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": 34,
   "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": 35,
   "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_1_2_16_50_14_1_1_0.5_300_5.32e-07_0.001_3.6e-05'),\n",
      " 'image_size': 28,\n",
      " 'input_image_scale': 0.5,\n",
      " 'kernel_size_pixels': 14,\n",
      " 'layers': 1,\n",
      " 'loss_plot_path': PosixPath('experiments/OpticalSystemMLP_quickdraw_1_2_16_50_14_1_1_0.5_300_5.32e-07_0.001_3.6e-05/OpticalSystemMLP_quickdraw_1_2_16_50_14_1_1_0.5_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_1_2_16_50_14_1_1_0.5_300_5.32e-07_0.001_3.6e-05/OpticalSystemMLP_quickdraw_1_2_16_50_14_1_1_0.5_300_5.32e-07_0.001_3.6e-05.pt'),\n",
      " 'name_id': 'OpticalSystemMLP_quickdraw_1_2_16_50_14_1_1_0.5_300_5.32e-07_0.001_3.6e-05',\n",
      " 'pixel_size_meters': 3.6e-05,\n",
      " 'propagation_distance': 300,\n",
      " 'resolution_scale_factor': 1,\n",
      " 'test_batch_size': 64,\n",
      " 'test_class_instances': 100,\n",
      " 'test_data_path': './assets/quickdraw16_test.npy',\n",
      " 'tile_size_scale_factor': 1,\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 = 1\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.input_image_scale = 0.5\n",
    "CONFIG.kernel_size_pixels = 28//2\n",
    "CONFIG.tile_size_scale_factor = 1\n",
    "CONFIG.resolution_scale_factor = 1 \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.input_image_scale}_{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": 36,
   "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": 37,
   "id": "bb84c1e5-0201-4815-bf88-d5512364e731",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([128000, 1, 14, 14]), torch.Size([1600, 1, 14, 14]))"
      ]
     },
     "execution_count": 37,
     "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 = torch.nn.functional.interpolate(train_data, scale_factor=CONFIG.input_image_scale, mode='bicubic')\n",
    "test_data = torch.nn.functional.interpolate(test_data, scale_factor=CONFIG.input_image_scale, mode='bicubic')\n",
    "train_data.shape, test_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "2684aad3-16db-41a9-914b-762151d865a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([128000, 16]), torch.Size([1600, 16]))"
