    "                train_data_shuffled = train_data[rnd_indx]\n",
    "                train_labels_shuffled = train_labels[rnd_indx]\n",
    "                \n",
    "            batch_inputs = train_data_shuffled[i:i+batch_size]\n",
    "            batch_targets = train_labels_shuffled[i:i+batch_size]\n",
    "            i = i + batch_size\n",
    "            yield batch_inputs, batch_targets\n",
    "    return f()\n",
    "\n",
    "batch_iterator = init_batch_generator(train_data, train_targets, CONFIG.batch_size)\n",
    "i = 0\n",
    "\n",
    "for epoch in ppp:     \n",
    "  batch_inputs, batch_targets = next(batch_iterator)\n",
    "  batch_inputs = batch_inputs.cuda()\n",
    "  batch_targets = batch_targets.cuda()\n",
    "  i = i + CONFIG.batch_size\n",
    "  passes_through_dataset = i//train_data.shape[0]\n",
    "  # apply model\n",
    "  predicted, convolved = model(batch_inputs)\n",
    "  # correct model\n",
    "  loss_value = loss_function(predicted, batch_targets)\n",
    "\n",
    "  loss_value.backward()\n",
    "  optimizer.step()\n",
    "\n",
    "  # для небольших батчей следует уменьшать частоту вывода \n",
    "  if epoch % 100 == 0:\n",
    "    acc = accuracy_score(to_class_labels(batch_targets), to_class_labels(predicted))\n",
    "    ppp.set_postfix_str(\"loss: {:e}, acc: {:.2f}, lr: {:e}, passes_through_dataset: {}/{}\".format(loss_value, acc, get_lr(optimizer), passes_through_dataset, CONFIG.max_passes_through_dataset))\n",
    "    loss_hist.append(loss_value.item())   \n",
    "    weight_hist.append(get_lr(optimizer))\n",
    "    acc_hist.append(acc)\n",
    "      \n",
    "  if epoch % 1000 == 0 and epoch > 0:  \n",
    "    vis_loss_hist = np.array(loss_hist)\n",
    "    ax1.cla()\n",
    "    ax2.cla()\n",
    "    ax3.cla()\n",
    "    ax1.plot(np.linspace(0, i, num=len(vis_loss_hist))/len(train_data), vis_loss_hist, label='aloss')\n",
    "    ax1.set_xlabel('passes_through_dataset')\n",
    "    ax1.set_yscale('log')\n",
    "    ax1.set_title(\"loss\")\n",
    "    ax2.set_title(\"optimizer learning rate\")\n",
    "    ax2.set_xlabel('passes_through_dataset')\n",
    "    ax2.set_yscale('log')      \n",
    "    ax2.plot(np.linspace(0,  i, num=len(weight_hist))/len(train_data), weight_hist, label='lr')\n",
    "    ax3.set_title(\"accuracy\")\n",
    "    ax3.set_xlabel('passes_through_dataset')\n",
    "    ax3.plot(np.linspace(0,  i, num=len(acc_hist))/len(train_data), acc_hist, label='acc')\n",
    "    clear_output(wait=True)\n",
    "    f.tight_layout()\n",
    "    display(f)\n",
    "    f.savefig(CONFIG.loss_plot_path)\n",
    "\n",
    "  set_lr(optimizer, passes_through_dataset)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae4259bb-199b-43ee-951a-4d481dd1cddc",
   "metadata": {},
   "source": [
    "### Тест"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f68545e2-7f65-464e-94ef-cee7ffd0236a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('Accuracy on test dataset: ', 0.87625)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inputs = test_data\n",
    "targets = test_targets\n",
    "\n",
    "predicted = []\n",
    "batch_start = 0\n",
    "while batch_start < test_data.shape[0]:\n",
    "    batch_end = min(batch_start + CONFIG.test_batch_size, test_data.shape[0])\n",
    "    batch_input = inputs[batch_start:batch_end].cuda() \n",
    "    batch_output, _ = model(batch_input)\n",
    "    predicted.append(batch_output.detach().cpu())\n",
    "    batch_start = batch_end\n",
    "\n",
    "predicted = torch.concat(predicted)\n",
    "\n",
    "test_acc = accuracy_score(to_class_labels(targets), to_class_labels(predicted))\n",
    "\"Accuracy on test dataset: \", test_acc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9a4cd483-be14-4222-b3c6-0fadd0b1c017",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAo8AAAKpCAYAAADdZcZQAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOy9d5wlVZn//z6n6uZ7u2/n7smJYYiCZGQICosI7KIC6rpLUJQVM2tCfyqY+Kr7VVwXUb4q4LoqgmFNgBlJCgqjxGFy7OncfXOoqvP746l7e5oZoBnpGbHP+/XqF0zdulV1K5x6zhM+jzLGGCwWi8VisVgslmmg9/UBWCwWi8VisVheOFjj0WKxWCwWi8UybazxaLFYLBaLxWKZNtZ4tFgsFovFYrFMG2s8WiwWi8VisVimjTUeLRaLxWKxWCzTxhqPFovFYrFYLJZpY41Hi8VisVgsFsu0scajxWKxWCwWi2XaWOPRAoBSiiuvvHKv7Ov222/nsMMOIx6Po5RifHx8r+z3mfjtb3+LUorf/va3M7L9G2+8EaUUGzdunJHt/61x8sknc/LJJz+v29y4cSNKKW688cbndbszyXN5rpRSvO1tb5vZA0KuzcEHHzzj+9kXzPRzvKfszTFvto01ln2DNR73Ao2HufHnui5z587loosuYtu2bfv68HbLvffey5VXXvm8D3IjIyOcf/75JBIJrr32Wv77v/+bVCr1vO7jmfjSl770gjI+ZiPf+ta3uOaaa/b1YcwIM/VcWf56fvazn83IBHpfj3l/r1SrVd7//vczZ84cEokExxxzDL/4xS/29WHNGtx9fQCziY997GMsXryYSqXC73//e2688UbuvvtuHnnkEeLx+L4+vCnce++9XHXVVVx00UVks9nnbbsPPPAA+Xyej3/845x66qnP23any5e+9CU6Ozu56KKLpiw/8cQTKZfLRKPRvX5Mlql861vf4pFHHuFd73rXlOULFy6kXC4TiUT2zYHtAeVyGdedHGZn6rmy/PX87Gc/49prr33eDci9Peb967/+K6997WuJxWIzvq99yUUXXcStt97Ku971Lvbbbz9uvPFGXvGKV/Cb3/yGE044YV8f3t891njci5xxxhkceeSRAFxyySV0dnby6U9/mh/96Eecf/75+/jo9g6Dg4MAf3MvTq3135wBb5mKUuoFd41eaMdref6ZiTGvWCw+rffScRwcx3ne9vW3yP333893vvMdPvvZz/Ke97wHgAsuuICDDz6Y973vfdx77737+Aj//rFh633IypUrAVi3bt2U5U888QTnnnsu7e3txONxjjzySH70ox9NWader3PVVVex3377EY/H6ejo4IQTTpjitn+6vLOLLrqIRYsWPe1xXXnllbz3ve8FYPHixc1w+7Pl0Nxyyy0cccQRJBIJOjs7+Zd/+ZcpYfmTTz6ZCy+8EICjjjoKpdQuHsCn8tBDD3HGGWfQ0tJCOp3mZS97Gb///e+nrNNIC/jd737HpZdeSkdHBy0tLVxwwQWMjY0111u0aBGPPvood955Z/M3Nc7P0+VK/eEPf+AVr3gFbW1tpFIpDj30UL7whS80P//LX/7CRRddxJIlS4jH4/T29vKGN7yBkZGRZ/xdz8QTTzzB+eefT1dXF4lEgv33358PfehDe3xe7rnnHi6//HK6urpIpVK88pWvZGhoqLneWWedxZIlS3Z7LMcdd1xzwgPgeR4f//jHWbp0KbFYjEWLFvHBD36QarX6jL/p6fKwnnreTz75ZH7605+yadOm5jVq3KtPl/P461//mpUrV5JKpchms/zTP/0Tjz/++JR1rrzySpRSrF27tun1a21t5eKLL6ZUKj3jsf/nf/4njuNMCTX/3//7f1FKcfnllzeX+b5PJpPh/e9/f3PZzjmP032ufvjDH3LwwQcTi8U46KCDuP3225/x+GDyPN5888188IMfpLe3l1QqxT/+4z+yZcuW3X7nscce45RTTiGZTDJ37lw+85nPTPm8VqvxkY98hCOOOILW1lZSqRQrV67kN7/5zS7b+s53vsMRRxxBJpOhpaWFQw45ZMpzAjA+Ps673vUu5s+fTywWY9myZXz6058mCIJn/X2LFi3irLPO4uc//3kzd/DAAw/k+9///rN+96677uK8885jwYIFxGIx5s+fz7vf/W7K5XJznYsuuohrr70WYEqKUYMgCLjmmms46KCDiMfj9PT0cOmll04ZX3bHs415zzZmNo4tnU6zbt06XvGKV5DJZHj961//tPvc3bPWOH+//e1vOfLII0kkEhxyyCHN5+773/8+hxxyCPF4nCOOOIKHHnpoyjafyzjX2Ec8Hmfp0qV85StfaT5/T+Wb3/xm8/e3t7fz2te+9mnv15259dZbcRyHN7/5zc1l8XicN77xjdx3333T2oblr8N6HvchjYe7ra2tuezRRx/lJS95CXPnzuUDH/gAqVSK7373u5xzzjl873vf45WvfCUgL6Krr76aSy65hKOPPppcLscf//hHHnzwQU477bS/6rhe9apX8eSTT/Ltb3+bz3/+83R2dgLQ1dX1tN+58cYbufjiiznqqKO4+uqrGRgY4Atf+AL33HMPDz30ENlslg996EPsv//+XH/99c0Q/tKlS592m48++igrV66kpaWF973vfUQiEb7yla9w8sknc+edd3LMMcdMWf9tb3sb2WyWK6+8ktWrV3PdddexadOm5ov1mmuu4e1vfzvpdLppjPX09Dzt/n/xi19w1lln0dfXxzvf+U56e3t5/PHH+clPfsI73/nO5jrr16/n4osvpre3l0cffZTrr7+eRx99lN///ve7HTCfib/85S+sXLmSSCTCm9/8ZhYtWsS6dev48Y9/zCc/+ck9Oi9vf/vbaWtr46Mf/SgbN27kmmuu4W1vexs333wzAK95zWu44IILeOCBBzjqqKOa39u0aRO///3v+exnP9tcdskll3DTTTdx7rnn8u///u/84Q9/4Oqrr+bxxx/nBz/4wXP6rbvjQx/6EBMTE2zdupXPf/7zAKTT6add/5e//CVnnHEGS5Ys4corr6RcLvPFL36Rl7zkJTz44IO7TJLOP/98Fi9ezNVXX82DDz7IV7/6Vbq7u/n0pz/9tPtYuXIlQRBw9913c9ZZZwFikGitueuuu5rrPfTQQxQKBU488cTdbmc6z9Xdd9/N97//fS677DIymQz/+Z//yatf/Wo2b95MR0fHM5884JOf/CRKKd7//vczODjINddcw6mnnsqqVatIJBLN9cbGxnj5y1/Oq171Ks4//3xuvfVW3v/+93PIIYdwxhlnAJDL5fjqV7/K6173Ot70pjeRz+f52te+xumnn87999/PYYcdBsgz8LrXvY6XvexlzfP4+OOPc8899zSfk1KpxEknncS2bdu49NJLWbBgAffeey9XXHEF/f3908pxXbNmDa95zWv4t3/7Ny688EJuuOEGzjvvPG6//fZnHPNuueUWSqUSb3nLW+jo6OD+++/ni1/8Ilu3buWWW24B4NJLL2X79u384he/4L//+7932call17aHOPe8Y53sGHDBv7rv/6Lhx56iHvuuedpUymeacybzpjZwPM8Tj/9dE444QT+4z/+g2Qy+azn66msXbuWf/7nf+bSSy/lX/7lX/iP//gPzj77bL785S/zwQ9+kMsuuwyAq6++mvPPP5/Vq1ejtfiXpjvOPfTQQ7z85S+nr6+Pq666Ct/3+djHPrbbd8cnP/lJPvzhD3P++edzySWXMDQ0xBe/+EVOPPHEXX7/U3nooYdYvnw5LS0tU5YfffTRAKxatYr58+c/53NkeQ4Yy4xzww03GMD88pe/NENDQ2bLli3m1ltvNV1dXSYWi5ktW7Y0133Zy15mDjnkEFOpVJrLgiAwxx9/vNlvv/2ay170oheZM8888xn3e9JJJ5mTTjppl+UXXnihWbhw4ZRlgPnoRz/a/PdnP/tZA5gNGzY86++r1Wqmu7vbHHzwwaZcLjeX/+QnPzGA+chHPtJc1jgXDzzwwLNu95xzzjHRaNSsW7euuWz79u0mk8mYE088cZdtHnH
      "text/plain": [
       "<Figure size 750x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class_id = 4\n",
    "image = test_data[test_labels==class_id][:1]\n",
    "imshow(image, title=f\"Input image\")\n",
    "softmax, convolved = model(image.cuda())\n",
    "\n",
    "for idx, psf in enumerate(convolved):\n",
    "    psf = psf.squeeze().cpu()\n",
    "    grid_to_depth = rearrange(\n",
    "        psf,\n",
    "        \"(m ht) (n wt) -> (m n) ht wt\",\n",
    "        ht = model.tile_size*model.resolution_scale_factor,\n",
    "        wt = model.tile_size*model.resolution_scale_factor,\n",
    "        m = model.tiles_per_dim,\n",
    "        n = model.tiles_per_dim\n",
    "    )\n",
    "    # 5\n",
    "    grid_to_depth = unpad_zeros(\n",
    "        grid_to_depth, \n",
    "        (model.kernel_size_pixels*model.resolution_scale_factor,  \n",
    "         model.kernel_size_pixels*model.resolution_scale_factor))\n",
    "    # 2\n",
    "    grid_to_depth = pad_zeros(\n",
    "        grid_to_depth, \n",
    "        size = (model.tile_size*model.resolution_scale_factor , \n",
    "                model.tile_size*model.resolution_scale_factor ),\n",
    "    )\n",
    "    grid_to_depth = rearrange(\n",
    "        grid_to_depth,\n",
    "        \"(m n) ht wt -> (m ht) (n wt)\",\n",
    "        ht = model.tile_size*model.resolution_scale_factor,\n",
