imlstagetrainer.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "calling imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.vision.all import *\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "from loss_functions.triplet_loss import TripletLoss\n",
    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "L2 normalization function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "class L2_norm(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(L2_norm, self).__init__()\n",
    "\n",
    "    def forward(self, x):\n",
    "        return F.normalize(x, p=2, dim=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/mnt/sda/nikhil/pbb/iml/train/mid/04995-base_zl_20_03283_tx_268729_ty_595319__from_1S_134-135_-pine-middle.jpg\n",
      "/mnt/sda/nikhil/pbb/iml/valid/mid/23772-base_zl_20_tx_893080_ty_409455__from_3s_119_136-pine-middle.jpg\n"
     ]
    }
   ],
   "source": [
    "from fastai.vision.all import *\n",
    "\n",
    "path = \"/mnt/sda/nikhil/pbb/iml/\"\n",
    "train_path = \"/mnt/sda/nikhil/pbb/iml/train/\"\n",
    "valid_path = \"/mnt/sda/nikhil/pbb/iml/valid/\"\n",
    "\n",
    "# Define the transformations and batch size\n",
    "item_tfms = Resize(224)\n",
    "batch_size = 64\n",
    "\n",
    "# Define the data block\n",
    "dblock = DataBlock(blocks=(ImageBlock, CategoryBlock),\n",
    "                   get_items=get_image_files,\n",
    "                   get_y=parent_label,\n",
    "                   splitter=GrandparentSplitter(train_name='train', valid_name='valid'))\n",
    "\n",
    "# Create the dataloaders for training and validation sets\n",
    "dls = dblock.dataloaders(path, item_tfms=item_tfms, bs=batch_size)\n",
    "print(dls.train_ds.items[0])\n",
    "print(dls.valid_ds.items[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 900x900 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "dls.show_batch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn = vision_learner(dls, resnet50, pretrained=True)\n",