      ]
     },
     "execution_count": 38,
     "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": 39,
   "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": 40,
   "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": 41,
   "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 [02:02<00:00, 343.16it/s, loss: 2.246252e+00, acc: 0.80, 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": 42,
   "id": "f68545e2-7f65-464e-94ef-cee7ffd0236a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('Accuracy on test dataset: ', 0.786875)"
      ]
     },
     "execution_count": 42,
     "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": 89,
   "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": "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
      "text/plain": [
       "<Figure size 750x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class_id = 0 \n",
    "example_num = 2\n",
    "image = test_data[test_labels==class_id][example_num:example_num+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": 44,
   "id": "296f2dab-6f4a-40b1-81ea-a1e7ed7e72ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAsYAAAHeCAYAAACYBc3eAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAABvz0lEQVR4nO3dd3SU1aIF8D1pk4Q0QkkIJPQqAgICQVSaFBVBUFFRQREsgNIs6AXEBooKqBQLgl5BBAQRFRCjYqEHUEB6DSQh1DRSZ+b94SP35eXs3AkkzDDs31pZ63o2Z+bLN+UePs7ssTgcDgdERERERK5yXq4+ABERERERd6CFsYiIiIgItDAWEREREQGghbGIiIiICAAtjEVEREREAGhhLCIiIiICQAtjEREREREAWhiLiIiIiADQwlhEREREBIAWxiIiIiIiALQwFpFi5OTk4LnnnkNUVBQCAgLQunVrrF692tWHJSIiUia0MBYRasCAAXjnnXfQr18/TJs2Dd7e3rj11lvx+++/u/rQRERESp3F4XA4XH0QIuJ+Nm7ciNatW2Py5MkYPXo0ACA7OxuNGzdG5cqVsXbtWhcfoYiISOnSFWMRMVq8eDG8vb0xePDggjF/f38MHDgQ69atQ0JCgguPTkREpPRpYSwiRlu3bkW9evUQEhJSaLxVq1YAgG3btrngqERERMqOFsYiYpSUlIQqVaoUGb8wlpiYeLkPSUREpExpYSwiRllZWbBarUXG/f39C3IRERFPooWxiBgFBAQgJyenyHh2dnZBLiIi4km0MBYRoypVqiApKanI+IWxqKioy31IIiIiZUoLYxExatasGfbu3Yu0tLRC4xs2bCjIRUREPIkWxiJidNddd8Fms+HDDz8sGMvJycGcOXPQunVrREdHu/DoRERESp+Pqw9ARNxT69atcffdd2PMmDFISUlBnTp18Omnn+Lw4cOYPXu2qw9PRESk1Omb70SEys7OxtixY/H555/j7NmzaNKkCV555RV07drV1YcmIiJS6rQwFhERERGB9hiLiIiIiADQwlhEREREBIAWxiIiIiIiALQwFhEREREBoIWxiIiIiAgALYxFRERERABoYSwiIiIiAkALYxERERERAFoYi4iIiIgA0MJYRERERASAFsYiIiIiIgC0MBYRERERAaCFsYiIiIgIAC2MRUREREQAaGEsIiIiIgJAC2MREREREQBaGIuIiIiIANDCWEREREQEgBbGIiIiIiIAtDAWEREREQGghbGIiIiICAAtjEVEREREAGhhLCIiIiICQAtjEREREREAWhiLiIiIiADQwlhEREREBIAWxiIiIiIiALQwFhEREREBoIWxiIiIiAgALYxFRERERABoYSwiIiIiAkALYxERERERAFoYi4iIiIgAAHxcfQD/n91uR2JiIoKDg2GxWFx9OCIichk5HA6kp6cjKioKXl66diNSGrKzs5Gbm+vqwwAA+Pn5wd/f39WHQZXZwnj69OmYPHkykpOT0bRpU7z33nto1arVf52XmJiI6OjosjosERG5AiQkJKBatWquPgyRK152djZqVg9CcorN1YcCAIiMjMShQ4fcdnFcJgvjL7/8EiNHjsSsWbPQunVrTJ06FV27dsWePXtQuXLlYucGBwcDABo8PA7efkVPWvjf2XSuV56dZr4Jp4zjdb84QedsnXgdzbIqetOsar+DNPt7Qy2a1W55lGapOfwJFPZklnHcERpE50xZ+jnNPjoTS7OVhxvSrJw//9voqZPBNAsIzqFZlVm+xvGQscfpnG27q9Os1qJ8mh3q6Uez6FX8DaXamP00O/ECP5aETuWM43EPvkvn9HlpKM3uH72CZt8NvpFmFpuDZql1+eOWWYVfzbORp2vAKX5flmLes4OP8ueWz+gUmo2uvopmZ23m8w8AW8/zx+2rn82vj8qN+HEE+fHn+PmZUTTzP81/7+wK/Pl6sgV/f6oTe4RmD0auM45PndiXzrH58H/Zs/CHG+kx5nn2nGwcnPpywf8XiMilyc3NRXKKDUfiayAk2LX/CpOWbkf1FoeRm5t7dS2M33nnHQwaNAgPP/wwAGDWrFn47rvv8Mknn+D5558vdu6F7RPefv7GhbFPMUfs5eALYx8vq3HcGmReeAGAjy9/0Lz9+P/x+Jbj/4flVcwTwaec+RgBwMenmMzLvKJwePM5wcW8OKy5/Jx4B/Lb9Pbn/wfpFVDMuQykEXx8zOey2HNczH35+PCFsVcAv00fH75qK+5YfHyK+b3Jc6G4x8b0mrggIIi/OHyKeS5YwFcvxb4GrMW8wZK78/a7uIWxjw+/r+JeN+WKOZc5Nv4atnrx1wB7DRf7+uVPkWLPcbG/t29x7zMX9/4UGGye513MMcL34hbG3tbit8ppK51I6QoKtiAo2LWvKzvc/3Vd6gvj3NxcxMfHY8yYMQVjXl5e6Ny5M9atK3o1IicnBzk5/7makpaWVtqHJCIiInJVsznsKOYfCC/bMbi7Ur+mfurUKdhsNkRERBQaj4iIQHJycpE/P3HiRISGhhb8aH+xiIiIiLiCyz/yO2bMGKSmphb8JCQkuPqQRERERDyKHQ63+CmJmTNnokmTJggJCUFISAhiY2OxYgX/PE1pKPWtFBUrVoS3tzdOnCj8obYTJ04gMjKyyJ+3Wq2wWvnePBERERG5NHbY4eqNDCU9gmrVqmHSpEmoW7cuHA4HPv30U/Ts2RNbt27FNddcUybHaHE4HKW+46R169Zo1aoV3nvvPQD/dBPHxMRg6NCh//XDd2lpaQgNDUXnmsOMH5g7PJl/krzGqHSaNV5qbnxY+VlbfizX8E+EB4Txdoyaz2bQbPdTRf9ycIHfGX4B/7G+39Nszke3Gsfz+KmCbybPrGf5U6LW4D00y8jjf8G5r8pGmnkX80L51zf3GsfDd9ApuPuZH2j2xcGWNDt3JIxm99+4lmYbn2xOs8TR/MN+vnGhxvHMG/nzx5bIP6nY62Z+jtfMaE2zR0d9Q7Nv7rqBZnYr/4Bawr/M49nn+Qe//u74Ic1aTX6aZnnFlBcEJvHncqX1Z2mW/hZ/7b9eb4lx/JGlj9M53ln8Ayev3DOfZv/66n6a5ZXnn1b8vttUmt07ZTTNou88ZBzftZW3dFzXkreytC3PG3qifM3n/3yGDYOab0FqaipCQkLofBFxzoV1VeKeam7RShFV/9glvb7Dw8MxefJkDBw4sJSP7h9l0koxcuRI9O/fHy1btkSrVq0wdepUZGZmFrRUiIiIiMjlY3M4YCv9a6ElPgagaNGCM7sHbDYbFi1ahMzMTMTG8lrZS1UmC