    "        wt = model.tile_size*model.resolution_scale_factor,\n",
    "        m = model.tiles_per_dim,\n",
    "        n = model.tiles_per_dim\n",
    "    )\n",
    "    \n",
    "    f, ax = imshow(grid_to_depth, figsize=(15*0.5,15*0.5), title=f\"Result of optical convolution with phase plate for image {idx}\")\n",
    "    ax[0].hlines(np.arange(0, grid_to_depth.shape[0], grid_to_depth.shape[0]//model.tiles_per_dim), 0, psf.shape[1]-1)\n",
    "    ax[0].vlines(np.arange(0, grid_to_depth.shape[1], grid_to_depth.shape[1]//model.tiles_per_dim), 0, psf.shape[0]-1)\n",
    "    y,x = (psf==torch.max(grid_to_depth)).nonzero()[0]\n",
    "    ax[0].text(x,y, \"max\", color='white');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63f39f87-5a98-454b-9f1c-fdc712b11f0b",
   "metadata": {},
   "source": [
    "### Сохранение рельефа"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "296f2dab-6f4a-40b1-81ea-a1e7ed7e72ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "imshow([torch.log(x.cpu().detach()).imag for x in model.height_maps], figsize=(20*0.5,10*0.5));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f29aec08-f946-4044-b19d-8718c4673f7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "for idx, heights in enumerate(model.height_maps):\n",
    "    heights = heights.cpu().detach()\n",
    "    heights = torch.log(heights).imag\n",
    "    m = heights.abs().mean()\n",
    "    s = heights.abs().std()\n",
    "    m1, m2 = heights.abs().min(), heights.abs().max()\n",
    "    ar = heights.numpy() \n",
    "    im = ar\n",
    "    im = im - im.min()\n",
    "    im = im / im.max()\n",
    "    im = im * 255\n",
    "    name_im = CONFIG.experiment_dir / (CONFIG.name_id + f\"_phasemask_{idx}.png\")\n",
    "    name_np = CONFIG.experiment_dir / (CONFIG.name_id + f\"_phasemask_{idx}\")\n",
    "    result = Image.fromarray(im.astype(np.uint8))\n",
    "    result.save(name_im)\n",
    "    np.save(name_np, ar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "397220b7-9f0f-416c-a8ad-0bd6ce8220ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save(model.state_dict(), CONFIG.model_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5eba0fb6-4ea2-416f-ba52-088524f7478b",
   "metadata": {},
   "outputs": [],
   "source": [
    "time.sleep(121)\n",
    "Path(CONFIG.experiment_dir / f\"{CONFIG.name_id}.ipynb\").write_bytes(Path(\"Propagator_QuickDraw.ipynb\").read_bytes());"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f21dd086-97e2-4a68-8231-618514de4eeb",
   "metadata": {},
   "source": [
    "### Отладка"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "170205af-f83c-4f3f-93b2-2dcfffef1df2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 1, 56, 56]) (448, 448)\n",
      "torch.Size([1, 16, 112, 112]) (56, 56)\n"
     ]
    }
   ],
   "source": [
    "class_id = 0\n",
    "image = test_data[test_labels==class_id][:1]\n",
    "softmax, convolved, dbg = model.forward_debug(image.cuda())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d4d4a275-c16d-430f-997d-ac25c52cda1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# resized input image\n",
    "imshow(dbg[0]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "be30414a-06b5-4768-a680-994d598421f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# padded input image\n",
    "imshow(dbg[1]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8d8e40d5-7d30-4a96-b747-3568d1e0c96d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# convolution output image\n",
    "imshow(dbg[2],figsize=(10,10));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e7cd6019-d1f7-4cd7-b90f-25eacaa6f8c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArsAAAGHCAYAAACwM5rJAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOy9e6xlyVUe/q2q/Tjn3Ef3zPgV44GAbF4mThzH4HEEAWIehiBbGBKhSHashL9sEmIpUkwSngEDIQIiHAMSAfJwiIxi8iDCQlZslGAHY3DiBMWBBGNe48fMdPe995yzH1Xr98daq6r26dsz0/xsT/dQn9Tq7nPP2ad27dp3f7XWt75FzMyoqKioqKioqKioeBLCPdEDqKioqKioqKioqPhEoZLdioqKioqKioqKJy0q2a2oqKioqKioqHjSopLdioqKioqKioqKJy0q2a2oqKioqKioqHjSopLdioqKioqKioqKJy0q2a2oqKioqKioqHjSopLdioqKioqKioqKJy0q2a2oqKioqKioqHjSopLdioqKioqKioqKJy0q2a2ouEvwjne8A0R06Z93v/vdT/TwKioqKioq7kg0T/QAKioqbg9/82/+TbzwhS9cvPbsZz/7CRpNRUVFRUXFnY1Kdisq7jJ84Rd+Ib7u677uiR5GRUVFRUXFXYEqY6iouAtxdnaGeZ6f6GFUVFRUVFTc8ahkt6LiLsOrX/1qnJ6eYrVa4Uu+5Evwq7/6q0/0kCoqKioqKu5YVBlDRcVdgq7r8IpXvAJf9VVfhac85Sn4jd/4DfzAD/wAvvALvxC//Mu/jOc///lP9BArKioqKiruOBAz8xM9iIqKij8afuu3fgvPe97z8EVf9EX4hV/4hSd6OBUVFRUVFXccqoyhouIuxrOf/Wy87GUvw3/+z/8ZIYQnejgVFRUVFRV3HCrZrai4y3H//fdjHEdcXFw80UOpqKioqKi441DJbkXFXY7/9//+H1arFY6Pj5/ooVRUVFRUVNxxqGS3ouIuwUc/+tGbXvvv//2/49//+3+PL//yL4dz9XauqKioqKg4RC1Qq6i4S/ClX/qlWK/XePGLX4ynPe1p+I3f+A38+I//ONq2xbve9S58zud8zhM9xIqKioqKijsOlexWVNwl+Cf/5J/gX/2rf4Xf+q3fwo0bN/DUpz4Vf/Ev/kV827d9W20XXFFRUVFRcQtUsltRUVFRUVFRUfGkRRX5VVRUVFRUVFRUPGlRyW5FRUVFRUVFRcWTFpXsVlRUVFRUVFRUPGlRyW5FRUVFRUVFRcWTFpXsVlRUVFRUVFRUPGlRyW5FRUVFRUVFRcWTFpXsVlRUVFRUVFRUPGlRyW5FRUVFRUVFRcWTFpXsVlRUVFRUVFRUPGlRyW5FRUVFRUVFRcWTFpXsVlRUVFRUVFRUPGlRyW5FRUVFRUVFxZMQv/RLv4Sv+ZqvwTOf+UwQEX7u537uto/xtre9DS960YtwcnKCpz71qXjFK16BD37wgx/3sX4iUcluRUVFRUVFRcWTEBcXF/jTf/pP441vfOMf6fO//du/jZe97GX40i/9Urzvfe/D2972NnzsYx/D137t136cR/qJBTEzP9GDqKioqKioqKio+MSBiPDWt74VL3/5y9NrwzDg7/29v4d//a//Na5du4bP+7zPw/d93/fhi7/4iwEAP/uzP4tv+IZvwDAMcE7io//hP/wHvOxlL8MwDGjb9gk4k9tHjexWVFRUVFRUVPwxxGtf+1q8613vws/8zM/gf/yP/4Gv//qvx1d+5VfiN3/zNwEAL3jBC+Ccw0/+5E8ihIDr16/jX/yLf4GXvOQldw3RBWpkt6KioqKioqLiSY/DyO6HPvQhfMZnfAY+9KEP4ZnPfGZ630te8hJ8/ud/Pr7ne74HAPDOd74Tf/kv/2U89NBDCCHggQcewH/6T/8JV69efQLO4o+GGtmtqKioqKioqPhjhve///0IIeAzP/MzcXx8nP68853vxP/9v/8XAPDggw/iG7/xG/GqV70K73nPe/DOd74TXdfh677u63A3xUqbJ3oAFRUVFRUVFRUVn1ycn5/De4/3vve98N4vfnZ8fAwAeOMb34grV67g+7//+9PP/uW//Je4//778d/+23/Di170ok/qmP+oqGS3oqKioqKiouKPGZ7//OcjhICPfOQj+MIv/MJL37PdblNhmsGIcYzxEz7GjxeqjKGioqKioqKi4kmI8/NzvO9978P73vc+AGIl9r73vQ8f+tCH8Jmf+Zn4q3/1r+KVr3wl/u2//bf47d/+bfzKr/wK3vCGN+Dnf/7nAQBf/dVfjfe85z34zu/8Tvzmb/4mfu3Xfg2vfvWr8Wmf9ml4/vOf/wSe2e2hFqhVVFRUVFRUVDwJ8Y53vANf8iVfctPrr3rVq/BTP/VTmKYJ//Af/kP883/+z/H7v//7eMpTnoIXvehF+I7v+A78qT/1pwAAP/MzP4Pv//7vx//5P/8Hm80GDzzwAL7v+74Pn/3Zn/3JPp0/MirZraioqKioqKioeNLiCZUxvPGNb8Sf/JN/EqvVCl/wBV+AX/mVX3kih1NRUVFRUVFRUfEkwxMW2f03/+bf4JWvfCV+9Ed/FF/wBV+AH/qhH8Jb3vIWfOADH8DTnva0R/1sjBF/8Ad/gJOTExDRJ2nEFRUVFR9/MDPOzs7wzGc+86ZCkIqKiooS+/0e4zg+0cNYoOs6rFarJ3oYj4onjOx+wRd8AV74whfiR37kRwAIgb3//vvxTd/0Tfi7f/fvPupnf+/3fg/333//J2OYFRUVFZ8U/O7v/i6e9axnPdHDqKiouEOx3+/x6Z92jAc/Ep7ooSzwjGc8A7/92799RxPeJ8R6bBxHvPe978XrX//69JpzDi95yUvwrne966b3D8OAYRjS/42f/4UrfwXt+gr4eAMQgbY78MUF4Dzo5Ai86oE5gM634HkGvAe1DeAd4BzYe4BI/jgCQgTNMxAj4H3+uXxp/psZcA5oPNg5ELN8BpDvCwGIEXyxA+/3oLYB9Sv5XgCIegw7duPB6xV41QLMoDnK38MI3u6BEIAwg0OUSPZqBWq8fK5pAOdA4wg+3wIxgEMEpgnwHu7kBFj38n02xljsb2IEQpSxeCd/bE4AYJzA2618d9uC2jbPl73HPsOcz83m2Dnw8Rph1YCYQVHe43YT6OxCvnvVgdtWzvPhRxCun8H1HdzVq0DXgPsecdMDDnA3dqDzrXzvZgXuWpnzix14mkBNAzRii8LTDIyybjjIuZN3oNVaxseczp1PjhBPelmLuxkYJ9A0ga/dQBxG+PvuQXj6PeDGwZ+PoIttnkc9Dg+DnEPXgza9HPdiD95t9bu9zFvXA1dOwG0Dd36B+JGPgQPD3XMFOD0GGo+4bhFbDxci3MUITDNot0e8fgNghnv6UzE99RTEDH9tB9ruZAzTJNeUo4zPEXDfvQhXN/Lej1wH3ziTe2G9kjW0H8Hn50CMcFevgk+O5HPTDCqtZWy+plnuwRDyfeHk3KhrZS67BhQCaApAZLk3tzu5T9croG2AaUa8cQbej/JZXUfuyin4aCPHDUHGECMwTHIfMwOx+GUfGWhb4N6riCc9aAxwZ1tgmvO6JgLmION3JGvEOblP96Oci/1+APLajhF8foG4G0CeQF0HePksHbbKdCTn5XRtTbN8HzOYWe7dvgV3XTo2MWOOI97xOz+Gk5MTVFRUVNwK4zjiwY8E/PZ7Pw2nJ3dGFujGWcSnv+B3MI5jJbuH+NjHPoYQAp7+9KcvXn/605+O//2///dN73/DG96A7/iO77jp9fbKfWiaNZjkohN14CbKg7c/Aq970BxBUCIVlfBFyHvgwUT68CKAA2iO4DGAOgJcAyYCzQGY9aGvJA4RwEQAjPAYKfYAHMARzBMYLYhaULuWB2FJCOdZHt4gAA3ArTwAx1HeMwIcnfybOrla5AA0IHggOoAbgOX8uVES4BhwQc4JDWgi+Rzp5e4bcC+klfYjMIxCzFYd0LVC+qeC9LcAGj3PACUCXh7eRHLODCAEcIwACEQN4BuAHHh2aAaS8zQS0TdAu84bhRB
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# grid as sequence of images\n",
    "imshow([x for x in dbg[3].squeeze()]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d41cb70b-45ee-4c18-a3ae-c85522ed4562",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArMAAAGHCAYAAACj5No9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAABsw0lEQVR4nO3de3hV9ZU//vfe5+ScXM8JAXKDJAS5gwSNAsGqqCilDiOVsdav34Fa6zztgI/IzK8zdKa1WqextS3alqL9VqXtDKWlU7T1Ri0WqAoKgSjXCBhIuCThlivkJOfsz+8PSjCutWkOoNkH3q/nOc8jn6zs89mXEz/Z2WstyxhjQERERESUgOzengARERER0bniYpaIiIiIEhYXs0RERESUsLiYJSIiIqKExcUsERERESUsLmaJiIiIKGFxMUtERERECYuLWSIiIiJKWFzMEhEREVHC4mKWiIiIiBIWF7NEn7DW1lY89NBD+PSnP42srCxYloUlS5aose+88w7++Z//GaWlpUhKSoJlWZ/sZImIiDyOi1miT9iRI0fwyCOPYMeOHSgpKTlr7Msvv4yf/exnsCwLgwcP/oRmSERElDi4mCX6hOXl5eHQoUPYt28fHn/88bPGfuUrX0FTUxM2btyIm2+++ROaIRERUeLw9/YEiC41wWAQubm5PYrNycn5mGdDRESU2HhnloiIiIgSFhezRERERJSwuJglIiIiooTFxSwRERERJSwuZomIiIgoYXExS0REREQJi4tZIiIiIkpYrDNL1At+/OMfo7GxEQcPHgQA/OEPf8D+/fsBAPfffz/C4TAAYN++ffjlL38JANi4cSMA4NFHHwUAFBUV4R//8R8/6akTERF5imWMMb09CaJLzaBBg7Bv3z71a9XV1Rg0aBAAYPXq1bjhhhvUuOuvvx6rV6/+mGZIRESUGLiYJSIiIqKExWdmiYiIiChhcTFLRERERAmLi1kiIiIiSlhczBIRERFRwuJiloiIiIgSFhezRERERJSwuJglIiIiooTFxSwRERERJSwuZomIiIgoYXExS0REREQJi4tZIiIiIkpYXMwSERERJaC1a9di+vTpyM/Ph2VZeP755+PexsqVKzFx4kRkZGSgf//+mDlzJvbu3XvB5/px4mKWiIiIKAG1tbWhpKQEixYtOqfvr66uxm233YYbb7wRlZWVWLlyJY4cOYLbb7/9As/042UZY0xvT4KIiIiIzp1lWVixYgVmzJjRNRaJRPAf//Ef+NWvfoXGxkaMGTMG3/nOdzB58mQAwG9/+1vcddddiEQisO1T9zf/8Ic/4LbbbkMkEkFSUlIv7En8eGeWiIiI6CI0d+5crFu3DsuWLcN7772HO+64A5/+9Kexa9cuAEBpaSls28Zzzz2HWCyGpqYm/PKXv8SUKVMSZiEL8M4sERERUcL76J3ZmpoaDB48GDU1NcjPz++KmzJlCsaPH49vf/vbAIA1a9bgc5/7HI4ePYpYLIaysjK8/PLLyMzM7IW9ODe8M0tERER0kdmyZQtisRiGDRuG9PT0rteaNWuwZ88eAEBdXR3uu+8+zJ49Gxs2bMCaNWsQCATwD//wD0ike53+3p4AEREREV1Yra2t8Pl8qKiogM/n6/a19PR0AMCiRYsQDofx3e9+t+tr//3f/42CggK8/fbbmDhx4ic653PFxSwRERHRReaKK65ALBZDQ0MDrr32WjXmxIkTXYlfp51e+DqO87HP8ULhYwZERERECai1tRWVlZWorKwEcKrUVmVlJWpqajBs2DDcfffdmDVrFn73u9+huroa77zzDsrLy/HSSy8BAG699VZs2LABjzzyCHbt2oVNmzbhnnvuQVFREa644ope3LP4MAGMiIiIKAGtXr0aN9xwgxifPXs2lixZgs7OTjz66KP4xS9+gQMHDqBfv36YOHEiHn74YVx++eUAgGXLluG73/0u3n//faSmpqKsrAzf+c53MGLEiE96d84ZF7NERERElLD4mAERERERnZfFixdj7NixCIVCCIVCKCsrwyuvvOIav2TJEliW1e2VnJx8Tu/9sSWALVq0CI8//jjq6upQUlKCH/3oRxg/fvzf/D7HcXDw4EFkZGTAsqyPa3pERB87YwxaWlqQn58vkiyIiD6qvb0dHR0dvT2NLoFAoMcLzIEDB+Kxxx7D0KFDYYzBz3/+c9x2223YvHkzRo8erX5PKBRCVVVV17/Pdd33sSxmf/3rX2P+/Pl46qmnMGHCBDzxxBOYOnUqqqqqkJ2dfdbvPXjwIAoKCj6OaRER9Yra2loMHDiwt6dBRB7W3t6O4qJ01DXEensqXXJzc1FdXd2jBe306dO7/fu//uu/sHjxYqxfv951MWtZFnJzc897nh/LYvYHP/gB7rvvPtxzzz0AgKeeegovvfQSnn32Wfz7v//7Wb83IyMDADB+8r/D7z9z8JJaOtV4f1O7HGw4qm/cL3c3MmqAGhrcUiPGTLvyXgDsPplizDmiz8Hu11dut7VVjTUxWRajc9xlamywRr7fiaH6Lw7+Nnkskxr1fbPaToixtpE5amzaloNizMkMqbF2U4sYM51RNTY6SL6fHdE/7FbVB3K7o/VjdjI7RYz5OvRSJEb5bTFl73F9DjE5t1hWuhob6SN/QKTuOKTPISLPW/vl+gIpuWKPnFeGPgenWZ4LFOXLMQB260n5/Q1H1FjVZYU9DrWb29TxSJH8DAWr9GPWMVT+kPRv3q3GHv3sGDF2rES/HsqurBJj2381UozFOtqx4xff6vq5RkTkpqOjA3UNMVRXFCGU0ft/yWlucVBcug9HjhxBKHTm/+XBYBDBYPCs3xuLxbB8+XK0tbWhrKzMNa61tRVFRUVwHAdXXnklvv3tb7sufM/mgi9mOzo6UFFRgQULFnSN2baNKVOmYN26dSI+EokgEol0/bul5dT/WP3+5G6LWb/fJ74XAPw+JX/NDuiTs+Xuxvz6bxt+ZRvG0v/HZtvypDqWPgct1lj6nxS09zOu85Xb9Se5xCrHUj2OACxbLsxct6sdB59+wdu23Gfj9mdYZZ/tqL7wtZTjbnwu81X2w+dSV8/YcjHrd9k3y8hjZrnMIabMQTuOrnNwux6U42C5bNexInLQ9bzJ4+N2ratctqu/l36Otc+s9nkFAEeLdZmvL6BcZyn69ZCUJrehff9pfGSKiHoqlGF7YjF72kf/Wv7QQw/hm9/8phq7ZcsWlJWVob29Henp6VixYgVGjRqlxg4fPhzPPvssxo4di6amJnzve9/DpEmTsG3btrj/knXBF7NHjhxBLBZDTk73u2k5OTnYuXOniC8vL8fDDz98oadBRERElHBixkHMA3WmYubUL/O1tbXizqyb4cOHo7KyEk1NTfjtb3+L2bNnY82aNeqCtqysrNtd20mTJmHkyJF4+umn8a1vfSuuufb60n/BggVoamrqetXW1vb2lIiIiIh6hQPjmReAruoEp19nW8wGAgEMGTIEpaWlKC8vR0lJCZ588ske7XdSUhKuuOIK7N6tPwp2Nhf8zmy/fv3g8/lQX1/fbby+vl59yNft2QtfxIHvQ8+M+qtcFrk5/cRQ003D1FBfRP7JMPXVd9VYM7RYjNkt+jN8xybJ5277vJemb7dWPtvXceUQNdb/xntiLBbUf/+I9ZPPpqa+qx8zkyafFbVcnld1MuR+pG3Stxs7Jp8htV2eMza2fNShc4T+ZwX/pvfFmDUwT41tv04+95iyo06NTT90TA4GktRY4+v5733N4+Qzvp2p+p+Z+66Wx/LEaH3fAk3y0YzAX7aqsbES+RnY8zn9mhy+UHk+vF45NgAO3Cmv1QG/128hRPfK7Ub7paqxSc1y304O6a/GHpokf14M3qkf3+d++SMxdt+wKWrs381bI8ZykprU2Lea5HPYgemHxVisLQL8TN0EEZHKgQMvNJK9ELNwHKfbo6RnE4vFsGXLFnzmM5+J+30u+J3ZQCCA0tJSrFq1qmvMcRysWrXqrA8BExEREV3qYsZ45hWPBQsWYO3atdi7dy+2bNmCBQsWYPXq1bj77rsBALNmzeqWT/XII4/gj3/8Iz7
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArMAAAGHCAYAAACj5No9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAABq/0lEQVR4nO3de5hU1Z0v/O/eVX3vruoL9I2+0MgdBBUVGpOIiiLHYWRkHMfH90CM8byZ0/iqnIwzZJKYaJI28WS8RESTGIlxGAzOgOOVKAYYFQwirVy0BWzoBrqba1+hb7XX+wexsf39FnYhpnbR38/z1PPYq1ftWnvXrnaxa//W1zHGGBARERERxSE31gMgIiIiIjpdnMwSERERUdziZJaIiIiI4hYns0REREQUtziZJSIiIqK4xcksEREREcUtTmaJiIiIKG5xMktEREREcYuTWSIiIiKKW5zMEhEREVHc4mSW6C+sra0Nd999N66++mpkZ2fDcRwsWbJE7furX/0Kl156KfLy8pCUlISysjLcfPPN2L179190zERERH4VjPUAiAaaQ4cO4Z577kFJSQkmTpyINWvWWPtu3rwZZWVl+Ou//mtkZWWhpqYGv/rVr/DCCy/gvffeQ2Fh4V9u4ERERD7EySzRX1hBQQHq6+uRn5+Pd955BxdddJG176OPPiraZs+ejQsvvBBPPfUU/vmf//nLHCoREZHv8TYDor+wpKQk5Ofnn/bzhw4dCgBoamo6MwMiIiKKY7wySxQHDh8+jEgkgtraWtxzzz0AgCuuuCLGoyIiIoo9TmaJ4sCQIUPQ2dkJAMjJycHDDz+MK6+8MsajIiIiij1OZoniwMsvv4yOjg588MEHePrpp9He3h7rIREREfkCJ7NEceCyyy4DAMycORPXXnstxo8fj/T0dMyfPz/GIyMiIootFoARxZlzzjkH559/Pv7t3/4t1kMhIiKKOV6ZJYpDx48f772HloiIaCDjlVkin+rp6cHRo0dF+5/+9Cds2bIFF154YQxGRURE5C+8MksUA4888giampqwf/9+AMDzzz+PvXv3AgBuu+02hMNhtLW1obi4GDfccAPGjRuHtLQ0bNmyBU8++STC4TC+973vxXIXiIiIfMExxphYD4JooBk6dCj27Nmj/q6mpgZDhw5FV1cX7rrrLvzxj3/E7t27cfz4cRQWFmL69On47ne/2xueQERENJBxMktEREREcYv3zBIRERFR3OJkloiIiIjiFiezRERERBS3OJklIiIiorjFySwRERERxS1OZomIiIgobnEyS0RERERxi5NZIiIiIopbnMwSERERUdziZJaIiIiI4hYns0REREQUtziZJSIiIopD69atw6xZs1BYWAjHcbBy5cqot7Fq1SpMmTIFGRkZGDx4MObMmYPdu3ef8bF+mTiZJSIiIopD7e3tmDhxIhYtWnRaz6+pqcG1116Lyy+/HFVVVVi1ahUOHTqE66677gyP9MvlGGNMrAdBRERERKfPcRysWLECs2fP7m3r7OzEv/zLv+Df//3f0dTUhPHjx+OnP/0ppk2bBgB49tlnceONN6KzsxOue+L65vPPP49rr70WnZ2dSEhIiMGeRI9XZomIiIjOQvPnz8f69euxbNkyvP/++7j++utx9dVXY8eOHQCASZMmwXVdPPnkk4hEImhubsbvfvc7TJ8+PW4msgCvzBIRERHFvc9ema2trcWwYcNQW1uLwsLC3n7Tp0/HxRdfjJ/85CcAgLVr1+Lv/u7vcPjwYUQiEZSXl+Oll15CZmZmDPbi9PDKLBEREdFZZsuWLYhEIhg5ciTS09N7H2vXrsWuXbsAAA0NDbj11lsxb948bNy4EWvXrkViYiL+9m//FvF0rTMY6wEQERER0ZnV1taGQCCATZs2IRAI9Pldeno6AGDRokUIh8P42c9+1vu7p59+GsXFxXj77bcxZcqUv+iYTxcns0RERERnmfPPPx+RSAQHDhzAV7/6VbXPsWPHegu/PvHJxNfzvC99jGcKbzMgIiIiikNtbW2oqqpCVVUVgBNLbVVVVaG2thYjR47