    "\n",
    "# Modify the second layer of the ResNet-50 model\n",
    "layers = learn.model[1]\n",
    "learn.model[1] = nn.Sequential(layers[0], layers[1], layers[2], layers[3], nn.Linear(in_features=4096, out_features=128, bias=False), L2_norm()).to(device)\n",
    "\n",
    "# Set the model directory\n",
    "learn.model_dir = '/mnt/sda/nikhil/pbb/imlmodels/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#triplet loss\n",
    "learn.loss_func = TripletLoss(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "SuggestedLRs(valley=0.02754228748381138)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkAAAAG1CAYAAAARLUsBAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABRd0lEQVR4nO3deVxVdf4/8Ne5G/cC97IKsoOiguKKK0Zli6S5Npa2aM5Y6YwzZU6N+TP7plM6TVnNTGqLUdoyauaUlZNSuVMhJO4CLuybrJf9Xu49vz+QOyGILPdygPt6Ph73oZx77uH9AeW++GxHEEVRBBEREZEdkUldABEREVFXYwAiIiIiu8MARERERHaHAYiIiIjsDgMQERER2R0GICIiIrI7DEBERERkdxiAiIiIyO4opC6gOzKbzcjNzYVWq4UgCFKXQ0RERG0giiIqKirg6+sLmaz1Ph4GoBbk5uYiICBA6jKIiIioA7KysuDv79/qOQxALdBqtQAavoA6nU7iaoiIiKgt9Ho9AgICLO/jrWEAakHjsJdOp2MAIiIi6mHaMn2Fk6CJiIjI7jAAERERkd3hEBgREZEVmUwmGI1GqcvotVQq1U1XeLUFAxAREZEViKKI/Px8lJWVSV1KryaTyRASEgKVStWp6zAAERERWUFj+PHy8oKjoyP3kbOBxn368vLyEBgY2KmvMQMQERFRJ5lMJkv48fDwkLqcXq1Pnz7Izc1FfX09lEplh6/DSdBERESd1Djnx9HRUeJKer/GoS+TydSp6zAAERERWQmHvWzPWl9jBiAiIiKyOwxAREREZHcYgIiIiLoLswm4cgQ4vavhT3Pn5rl0heDgYLz55puWjwVBwBdffCFZPW3FVWBERETdwbk9wLcrAH3u/47pfIF7XgEGz5Curl6KAYh6nHqTGXnltdBplNCpFc0mxFUb6pFTWoPs0hpU1NVDFEUAgCgCIkSE9dUhrK+WkxU7yGwWka+vRWZJNTKLq5FZUo2MkmqYzGb083RGfy8n9O/jjH59nKFWyFBeY0R5jRFlNUaUVxtRUmVASZUBxVUGlFTVobzGCLlMgEImg1Iug0ohwNlBgcG+Ogz1c0GIpzPkMn6vqJc7twfYuQCA2PS4Pq/h+APbGIKsjAGIeoS88hocTr2KQ6lXcSStCBW19QAAlVwGD2cVPJxVkAkCckprUFxluOn1gj0cERPRF/cM6YsRAa4QBAH1JjNKqgworKhDcZUBFbVGVNbWo6K2HhW1RhhMIlRyAUq5DEpFw5u1k0oOF42y4eGohE6tRF29GeU1RuhrjNDXGlFrNGFCP08EekizPNZoMiOjuBq1RhN8XTVwc1S2Kfw1Bs3Mkmqk5FcgtaACF/IrkFZQgSpD13XLO6rkGOKrwwBvLTydVPBwdoC7U8P33FGlgFwQIJPhWogS0MdZDZ2meTA2m0VklVbjfJ4eeeW1cFTJ4ahSwMmh4U9HlRwapRxqpRyaa393VMkZlMn2zKaGnp/rww9w7ZgAfPscEHYvIJNb9VO/8847WLt2LbKysprcXmLGjBlwc3PDCy+8gOXLl+Onn35CVVUVwsPDsX79etx1111t/hw5OTlYvnw59u/fD5lMhltuuQX/+Mc/EBwcjMOHD+POO+9EVlYW+vbta3nNn//8Zxw/fhyHDx+2ant/jQGIupWyagPSCiuRXlSF9OIqpBdXIzW/AmmFlU3OU8gE1JtFGK69SeeV1zZ5XqdWwN/NETqNAjJBgCAAMkGAod6ME1llSC+uxjuHLuOdQ5fh6dywp0RxlQFiSz9/rCSqvwfmjglAzJC+UCut+0Osrt6EnNIaZJXWIKukoVfm8tVKXL5ahcySatSb/9cwR5Ucfq4a+LlpoFMrIRMaxuwFAYAIFFTUIqukBrllNU1e92sKmQA/Nw0C3R0R6O6IIA9HyAQBl4uqcKmwEpeuVqGoss5yvtZBARfHhqDo7qSyPDycVHDRKCECMNSbUW8WYaw3o7jKgDM55Tibq0e1wYTj6aU4nl7a5q+Hs4MC/m4a+Ltp4OaowuWiKlzI07c7uAW4azBzuB9mjfRFqJe2Xa8larOM+KbDXs2IgD6n4byQaKt+6vvvvx9PPvkkDhw4gDvvvBMAUFpain379uGrr75CZWUlpk6dipdeeglqtRpbt27F9OnTkZKSgsDAwJtev7q6GpMmTUJ0dDQOHz4MhUKBl156Cffccw9OnTqFW2+9Ff369cNHH32EZ599FgBQX1+Pjz/+GH/729+s2tbrMQCR5Ioq6/DtmXx8cyoPP18pRkvvuYIAjAhwxW0D++C2gX0wzN8VRpMZRZV1KK40oLiqDvUmEf5ujvBz08BFc+PdQavq6nEgpRDfnsnHgQuFKKr8X4+RTAA8nB3g4aSCTqOE1kEBrVoBZ7UCKrkc9WYzjCYzDPUN4au6rr5haOdXDweF7H+9Qhol6k0ijmeUIP5SMeIvFUOnVuCucG8IgoCqunpUGepRVVcPg8kMuSBAEATIrgU2syg2hAKTCKPJjHqTGeZrQ3lmc0PNhmtfh9bCW2NvR1FlHaoNJqQVVjYLlS1RygX4uzki1MsZYX21GOitxaC+WoR4OkEpb30NRXmNESazCJ1aAcVNzr0Rk1nEpauVOJ1djoySapRU1aGkyoCiSgOKK+tQazTDLIowmUWYxYavU3mNEZV19biQ39Bj9WsqhQwDvZ0R6O6IOqMZVYZ6VBtMqKpr+LPWaEKN0YRaY8MXN6ukBm8duIi3DlzEEF8dZo/0w13h3gjy4G0OyIoqC6x7Xju4u7vjnnvuwaeffmoJQJ999hnc3d1x5513Qi6XY/jw4ZbzX3rpJfznP//Bnj178Mc//vGm19++fTtkMhm2bNli+T/zwQcfwNXVFQcPHsTkyZOxaNEifPDBB5YA9M0336C6uhoPPPCA1dv7awxA1OWKK+uQkl+B8/kV+OFCAX681DT0+LlqEOzpiGAPJwR7OCHE0wmRQW5wc2p64zu5TA5/N0f4u7VvaMnJQYFpw3wxbZgvao0mnMkph5ODAp7XhlZsMd8ku7Qau5Ky8VliNnLKarD7RI7VP4dGKUeAuwYBbo4IcHdE/z5O6NfHGf36OKGvTg1BEFBrNCG3rAY5ZTXIKa1BlcEEURQt86NEEfB0dkCAuyMC3DXw1qoh6+DXo7UQ2lZymYCB3g3Bq61qDCbklNUgu7QaOWU1KKowINjTEeE+OvTzdGpTGDObRVQa6nEo5Sq+OJGDQ6lXcTZXj7O5erz0zXn4uWowMdQDE0M9MaG/B7y06s40k+yds7d1z2unhx9+GE888QQ2bdoEBwcHfPLJJ5g3bx7kcjmqqqqwZs0afP3115bbT9TU1CAzM7NN105KSsLFixeh1Tb9P1xbW4tLly4BABYuXIjnn38eP/30E8aPH4/Y2Fg88MADcHJysnpbf40BiAA09MIU6GsR1lfXYgCoMZjwRXIOPk/KhgggyMMRQe5OCPZseLNtHMrQqpWW15dUGXCxsNLySCts+I38akVds+sP83fBvUN9MHWoDwLcu26ujFopx+hgd5t/Hn83Ryy7ayCevGMAjl0qQmJ6KdRKOZwdGuehKOCgkMEsijCLaPjTLEIQBCjlAhRyGZTX5h/9ekivsafIx0UNdyfVTXsl1Er5tVDkbPM2S0WjkiPUyxmhXh1vo0wmQKdWYvpwX0wf7ouSKgO+OZ2Hr0/m4pfMUuSU1WBnYjZ2JmYDALy0DpagNtDbGQP7ahHWVwtHFX/EUhsERTWs9tLnoeV5QELD80FRNvn006dPh9lsxjfffIMxY8bgyJEjeP311wEAzz77LPbt24fXXnsNoaGh0Gg0mDNnDgyGm8+1BBpuXhoZGYlPPvmk2XN9+vQBAHh5eWH69On44IMP0K9fP+zduxcHDx60WvtuhP877dyZnHLEHr2Cr07lwmgS4eGkwh1hXrhrsDeiB3iiuNKAj3/KwPbjWSivMVpel5Rx4/kYWgcFZDKhyfnXC3R3xKC+WowKdMO9Q30kmyDc1WQyAdED+iB6QB+pS6F2cHdSYf74IMwfH4RqQz0SrjQMaR67WIRzeXoUVtShsKIORy8WWV4jE4AQTycM9nXBYB8dwny06O/pDD83DVe1UVMyecNS950LAFybjGdx7d/KPX+z+gToRhqNBvfddx8++eQTXLx4EQMHDkRkZCQA4MiRI1i4cCFmz54NAKisrER6enqbrz1q1Cjs2LEDXl5e0Ol0Nzzvsccew7x58+Dv74/+/ftj4sSJnWpTWzAA2SFDvRk/XChA7NF0JKSXWI5rlHIUVxnwWVI2PkvKhoNCBuO1OSdAQ2hZMCEIfV3UyCiuRsa1ScrZJdUoqzGi+toE04q6ess1/Vw1lt/GB3g5Y9C1eSRODvynRz2To0qB2wd54fZBXgCAyrp6XCysRGp+BVIKGlbLnc+rQFFlHS5drcKlq1X46uT/JriqFDIEeziifx9nDPbRITLIDcMDXPl/wt4NntGw1L3FfYD+ZvMl8A8//DCmT5+Os2fP4pFHHrEcDw0Nxe7duzF9+nQIgoDVq1fD3DgBsY3XffXVVzFz5kysXbsW/v7+yMzMxO7du/Hss8/C398fABATEwMXFxe89NJLWLt2rdXb1xL+j7MTmcXVOJR2FYdSruLHS0WW1TAKmYBpw3zw24khGOyrw/ErJdh/rgBx5wqQU1YDALgl1BMLo4IxKcyr1d9cDfVmVNQaoa+tR129CQFujvyhTr2es4MCIwJcMSLAtcnxwopanMvV41xew9yhiwWVuFJcBUO9GakFlUgtqMR/z+QDaJjrFO6jxeggd8yfEIT+vXiIkloxeEbDUveM+IYJz87eDcNeNur5+bU77rgD7u7uSElJwUMPPWQ5/sYbb+B3v/sdoqKi4OnpiRUrVkCv17f5uo6Ojjh8+DBWrFiB++67DxUVFfDz88Odd97ZpEdIJpNh4cKFWLduHRYsWGDVtt2IIIq2XPjbM+n1eri4uKC8vLzVLjspiaKIpIxS1BrNGB3s1uKy6qySanz+Szb2JOficlFVk+c8nVWYNyYQj4xv6NFp6foXCyvhoJDbzfAUka2ZzCJyy2pw8WolLhVW4mR2OZLSS5D7q20ctA4KbHpkFIdJe5ja2lpcuXIFISEhUKs5Kb4jHn/8cRQUFGDPnj2tntfa17o979/89byHKakyYFdSFv6dkIUr10KNg0KG8f08cNvAPpgY6olzeeX4LDEb8ZeKLa9TyASMCnKzLCMf7KNrdXWPIAgY0I6VN0R0c3KZcG2FnSMmXRtCA4DcshokZZRia3w6EjNK8dsPjuPl2RGYO+bm+6wQ9XTl5eU4fvw4PvnkE3z55Zdd9nkZgHoAs1nET1eK8e+ELOw7kw+DqWH81fnaHjV55bU4dG2X5OtF9ffA/aP9cVe4N7Tqzi9LJiLr83XVwNdVg8lDvLFi1