+O+ffvi5MmTGDduHJKTk9GsWTOsXLmyyAfyRERERKTsXcwe37I4BgBFihbGjx+Pl156yThn+/btiI2NRXZ2NoKCgrB06VI0atSozI6xzL75bujQoRg6lH8ZgYiIiIhcfRISEgptpSjuanH9+vWxbds2pKamYvHixejfvz/WrFlTZovjMlsYi4iIiIh7sMMBm5tcMb7QMuEMPz8/1KlTBwDQokULbNq0CdOmTcMHH3xQJseohbGIiIiIh3OnrRSXdBt2e6EvhittWhiLiIiIiNsZM2YMunfvjpiYGKSnp2P+/Pn45ZdfsGrVqjK7zzKpa7sUF2pFkvdEG2tFGv00mM4N+82fZmda5RnHN3SdRue0+Xokze5oG0+zuC9b0Syjtvk4AOBfNy2n2cx37qRZ5V9OGMcz61ekc46aG94AAMH7+d+XfhoxmWax83gNlP8ZXlf14sAvaJZpN+87mn+cn+NT31Wj2RODltFs1syeNMs1N6sBAO6/5yea/XayDs327q9iHK/3xBY658hL/PdGA17zVmU237+V0pxXqKFlKo1qDOfZ7tcrGceHN+fnitV3AcCr7z5As8x2/Pe2bgmiWU44f+ubctccmo1YbG7Xsfvy27Oe5hVJ+QF8Xm5lXvcXHn9x1zUqfriOZrYO5urBEy34e6tPFr+vqBWJNDvUL8p8DDnZ2P/GC6prEyklF9ZVe3dFINjFdW3p6XbUa3jC6df3wIEDERcXh6SkJISGhqJJkyZ47rnncMs
      "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": 45,
   "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": 19,
   "id": "397220b7-9f0f-416c-a8ad-0bd6ce8220ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.save(model.state_dict(), CONFIG.model_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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": 47,
   "id": "170205af-f83c-4f3f-93b2-2dcfffef1df2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 1, 14, 14]) (56, 56)\n",
      "torch.Size([1, 16, 14, 14]) (14, 14)\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": 48,
   "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": 49,
   "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": 50,
   "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": 51,
   "id": "e7cd6019-d1f7-4cd7-b90f-25eacaa6f8c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAsAAAAGHCAYAAAC+muSmAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAAA6oUlEQVR4nO3de3hU1b3/8c8kkEnATCBgMskhYLxxBxEkRqwHSw4RI9UjvaAoqFSOnNAKaRXpDyiFaipWxQuFUhXoKXjrqdSCBSPXIuEWSEW0EWyUWElyvJCBQC7M7N8fNFMHAiQ4e2Yx83712c/T7L3yne+EJHxYrr22w7IsSwAAAECUiAl3AwAAAEAoEYABAAAQVQjAAAAAiCoEYAAAAEQVAjAAAACiCgEYAAAAUYUADAAAgKhCAAYAAEBUIQADAAAgqhCAAQAAEFUIwIAh6uvrNXXqVKWnpyshIUFZWVkqKioKd1sAAEQcAjBgiLvuuktPPPGExowZo6eeekqxsbG68cYbtXnz5nC3BgBARHFYlmWFuwkg2m3fvl1ZWVl67LHH9OMf/1iSVFdXpz59+iglJUVbtmwJc4cAAEQOZoABA/z+979XbGysJkyY4D8XHx+v8ePHq7i4WBUVFWHsDgCAyEIABgywe/duXX