ETTfdhLlz5+I///M/UVNTgz/96U+orKzEiy++CAC45pprsHHjRtxzzz3YsWMH3n33Xdx8880oLS3F+eefH8M9iw4LwIiIiIji0Jo1a3DZZZeJ9nnz5mHJkiXo7u7Gj370Izz11FPYt28fBg0ahClTpuCHP/whzj33XADAsmXL8LOf/QwfffQRUlNTUV5ejp/+9KcYPXr0X3p3Thsns0REREQUt3ibARERERHFrS+tAGzRokW4//770dDQgIkTJ+IXv/gFLr744s99nud52L9/PzIyMuA4zpc1PCKiL50xBq2trSgsLBRFFkREn9XR0YGurq5YD6NXYmIikpOTYz2Mz/Wl3GbwzDPPYO7cuXjssccwefJkPPjgg1i+fDmqq6uRm5t7yufu3bsXxcXFZ3pIREQxU1dXh6KiolgPg4h8rKOjA2Wl6Wg4EIn1UHrl5+ejpqbG9xPaL2UyO3nyZFx00UV45JFHAJy42lpcXIzbbrsN//zP/3zK5zY3NyMzMxPTCm9B0E3sbTdJiWp/p1P+C6Z5UqHSEwhtOyzaDk0ZrPbN3tYq2rzEgNITCO7cL9qM5V9Wbk6W7Nt2XO3rBOSVnKOXlqp9Q9Vtou1YUaraN7VBvl4kSb9In7CzXrS1TtHHkLa3XbQFDsvjCADHRsjjnvpBg9oXQXncjw8bpHdt7xFtbkRfXiRwqEW0dRVnq329oHwvepL18yG1Vu6z03BQ7ds9SpngWL6RSGiU49XOfwDwmmVfDB2i9nX2Nsq2FP0Pl7rdiP6H10nPkG1p+na78zNFW3CXfj50jZH70ZOivxdp7+8TbbbPZlv5MDmudP1q6uGJsm3475rkuCKdWPvRL9DU1IRwOKxui4gIAFpaWhAOh1GzqRShjNh/k9PS6qFs0h40NzcjFArFejindMZvM+jq6sKmTZuwcOHC3jbXdTF9+nSsX79e9O/s7ERnZ2fvz62tJyYCQTcRQTept90ELJNZV/6PP5ig/w8zGEgSbYFEW1/5PzwvqB+uT0+6P2Esd0i4rhyDcS2TAeVryYB137plm7Wv/PeLE8W+2bcr9yPg6hOHYFBuI6gcGwCAKycq2vNPtCuTWVgms26naPMs29Ums0iw/ONGOXcc5TgCgNFezzKZDQbkeLXzHwA8R3k95fw/8XKyr2N5L9TtOrbzt//b1Y6Ddu4BlvfI9l5on03L/yO089pL1Du7yhC0vy+f4C1TRNRfoQzXF5PZeHLGj9ahQ4cQiUSQl5fXpz0vLw8NDfJKS2VlJcLhcO+DtxgQERHRQBUxnm8e8SLmU/+FCxeiubm591FXVxfrIRERERHFhAfjm0e8OOO3GQwaNAiBQACNjX3vw2tsbER+fr7on5SUhKQk+fXcgelFfW4ByF0j7+sDAChfs7oRyxug3IOauUO/X7VpjLzfL/u/tqt9Oy4eIdpSdh3Sx9Ahvyq2MRlpoi38gX4PauCobE/fe0Dt66TLe2ndFMtXpF3y9oWko7INANwWeSy7C+Q9wgCQ8u4e0WY8y9fVYXmvTmKTfhx70pWvti33zGr3YSds36v2xaBM0eTmpqtdO4rkuZPaLO9pBgBHOVU7BiWofQNtKXIMak/AHSTv/d3/Vf29KHz2iGg7dq5+f21Kndw376MafQzK+dtVrI/B/e/35XbP1xfsbhohz9W8P+jv265/KBNtpS/o70XdbHn+ZeU0q32LUzpEW/avZN/u9i5guroJIiKVB89yc9xflj9G0T9n/MpsYmIiJk2ahNWrV/e2eZ6H1atXo7y8/Ey/HBEREdFZI2KMbx7x4ktZZ3bBggWYN28eLrzwQlx88cV48MEH0d7ejptvvvnLeDkiIiKis4JfvuL3wxj660uZzN5www04ePAgvv/976OhoQHnnXceXnnlFVEURkRERET0RXxpCWDz58/H/Pnzv6zNExEREZ11PBhEfHBVdMBfmSUiIiKi6PE2g+j5djKb9eFxBIOfOpBHmvSOqbIyP+mwXm2PelndnyADrk68/ma
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArMAAAGHCAYAAACj5No9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAABp2ElEQVR4nO39e3xV5Zk3/n/W2js75+yQADmQBKIgJwUEBUJrRYtS6vjIyDg+/uwLxtrOdB7gUXk6ndJp66ltbLVF2+KhT62041Ba/BV9qlVqscCooBCMchDkEEiAHDjlCDmtdX//QILxum7M5tCsbT7v12u/Wu5ce+17rb12vLP2uq7LMcYYEBERERHFIbe3J0BEREREdLa4mCUiIiKiuMXFLBERERHFLS5miYiIiChucTFLRERERHGLi1kiIiIiiltczBIRERFR3OJiloiIiIjiFhezRERERBS3uJglIiIiorjFxSzR31hzczPuvfdefOELX0BWVhYcx8GSJUs+8XkdHR0YNWoUHMfBI488cuEnSkREFAe4mCX6Gzt8+DAeeOABvP/++xg7dmyPn/ezn/0MlZWVF3BmRERE8YeLWaK/sby8PFRXV2Pfvn14+OGHe/Scuro6PPDAA/j3f//3Czw7IiKi+MLFLNHfWGJiInJzc2N6zje/+U0MHz4cX/rSly7QrIiIiOJTuLcnQERn9vbbb+PXv/41Xn/9dTiO09vTISIiChRemSUKMGMM5s+fj1tvvRUlJSW9PR0iIqLA4ZVZogBbsmQJNm/ejOeee663p0JERBRIvDJLFFCNjY1YuHAh/u3f/g2FhYW9PR0iIqJA4pVZooB65JFH0N7ejltvvRV79+4FAOzfvx8AcOzYMezduxf5+fmIRCK9OEsiIqLexSuzRAFVWVmJY8eOYfTo0SguLkZxcTGuuuoqAMAPfvADFBcXY9u2bb08SyIiot7FK7NEAfW///f/xsyZM7uN1dXV4V/+5V/wT//0T7jppptQXFzcO5MjIiIKCC5miXrBz3/+c9TX1+PgwYMAgD/+8Y9dtxDMnz8f0WgU48ePx/jx47s979TtBqNHjxYLXSIior6Ii1miXvDII49g3759Xf/+wx/+gD/84Q8AgC996UuIRqO9NTUiIqK44hhjTG9PgoiIiIjobDABjIiIiIjiFhezRERERBS3uJglIiIiorjFxSwRERERxS0uZomIiIgobnExS0RERERxi4tZIiIiIopbXMwSERERUdziYpaIiIiI4hYXs0REREQUt7iYJSIiIqK4xcUsERERURxau3YtbrzxRuTn58NxHDz//PMxb2PlypWYPHky0tPTMWDAAMyaNQt79+4973O9kLiYJSIiIopDLS0tGDt2LBYvXnxWz6+oqMBNN92Ea6+9FuXl5Vi5ciUOHz6Mm2+++TzP9MJyjDGmtydBRERERGfPcRysWLECM2fO7Bpra2vDf/zHf+C3v/0t6uvrcemll+KHP/whpk6dCgB47rnncNttt6GtrQ2ue/L65h//+EfcdNNNaGtrQ0JCQi/sSex4ZZaIiIjoU2jevHlYt24dli1bhvfeew+33HILvvCFL2Dnzp0AgAkTJsB1XTzzzDPwPA8NDQ34z//8T0ybNi1uFrIAr8wSERERxb2PX5mtrKzERRddhMrKSuTn53fFTZs2DRMnTsQPfvADAMCaNWvwj//4jzhy5Ag8z0NJSQn+9Kc/ITMzsxf24uzwyiwRERHRp8zmzZvheR4uueQSpKWldT3WrFmD3bt3AwBqamrw1a9+FXPmzMGGDRuwZs0aRCIR/MM//APi6VpnuLcnQERERETnV3NzM0KhEMrKyhAKhbr9LC0tDQCwePFiRKNR/OhHP+r62bPPPovCwkK89dZbmDx58t90zmeLi1kiIiKiT5nLL78cnuehrq4OV111lRpz/PjxrsSvU04tfH3fv+BzPF94mwERERFRHGpubkZ5eTnKy8sBnCy1VV5ejsrKSlxyySW4/fbbMXv2bPzhD39ARUUF3n77bZSWluKll14CANxwww3YsGEDHnjgAezcuRObNm3CHXfcgcGDB+Pyyy/vxT2LDRPAiIiIiOLQ6tWrcc0114jxOXPmYMmSJejo6MD3vvc9/OY3v8GBAwfQv39/TJ48Gffffz8uu+wyAMCyZcvwox/9CB988AFSUlJQUlKCH/7whxgxYsTfenfOGhezRERERBS3eJsBEREREcWtC5YAtnjxYjz88MOoqanB2LFj8bOf/QwTJ078xOf5vo+DBw8iPT0djuNcqOkREV1wxhg0NTUhPz9fJFkQEX1ca2sr2tvbe3saXSKRCJKSknp7Gp/ogtxm8Lvf/Q6zZ8/Gk08+iUmTJuHRRx/F8uXLsWPHDgwcOPCMz92/fz8KCwvP95SIiHpNVVUVCgoKensaRBRgra2tKB6chpo6r7en0iU3NxcVFRWBX9BekMXspEmTcOWVV+LnP/85gJNXWwsLCzF//nx885vfPONzGxoakJmZialF/4ywG+ka9/qlqfGhQw1irK14gBobOVAvxjoHpKux4YpaMdY6epAam7D6Xfn8vBw19vioPDGWsuWgGmuicp87M5P1OVQfk89P1k8+E5EX5J0DdWqsk5QoxtqH6H+QJBw9Lsb81IgSCXSkyfGEN7epsW6