yl8kZyLFZ+fRnpxNZ6dPKjDWxEQ9QQzZ85EQkICFi9ejLvvvrvLPi8DUDeWX16LXUlZ2JmYjcySasvxYf4ueGhsIKYP94WjSo60wkocTCnEwZSrOJ5eAm+dGnMi/fGbUf5duqSciDrHQSHHG3NHIMjDCf/4Pg2bD15CZkk11swYAk9nB6nLI7KJrljy3hIGoG7odHY5Xo9LwaHUq5YVWM4OCkwf7ouHxwUiws+lyfmN+488cWt/mMyi5dYGRNTzCIKAp+8eiEB3Rzy3+xS+OZWHb8/k45ZQT8wc4YvJQ/rCmYsLiDqN/4u6EVEU8f7RK3jl2wswmhqSz9hgd8wdE4CpQ32gUd18JQD3FyHqHX4T6Q9/Nw3W7T2Pk9nllmFuB8Vp3BHmhegBfTAx1AOB7rwtR3fCdUW2Z62vMQNQN1FSZcCzn53E9xcKAQAxQ7yx4p6wXr1jLxG1blw/D3z5x1twpagKe5Jz8WVyDi4XVeG/Z/ItS+j9XDWI6u+B+0b5Y0J/D4krtl9KZcMcy+rqamg0Gomr6d0ad6GWyzu3PQCXwbegq5fB/3y5GE9tT0a+vhYqhQyrpw3GI+MC+VsdETUhiiLO5Ojx/YUCxF8qxonMUktvsSAAu5ZEITLITeIq7VdeXh7Kysrg5eUFR0f2zNmC2WxGbm4ulEolAgObv0+25/2bAagFXRmAkjJKcP/bP8IsAv36OOGtB0dhsG/33HuIiLqXakM9EtNL8f7RKziUehUDvZ3x9Z+ioVLc/IavZH2iKCI/Px9lZWVSl9KryWQyhISEQKVSNXuO+wD1IF+fyoNZBKIHeOKd+ZG8eSIRtZmjSoFbB/bBUD8X3PX6IaQWVOKdQ5fwpzsHSF2aXRIEAT4+PvDy8oLReON7IVLnqFQqyGSdD/l8t5VYclYZAOC+UX4MP0TUIW5OKrwwfTCe2p6Mf/1wEVOH+fB2GhKSy+Wdnp9Ctsd+UgkZ6s04m9twT5URARy3J6KOmzHcF7cP6gODyYyVu0/DbObsBqLWMABJ6EK+HoZ6M1wdlQjm/baIqBMEQcBfZ0ZAo5Qj4UoJdiRmSV0SUbfGACShxuGv4f6uXC1ARJ0W4O6IP08eCABYt/c8CvW1N3kFkf1iAJJQcmYZAGBEgKukdRBR77EwKhhD/VxQUVuPFZ+fgqHeLHVJRN0SA5CEGnuARgS6SloHEfUeCrkMf/vNUCjlAg6kXMXijxJRazRJXRZRt8MAJJHyaiMuF1UBaBgCIyKyliG+LnhvwWiolTIcSLmKR2MTUFHLZdlEv8YAJJHk7DIAQJCHI9ydmm/mRETUGbcP8sK2342Ds4MCP18pwSNbfkZplUHqsoi6DQYgiZxsHP7i/B8ispGxIe749PFxcHNU4mR2Oea9+xMnRhNdwwAkkWQGICLqAsP8XbFz8QR4aR2QUlCBx7clcmI0ERiAJCGKIgMQEXWZAd5afLZkAnRqBU5ml+P1uFSpSyKSnOQBaNOmTQgJCYFarUZkZCSOHDnS6vkbN25EeHg4NBoNBg0ahG3btjV5/vbbb4cgCM0e9957ry2b0S5ZJTUoqTJAKRd441Mi6hJBHk545TfDAADvHL6EYxeLJK6ISFqSBqAdO3Zg2bJlWLVqFU6cOIHo6GhMmTIFmZmZLZ6/efNmrFy5Ei+++CLOnj2LNWvWYOnSpfjqq68s5+zevRt5eXmWx5kzZyCXy3H//fd3VbNu6kRWKQBgsI8ODgreL4aIusaUoT54cGwgRBF4ekcyiivrpC6JSDKSBqDXX38dixYtwmOPPYbw8HC8+eabCAgIwObNm1s8/6OPPsLixYsxd+5c9OvXD/PmzcOiRYvwyiuvWM5xd3dH3759LY+4uDg4Ojp2qwDE4S8iksoL0wYj1MsZhRV1eHbXKYgi7xlG9kmyAGQwGJCUlITJkyc3OT558mTEx8e3+Jq6ujqo1eomxzQaDRISEmA0trzHxfvvv4958+bBycnphrXU1dVBr9c