755XK5XAHnBw8eLEkqLS0NQ1cAAEQmAjBggIMHDyotLe2U803nPv3001C3BABAxCIAAwY4duyYnE7nKefj4+P91wEAQHAQgAEDJCQkqL6+/pTzdXV1/usAACA4CMCAAdLS0nTw4MFTzjedS09PD3VLAABELAIwYIArrrhCH3zwgTweT8D5bdu2+a8DAIDgIAADBvj2t78tr9erRYsW+c/V19dr8eLFysrKUkZGRhi7AwAgsrQJdwMApKysLH3nO9/RtGnTVF1drUsvvVRLly7VRx99pOeffz7c7QEAEFF4EhxgiLq6Os2YMUO/+93v9OWXX6pfv36aM2eOcnNzw90aAAARhQAMAACAqMIaYAAAAEQVAjAAAACiCgEYAAAAUYUADAAAgKhCAAYAAEBUIQADAAAgqhCAAQAAEFUIwAAAAIgqBGAAAABEFQIwAAAAogoBGAAAAFGFAAwAAICoQgAGAABAVCEAAwAAIKoQgAEAABBVCMAAAACIKgRgAAAARBUCMAAAAKIKARgAAABRhQAMAACAqEIABgAAQFQhAAMAACCqEIABAADwtSxYsED9+vWTy+WSy+VSdna2/vznP/uv19XVKT8/X506ddIFF1ygUaNGqaqqKqDGgQMHlJeXp3bt2iklJUUPPPCAjh8/HjBmw4YNuvLKK+V0OnXppZdqyZIl59Rvm3P6LBv5fD59+umnSkxMlMPhCHc7AHDOLMvS4cOHlZ6erpgY5hsAnFldXZ0aGhrC3YZfXFyc4uPjWzS2S5cu+sUvfqHLLrtMlmVp6dKluvnmm7V792717t1bU6ZM0apVq/Tqq68qKSlJkyZN0q233qq3335bkuT1epWXlye3260tW7bo4MGDGjt2rNq2batHHnlEklReXq68vDzdd999WrZsmdauXavvf//7SktLU25ubuvenGWYiooKSxIHBwdHxBwVFRXh/tUKwHDHjh2z3CmxYf999dXD7XZbx44dO+f31LFjR+u5556zDh06ZLVt29Z69dVX/dfef/99S5JVXFxsWZZlvfHGG1ZMTIxVWVnpH7NgwQLL5XJZ9fX1lmVZ1oMPPmj17t074DW+973vWbm5ua3uzbgZ4MTERElS+qPTFJPQsn91tFTGyqCW86v4T58tdd1v2vPHE9to2VK3rkOsLXVdB+ptqVvfoa0tddsc9Z5XdWMa7alb1zm4P79NYmz6/j2eEPwZWm9jnUpWP+z/vQYAp9PQ0KDKaq/KS7rJlRj+/2LkOexT5sCP9dlnn8nlcvnPO51OOZ3OM36u1+vVq6++qtraWmVnZ6ukpESNjY3Kycnxj+nRo4e6du2q4uJiXX311SouLlbfvn2VmprqH5Obm6uJEydq7969GjBggIqLiwNqNI2ZPHlyq9+fcQG4adlDTEJ80ANwG3vyjmIS7AnAbdraFIBlT4CIjbMnALdpY89SGG9bmwJwG5sCsE11Yyyb+m1rUwC26ftXbe37C4flXABaypUYY0QAbpKRkRHw8U9/+lPNmjWr2bF79uxRdna26urqdMEFF+i1115Tr169VFpaqri4OHXo0CFgfGpqqiorKyVJlZWVAeG36XrTtTON8Xg8OnbsmBISElr8vowLwAAAANHKa/nktenf+a3tQ5IqKipOmQE+ne7du6u0tFQ1NTX6/e9/r3Hjxmnjxo2293ouCMAAAACG8MmSz67/0tXKPiT5d3Voibi4OF166aWSpIEDB2rHjh166qmn9L3vfU8NDQ06dOhQwCxwVVWV3G63JMntdmv79u0B9Zp2ifjqmJN3jqiqqpLL5WrV7K/ENmgAAADG8Bn0v6/9Xnw+1dfXa+DAgWrbtq3Wrl3rv1ZWVqYDBw4oOztbkpSdna09e/aourraP6aoqEgul0u9evXyj/lqjaYxTTVagxlgAAAAQ3gtS14r/DPAre1h2rRpGjFihLp27arDhw9r+fLl2rBhg9asWaOkpCSNHz9eBQUFSk5Olsvl0g9+8ANlZ2fr6quvliQNHz5cvXr10p133qm5c+eqsrJS06dPV35+vn/ZxX333adnn31WDz74oO655x6tW7dOr7zyilatWtXq92fbDPD8+fN10UUXKT4+XllZWadMawMAACBQ0xIIE47WqK6u1tixY9W9e3cNGzZMO3bs0Jo1a/Qf//EfkqQnn3xSN910k0aNGqXrrrtObrdbf/jDH/yfHxsbq5UrVyo2NlbZ2dm64447