/qJxXRG+z1zAhX4wlHetQYxP3HBJjprFJjfWHyT+w3IYTaqzT2ia32yKPDQC0XzpYjEXeP6DGqq+VIt8fAPAPH5WxlmPmpKbK51uOg6vEwvIrxKQq52qD5fgOyZWDW3arsZ2TZFKCH9K/xUkq3yvndUJ/3xpuHCPGvIi+3Y40OZ50TJax8TpaUb7ie6ivr0c0Ks9jIqJTGhsbEY1GUVE2GBnpvf9NTmOTj+IJ+9DQ0ICMjIzens4ZnffbDNrb21FWVoaFCxd2jbmui2nTpmHdunUivq2tDW1tp//j39R08j92YTeCsHv6P9ROSP+PdsiV415YX8SFtW3YYl252ArbYh25SAgr87JtQ3stADAxzVfGqs8HYELKYtYyB0fZrm89vvKvSd82h7ByfJXjCACuMjfbfMMJyvENh5RIyzFz5EIUAPyQ3K4b0mvwOcrvION06tuN4XzQX8uymHWUY2Y5vup7bDkO2nthXcxq773b8+MLy3y1z4BtMRtWjoNx9KseIeXcgWUx6yvjoQR7TUbeMkVEPZWR7gZiMRtPzvvROnz4MDzPQ05O9yuTOTk5qKmpEfGlpaWIRqNdD95iQERERH2VZ/zAPOJFry/9Fy5ciIaGhq5HVVVVb0+JiIiIqFf4MIF5xIvzfptB//79EQqFUFvb/Z7T2tpa5ObK++ISExORmKh8Hek4Jx8fchv1+9yMkvXnduh/TXQMyhRj4Qb9a8/Oi+W9rUlle9TY9qmyS4bTpGcjJm9UtmG5sdpplvsc7tC/robyNaZzrFEN7bxIvg9h5b5UADgySd77m712vxprMuT9lO5eeTUeACI52XJQuT8XAEyD3A9nQH81Nu3/vSPnoN27CcAvkO+xo7wWADjblPdtkHKfJwAvJ1OMmUFZamzidnl/bGexvl248j12yz/QQ3Plfc211+n3fA98brt8fppybywAkynvMbedZ2Z/tRy8ZIga6x6Xnxfbe1w7Un5ecv9zsxq748HRYqzgL/rvh4aL5N/2nWn6L3NfuaUg8YuHxZhpaQN+r26CiEjlw0cQrokGYxY9c96vzEYiEUyYMAGrVq3qGvN9H6tWrUJJScn5fjkiIiKiTw3PmMA84sUFqTO7YMECzJkzB1dccQUmTpyIRx99FC0tLbjjjjsuxMsRERERfSoE5Sv+IMyhpy7IYvbWW2/FoUOH8N3vfhc1NTUYN24cXnnlFZEURkRERER0Li5YB7B58+Zh3rx5F2rzRERERJ86Pgy8AFwV7fNXZomIiIgodrzNIHaBXcw2jRrQrQB+pFHP4nfblA5elpuWIztkdrXJ0DuLJRyql4OW2Eh5hTquys6UY5YKBd4AWWEgdEBmTAOAUbpOYaBSMQBAuKFVjPnpKWps5nOyOoAZYqkF7MvMR79Rz3R3s+S++Zb
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# grid as sequence of images, unpadded\n",
    "imshow([x for x in dbg[4].squeeze()]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8a803ba7-338c-4be0-ad1a-67aa6d66de54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 16 artists>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAicAAAGdCAYAAADJ6dNTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAfHUlEQVR4nO3df1SW9f3H8Rc/5MZMKWXcCGFYWWoakAQHrXU63Yuah+Y6LWYmHCp3anBC780pFbBmibZJ9INkWq7+yEnrTFfpcMTE5hFjQaw8M638AbMBelpguMBxX98/Ot19SVQuvPH+ePN8nHP9wcV13df7OtTds+u+7vsOsizLEgAAgCGC/T0AAADA/0ecAAAAoxAnAADAKMQJAAAwCnECAACMQpwAAACjECcAAMAoxAkAADBKqL8HGAiPx6NPP/1Uo0ePVlBQkL/HAQAAA2BZlo4dO6aYmBgFBw/8esh5ESeffvqp4uLi/D0GAAAYhJaWFl1yySUD3v68iJPRo0dL+urkxowZ4+dpAADAQHR2diouLs773/GBOi/i5OuXcsaMGUOcAABwnrF7SwY3xAIAAKMQJwAAwCjECQAAMApxAgAAjEKcAAAAoxAnAADAKMQJAAAwCnECAACMQpwAAACjECcAAMAotuPk7bffVkZGhmJiYhQUFKRNmzadcZ/a2lpde+21cjgcuuKKK/TSSy8NYlQAADAc2I6Trq4uJSQkqLy8fEDbHzhwQLNnz9ZNN92kpqYmLVy4UPfff7+2bt1qe1gAABD4bH/x32233abbbrttwNtXVFRo4sSJWrVqlSRpypQp2rFjh5566imlp6fbPTwAAAhwQ37PSV1dnVwuV5916enpqqurO+U+3d3d6uzs7LMAAIDhwfaVE7taW1vldDr7rHM6ners7NR///tfjRw58qR9SkpK9Nhjjw31aMNG/NLNQ/bYB1fMHrLHBgAMT0a+W6egoEAdHR3epaWlxd8jAQCAc2TIr5xER0erra2tz7q2tjaNGTOm36smkuRwOORwOIZ6NAAAYKAhv3KSlpammpqaPuuqq6uVlpY21IcGAADnIdtx8sUXX6ipqUlNTU2SvnqrcFNTk5qbmyV99ZJMVlaWd/sHHnhA+/fv1y9+8Qt9+OGHev755/Xqq69q0aJFvjkDAAAQUGzHybvvvqukpCQlJSVJktxut5KSklRUVCRJ+ve//+0NFUmaOHGiNm/erOrqaiUkJGjVqlV64YUXeBsxAADoV5BlWZa/hziTzs5ORUREqKOjQ2PGjPH3OOcd3q0DAPCHwf7328h36wAAgOGLOAEAAEYhTgAAgFGIEwAAYBTiBAAAGIU4AQAARiFOAACAUYgTAABgFOIEAAAYhTgBAABGIU4AAIBRiBMAAGAU4gQAABiFOAEAAEYhTgAAgFGIEwAAYBTiBAAAGIU4AQAARiFOAACAUYgTAABgFOIEAAAYJdTfAwAYmPilm4fssQ+umD1kjw0AdnHlBAAAGIU4AQAARiFOAACAUYgTAABgFOIEAAAYhTgBAABGIU4AAIBRiBMAAGAU4gQAABiFOAEAAEYhTgAAgFGIEwAAYBTiBAAAGIU4AQAARiFOAACAUYgTAABgFOIEAAAYhTgBAABGIU4AAIBRiBMAAGAU4gQAABiFOAEAAEYhTgAAgFGIEwAAYBTiBAAAGIU4AQAARiFOAACAUYgTAABgFOIEAAAYJdTfAwAAcD6KX7p5yB774IrZQ/bY5wOunAAAAKMQJwAAwCjECQAAMApxAgAAjMINsRgS3CgGABgsrpwAAACjECcAAMAoxAkAADDKoOKkvLxc8fHxCg8PV2pqqurr60+7fVlZma666iqNHDlScXFxWrRokb788stBDQwAAAKb7TiprKyU2+1WcXGxGhsblZCQoPT0dLW3t/e7/fr167V06VIVFxdrz549evHFF1VZWamHH374rIcHAACBx/a7dUpLS7VgwQLl5ORIkioqKrR582atW7dOS5cuPWn7nTt3atasWbr77rslSfHx8Zo7d67eeeedsxwd8C/ekQQAQ8PWlZOenh41NDTI5XJ98wDBwXK5XKqrq+t3n5kzZ6qhocH70s/+/fu1ZcsWff/73z/lcbq7u9XZ2dlnAQAAw4OtKydHjx5Vb2+vnE5nn/VOp1Mffvhhv/vcfffdOnr0qK6//npZlqX//e9/euCBB077sk5JSYkee+wxO6MBAIAAMeQfwlZbW6vly5fr+eefV2pqqj7++GPl5+dr2bJlKiws7HefgoICud1u78+dnZ2Ki4sb6lEBAD7Cy544G7biJDIyUiEhIWpra+uzvq2tTdHR0f3uU1hYqPnz5+v++++XJE2fPl1dXV36yU9+okceeUTBwSe/suRwOORwOOyMBgAAAoSte07CwsI0Y8YM1dTUeNd5PB7V1NQoLS2t332OHz9+UoCEhIRIkizLsjsvAAAIcLZf1nG73crOzlZycrJSUlJUVlamrq4u77t3srKyFBsbq5KSEklSRkaGSktLlZSU5H1Zp7CwUBkZGd5IAQDgbPAyUmCxHSeZmZk6cuSIioqK1NraqsTERFVVVXlvkm1ubu5zpeTRRx9VUFCQHn30UR0+fFjf+c53lJGRoSeeeMJ3ZwEAAALGoG6IzcvLU15eXr+/q62t7XuA0FAVFxeruLh4MIcKSBQ+AACnxnfrAAAAoxAnAADAKMQJAAAwCnECAACMMuSfEAsAdgzVDePcLA6cP7hyAgAAjEKcAAAAoxAnAADAKMQJAAAwCnECAACMQpwAAACj8FZiAMPacPiuq+FwjggsXDkBAABGIU4AAIBRiBMAAGAU4gQAABiFOAEAAEYhTgAAgFGIEwAAYBTiBAAAGIU4AQAARiFOAACAUYgTAABgFOIEAAAYhS/+AwDgPDCcvsCRKycAAMAoxAkAADAKcQIAAIxCnAAAAKMQJwAAwCjECQAAMApxAgAAjEKcAAAAoxAnAADAKHxCLACcY0P1SZ+mfconMFjECYBTGk4flw3AHMM+TnjyBQDALNxzAgAAjEKcAAAAoxAnAADAKMQJAAAwCnECAACMQpwAAACjECcAAMAoxAkAADAKcQIAAIxCnAAAAKMQJwAAwCjECQAAMApxAgAAjDLsv5UYgYFvlwaAwMGVEwAAYBTiBAAAGIU4AQAARiFOAACAUYgTAABgFOIEAAAYhTgBAABGIU4AAIBRBhUn5eXlio+PV3h4uFJTU1VfX3/a7T///HPl5uZq/PjxcjgcuvLKK7Vly5ZBDQwAAAKb7U+IrayslNvtVkVFhVJTU1VWVqb09HTt3btXUVFRJ23f09Oj733ve4qKitJrr72m2NhYHTp0SBdddJEv5gcAAAHGdpyUlpZqwYIFysnJkSRVVFRo8+bNWrdunZYuXXrS9uvWrdNnn32mnTt3asSIEZKk+Pj4s5saAAAELFsv6/T09KihoUEul+ubBwgOlsvlUl1dXb/7vP7660pLS1Nubq6cTqemTZum5cuXq7e395TH6e7uVmdnZ58FAAAMD7bi5OjRo+rt7ZXT6eyz3ul0qrW1td999u/fr9dee029vb3asmWLCgsLtWrVKj3++OOnPE5JSYkiIiK8S1xcnJ0xAQDAeWzI363j8XgUFRWlNWvWaMaMGcrMzNQjjzyiioqKU+5TUFCgjo4O79LS0jLUYwIAAEPYuuckMjJSISEhamtr67O+ra1N0dHR/e4zfvx4jRgxQiEhId51U6ZMUWtrq3p6ehQWFnbSPg6HQw6Hw85oAAAgQNi6chIWFqYZM2aopqbGu87j8aimpkZpaWn97jNr1ix9/PHH8ng83nX79u3T+PHj+w0TAAAwvNl+Wcftdmvt2rV6+eWXtWfPHj344IPq6uryvnsnKytLBQUF3u0ffPBBffbZZ8rPz9e+ffu0efNmLV++XLm5ub47CwAAEDBsv5U4MzNTR44cUVFRkVpbW5WYmKiqqirvTbLNzc0KDv6meeLi4rR161YtWrRI11xzjWJjY5Wfn68lS5b47iwAAEDAsB0nkpSXl6e8vLx+f1dbW3vSurS0NO3atWswhwIAAMMM360
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# max pool sequence\n",
    "plt.bar(np.arange(CONFIG.class_slots), dbg[5].cpu().detach().squeeze())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2bb8e371-b841-4a72-bca9-6370d3d94c88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1500x1500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for idx, psf in enumerate(convolved):\n",
    "    psf = psf.squeeze().cpu()\n",
    "    grid_to_depth = rearrange(\n",
    "        psf,\n",
    "        \"(m ht) (n wt) -> (m n) ht wt\",\n",
    "        ht = model.tile_size*model.resolution_scale_factor,\n",
    "        wt = model.tile_size*model.resolution_scale_factor,\n",
    "        m = model.tiles_per_dim,\n",
    "        n = model.tiles_per_dim\n",
    "    )\n",
    "    # 5\n",
    "    grid_to_depth = unpad_zeros(\n",
    "        grid_to_depth, \n",
    "        (model.kernel_size_pixels*model.resolution_scale_factor,  \n",
    "         model.kernel_size_pixels*model.resolution_scale_factor))\n",
    "    # 2\n",
    "    grid_to_depth = pad_zeros(\n",
    "        grid_to_depth, \n",
    "        size = (model.tile_size*model.resolution_scale_factor , \n",
    "                model.tile_size*model.resolution_scale_factor ),\n",
    "    )\n",
    "    grid_to_depth = rearrange(\n",
    "        grid_to_depth,\n",
    "        \"(m n) ht wt -> (m ht) (n wt)\",\n",
    "        ht = model.tile_size*model.resolution_scale_factor,\n",
    "        wt = model.tile_size*model.resolution_scale_factor,\n",
    "        m = model.tiles_per_dim,\n",
    "        n = model.tiles_per_dim\n",
    "    )\n",
    "    \n",
    "    f, ax = imshow(grid_to_depth, figsize=(15,15), title=f\"Result of optical convolution with phase plate for image {idx}\")\n",
    "    ax[0].hlines(np.arange(0, grid_to_depth.shape[0], grid_to_depth.shape[0]//model.tiles_per_dim), 0, psf.shape[1]-1)\n",
    "    ax[0].vlines(np.arange(0, grid_to_depth.shape[1], grid_to_depth.shape[1]//model.tiles_per_dim), 0, psf.shape[0]-1)\n",
    "    y,x = (psf==torch.max(grid_to_depth)).nonzero()[0]\n",
    "    ax[0].text(x,y, \"max\", color='white');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7743069d-2ec2-413b-aaaf-3e68881fc88f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "imshow(model.U.cpu());"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8336f1f6-da6a-432c-ac0c-86a37e70ee5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "imshow([model.x, model.y]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "cee5e6d7-2201-4458-9750-cfec98f6a707",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1040x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "imshow([model.Kx, model.Ky]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "167e777f-627d-48ca-8023-6f4eeed78d87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 2000x2000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "imshow(model.vv, figsize=(20,20));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9e305082-be6e-4331-866c-70bb4981c28d",
   "metadata": {},
   "outputs": [],
   "source": [
    "time.sleep(121)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4c6a3586-20ec-4c5e-8719-5525f052f5c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "Path(CONFIG.experiment_dir / f\"{CONFIG.name_id}.ipynb\").write_bytes(Path(\"Propagator_QuickDraw.ipynb\").read_bytes());"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "62f07333-6211-48a9-9f57-37462c87084b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}