NHbsWM2ePds/JjMzU6tWrVJRUZH69++vxx9/XM8991zr9wCWTTPAL7/8sgoKCrRw4UJlZWVp3rx5ys3NVVlZmVJSUux4SQAAAITJ888/f8br8fHxmj9/vubPn3/aMd26ddMbb7xxxjpDhw7V7t27z6nHr7JlBviJJ57Qvffeq7vvvlu9evXSwoUL1a5dO73wwgt2vBwAAEBE8MmS14DDhBvx7BT0GeCGhgaVlJRo2rRp/nMxMTHKyclRcXHxKePr6+tVX/+vBx14PJ5gtwQAAHBeMG0XiEgV9Bngzz77TF6vt9mNips2Mv6qwsJCJSUl+Y+TN1wGAACIFk03wZlwRLKwb4M2bdo01dTU+I+KiopwtwQAABAWPoOOSBb0JRCdO3dWbGxssxsVN21k/FUteaY0AAAAECxBnwGOi4vTwIEDAzYq9vl8Wrt27TltVAwAABAtwn3z21ePSGbLNmgFBQUaN26cBg0apMGDB2vevHmqra3V3XffbcfLAQAARASvdeIINxN6sJMtAfh73/ue/u///k8zZ85UZWWlrrjiCq1evfqUG+MAAADwL6asvzWhBzvZ9ijkSZMmadKkSXaVBwAAiDg+OeSVI9xtyGdAD3ayLQADAACgdXzWiSPcTOjBTmHfBg0AAAAIJWaAAQAADOE1ZAmECT3YiQAMAABgCAJwaBgbgJ0H2yo2vm1Qa1bdfTio9Zpk/saeB3n4Yu25B7N92f/ZUvf4Vac+6CQYqgbG21I3bUutLXV9cbG21G37t09sqavGBlvKXnDQZUvdmkHpttQ93DX4f27eenu+FwBELp/lkM8Kf/g0oQc7GRuAAQAAog0zwKFBAAYAADCEVzHyGrBHgTfcDdgs/F9hAAAAIISYAQYAADCEZcgaYMuAHuxEAAYAADAEa4BDgwAMAABgCK8VI68V/hWq3gh/EhwBGAAAwBA+OeQz4BYtnyI7AROAAQAADMESiNAI/z8xAAAAgBBiBhgAAMAQ5qwBZgkEAAAAQuDEGuDwLz8woQc7EYABAAAM4TPkSXDcBAcAAICQYAlEaBCAAQAADOFTDNughUD4v8IAAABACDEDDAAAYAiv5ZDXCv8NaCb0YCcCMAAAgCG8htwE543wJRAEYAAAAEP4rBj5DLgJzsdNcAAAAAgFZoBDgwAMAABgCJ/MWH/rC3cDNgv/PzEAAACAEDJ2Bji
      "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": "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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": 52,
   "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": "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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, unpadded\n",
    "imshow([x for x in dbg[4].squeeze()]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "8a803ba7-338c-4be0-ad1a-67aa6d66de54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 16 artists>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "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": 54,
   "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": 55,
   "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": 56,
   "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": 57,
   "id": "cee5e6d7-2201-4458-9750-cfec98f6a707",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAroAAAGHCAYAAABf8fH3AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAAA260lEQVR4nO3df3RU9Z3/8dfkx0yAMAOBkCFLQqEq8UcD2yhhWusqpqSsy8qS9tiWrWBz6qk74QixFakV0OrGSg+IGlG7CHZXFktb7Kmu/GisUDWhGM3Wn1nx0G/SwoR2KwmwzSTMvd8/kKkjAZnkhvuZyfNxzucc5nNvZt43nBNe+fC+n+uxbdsWAAAAkGYy3C4AAAAAGAwEXQAAAKQlgi4AAADSEkEXAAAAaYmgCwAAgLRE0AUAAEBaIugCAAAgLRF0AQAAkJYIugAAAEhLBF0AAACkJYIuYIhoNKqlS5eqsLBQw4YNU3l5uXbu3Ol2WQAApCyCLmCIhQsXavXq1Zo/f77Wrl2rzMxM/f3f/71efPFFt0sDACAleWzbtt0uAhjqfvOb36i8vFyrVq3St771LUlSd3e3LrnkEo0bN04vv/yyyxUCAJB6WNEFDPCTn/xEmZmZuvHGG+NzOTk5qq6uVmNjo9rb212sDgCA1ETQBQzw2muv6YILLpDf70+Ynz59uiSppaXFhaoAAEhtBF3AAAcPHtT48eNPmT85d+DAgXNdEgAAKY+gCxjgL3/5i3w+3ynzOTk58eMAACA5BF3AAMOGDVM0Gj1lvru7O34cAAAkh6ALGGD8+PE6ePDgKfMn5woLC891SQAApDyCLmCAadOm6X/+53/U1dWVML9nz574cQAAkByCLmCAL37xi4rFYnrsscfic9FoVBs2bFB5ebmKiopcrA4AgNSU5XYBAKTy8nJ96Utf0rJly3To0CGdd955euKJJ/S73/1O69evd7s8AABSEk9GAwzR3d2tO+64Q//xH/+h999/X6Wlpfre976nyspKt0sDACAlEXQBAACQlujRBQAAQFoi6AIAACAtEXQBAACQlgi6AAAASEsEXQAAAKQlgi4AAADSEkEXAAAAaYmgCwAAgLRE0AUAAEBaIugCAAAgLRF0AQAAkJYIugAAAEhLBF0AAACkJYIuAAAA0hJBFwAAAGmJoAsAAIC0RNAFAABAWiLoAgAAIC0RdAEAAJCWCLoAAABISwRdAAAApCWCLgAAANISQRcAAABpKWuw3ri+vl6rVq1SJBLR1KlT9eCDD2r69Okf+3WWZenAgQMaOXKkPB7PYJUHAIPOtm0dOXJEhYWFyshgXQHAmXV3d6unp8ftMuK8Xq9ycnLcLmNAPLZt206/6VNPPaXrr79ejzzyiMrLy3X//fdry5Ytam1t1bhx4874tb///e9VVFTkdEkA4Jr29nZNmDDB7TIAGKy7u1uTJuYqcijmdilxwWBQ+/fvT+mwOyhBt7y8XJdddpkeeughSSdWaYuKirRo0SLddtttZ/zazs5OjRo1Spfr75WlbKdLA4Bz5rh69aL+S4cPH1YgEHC7HAAG6+rqUiAQ0P7mifKPdP9/gLqOWJpU9v/U2dkpv9/vdjn95njrQk9Pj5qbm7Vs2bL4XEZGhioqKtTY2HjK+dFoVNFoNP76yJEjHxSWrSwPQRdACvtgGYE2LABnyz8yw4igmy4c/07+6U9/UiwWU0FBQcJ8QUGBIpHIKefX1dUpEAjEB20LAABgqIrZljEjHbj+K8OyZcvU2dkZH+3t7W6XBAAA4ApLtjFjIO699155PB4tXrw4Ptfd3a1wOKwxY8YoNzdXVVVV6ujoGOB37Mwcb10YO3asMjMzTym8o6NDwWDwlPN9Pp98Pt8p855srzy0LgBIYR7bI/W6XQWAVGLJkglrqQOpYu/evXr00UdVWlqaML9kyRI9++yz2rJliwKBgGpqajRv3jy99NJLAy33tBxf0fV6vSorK1NDQ0N8zrIsNTQ0KBQKOf1xAAAAaSNm28aM/jh69Kjmz5+vH/7whxo9enR8vrOzU+vXr9fq1as1c+ZMlZWVacOGDXr55ZfV1NTk1LfvFIPSulBbW6sf/vCHeuKJJ/T222/rpptu0rFjx3TDDTcMxscBAACkBbfbFT7autDV1ZUwPryBQF/C4bCuueYaVVRUJMw3Nzert7c3Yb6kpETFxcV9blbglEF5YMR1112nP/7xj1q+fLkikYimTZumbdu2nXKDGgAAAMz10U0CVqxYoZUrV/Z57ubNm/Xqq69q7969pxyLRCLyer0aNWpUwvzpNitwyqA9Ga2mpkY1NTWD9fYAAABpx5Kt2ABvBHOqDunEA28+vI9uX/dVnTzv5ptv1s6dO416wMSgBV0AAAAkx4kdD5yqQ5L8fv9ZPTCiublZhw4d0qc//en4XCwW0+7du/XQQw9p+/bt6unp0eHDhxNWdU+3WYFTjA26nhyvPB6v22UAQL+x6wKAZA3kRjCn60jG1Vdfrddffz1h7oYbblBJSYmWLl2qoqIiZWdnq6GhQVVVVZKk1tZWtbW1DepmBcYGXQAAgKHG+mC4LdkaRo4cqUsuuSRhbsSIERozZkx8vrq6WrW1tcrLy5Pf79eiRYsUCoU0Y8YMh6o+FUEXAAAAg27NmjXKyMhQVVWVotGoKisr9fDDDw/qZxJ0AQAADBEz5GY0J2p44YUXEl7n5OSovr5e9fX1A37vs0XQBQAAMETMPjHcZkINTjA26Hqys+XJ4BHAAFKXx0qTfykAnDOp2qNrKmODLgAAwFBjyaOYPG6XIcuAGpxA0AUAADCEZZ8YbjOhBidkuF0AAAAAMBhY0QUAADBEzJDWBRNqcAJBFwAAwBAEXWcZG3Q9Xq88GTwCGEDq8qTLbcsAzhnL9siy3Q+ZJtTgBGODLgAAwFDDiq6zCLoAAACGiClDMQP2Coi5XYBD3P9OAgAAAIOAFV0AAABD2Ib06NoG1OAEc4OuL1viZjQAqSxddlwHcM7Qo+ssc4MuAADAEBOzMxSz3e8sjaXJ7+kEXQAAAENY8sgy4BYqS+mRdAm6AAAAhqB1wVnu/8oAAAAADAJWdAEAAAxhTo8urQuDys7Kkp1pbHkA8LHsWLpsuQ7gXDnRo+t+24AJNTiBJAkAAGAIy5Ano3EzGgAAABxF64KzCLoAAACGsJTB9mIOcv87CQAAAAwCc1d0vdlSZrbbVQBA/8UstysAkGJitkcx2/0bwUyowQnmBl0AAIAhJmbIzWgxWhcAAADgJMvOMGYkY926dSotLZXf75ff71coFNJzzz0XP97d3a1wOKwxY8YoNzdXVVVV6ujocPrbdwqCLgAAgCFOruiaMJIxYcIE3XvvvWpubtYrr7yimTNn6tprr9Wbb74pSVqyZIl+8YtfaMuWLdq1a5cOHDigefPmDca3MAGtCwAAAIawZEZ/bLJ3GMyZMyfh9T333KN169apqalJEyZM0Pr167Vp0ybNnDlTkrRhwwZdeOGFampq0owZMxyq+lSs6AIAAKBPXV1dCSMajX7s18RiMW3evFnHjh1TKBRSc3Ozent7VVFRET+npKRExcXFamxsHMzyzV3RtbxZsngEMIAUZvEIYABJMmcf3RM1FBUVJcyvWLFCK1eu7PNrXn/9dYVCIXV3dys3N1dbt27VRRddpJaWFnm9Xo0aNSrh/IKCAkUikcEoP44kCQAAYAhznox2oob29nb5/f74vM/nO+3XTJkyRS0tLers7NRPfvITLViwQLt27Rr0Ws+EoAsAAGAISx5ZMqFH90QNJ3dROBter1fnnXeeJKmsrEx79+7V2rVrdd1116mnp0eHDx9OWNXt6OhQMBh0vPYPc/9XBgAAAEj664quCWOgLMtSNBpVWVmZsrOz1dDQED/W2tqqtrY2hUKhAX/OmbCiCwAAYAhzHhiRXA3Lli3T7NmzVVxcrCNHjmjTpk164YUXtH37dgUCAVVXV6u2tlZ5eXny+/1atGiRQqHQoO64IBkcdO0sj+ws9/+iAaC/bI/7//0IAOfCoUOHdP311+vgwYMKBAIqLS3V9u3b9fnPf16StGbNGmVkZKi
      "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": 58,
   "id": "167e777f-627d-48ca-8023-6f4eeed78d87",
   "metadata": {},
   "outputs": [
    {
     "data": {
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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": null,
   "id": "9e305082-be6e-4331-866c-70bb4981c28d",
   "metadata": {},
   "outputs": [],
   "source": [
    "time.sleep(121)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "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
}