3edgSN0AkIqloVHL868GRUClk+OFCIbbGp0tdEpEkJAtARUVFMJlM8Pb2bnLc29sb+fn5Lb4mJiYGW7ZsQVJSEkRRRGJiImJjY2E0GlFU1Hw8OyEhAWfOnMFjjz3Wai3r16+Hi4uL5REQENDxht0E7wBPRFIL99Fh1dRwAMC6vRdwId+2v/QRdUeST4K+/iagoije8Magq1evxpQpUzB+/HgolUrMnDkTCxcuBADI5c3n0rz//vuIiIjA2LFjW61h5cqVKC8vtzyysmx3F2XeAZ6IuoMFE4JwZ5gXDCYzNh24JHU5RF1OsgDk6ekJuVzerLensLCwWa9QI41Gg9jYWFRXVyM9PR2ZmZkIDg6GVquFp6dnk3Orq6uxffv2m/b+AICDgwN0Ol2Th63wDvBE1B0IgoCn7264c/x/z+ThagUnRJN9kSwAqVQqREZGIi4ursnxuLg4REVFtfpapVIJf39/yOVybN++HdOmTYNM1rQpO3fuRF1dHR555BGr194ZjXeAH84J0EQksQg/F4wIcIXRJGJnou16vom6I0mHwJYvX44tW7YgNjYW58+fx9NPP43MzEwsWbIEQMPQ1IIFCyznp6am4uOPP0ZaWhoSEhIwb948nDlzBuvWrWt27ffffx+zZs2Ch4dHl7WnLRp7gEYyABFRN/DI+CAAwKc/Z8Jk5oowsh8KKT/53LlzUVxcjLVr1yIvLw8RERHYu3cvgoIa/kPm5eU12RPIZDJhw4YNSElJgVKpxKRJkxAfH4/g4OAm101NTcXRo0exf//+rmzOTTW5AzwDEBF1A9OG+eCvX59DTlkNDqUW4o6wlqcgEPU2gshNIJrR6/VwcXFBeXm5VecDHUq9ikdjExDk4YhDz06y2nWJiDrjpa/PYcvRK7gjzAuxC8dIXQ5Rh7Xn/VvyVWD2JMJXhzfnjsCf7hggdSlERBYPXxsGO5BSiKySaomrIeoaDEBdyMPZAbNG+mFOpL/UpRARWYR4OuGWUE+IIvDvhJZvRUTU2zAAERERHhkfCADYmZgFQ71Z4mqIbI8BiIiIcFe4N7x1DiiqNODbsy3vxk/UmzAAERERFHIZHhzb0Av08Y8ZEldDZHsMQEREBACYNyYQcpmAhPQSHLvY/P6KRL0JAxAREQEA+rqo8ZtRfgCAxR8l4UxOucQVEdkOAxAREVmsnRmB8f3cUVlXj0djE3D5aqXUJRHZBAMQERFZqJVyvLdgNCL8dCiuMmD++wnIL6+Vuiwiq2MAIiKiJrRqJT787Vj083RCTlkN5r//M8qqDVKXRWRVDEBERNSMp7MDti0ai746NdIKK/G7D49zfyDqVRiAiIioRf5ujvho0Vi4aJT4JbMM//ohTeqSiKyGAYiIiG5ogLcW62YPBQBsOngJyVll0hZEZCUMQERE1Kp7h/lgxnBfmMwilu9MRq3RJHVJRJ3GAERERDe1duYQeGkdcPlqFV759oLU5RB1GgMQERHdlKujCq/MGQYA+OBYOuIvcado6tkYgIiIqE0mDfKy3C/s2c9OQV9rlLgioo5jACIiojZ7/t5wBLo7IqesBi99fU7qcog6jAGIiIjazMlBgdfuHw5BAHYmZiPhSonUJRF1CAMQERG1y9gQd8wbEwAAWP3FGRhN3CCReh4GICIiare/xITBzVGJlIIKbI1Pl7oconZjACIionZzc1Jh5ZRwAMAbcam8YSr1OAxARETUIXMi/TEq0BVVBhP++g0nRFPPwgBEREQdIpMJeGnWUMgE4JtTeTicelXqkojajAGIiIg6bLCvDo9GBQMA/m/PWdTV8zYZ1DMwABERUacsv3sgvLQOuFJUhfePXpG6HKI2YQAiIqJO0aqVWHFPGABgW3wG6rksnnoABiAiIuq0acN94O6kQr6+Foc4F4h6AAYgIiLqNAeFHL8Z5QcA+HdClsTVEN0cAxAREVnF3DENN0o9kFKIAj33BaLujQGIiIisItTLGWOC3WAyi/gskb1A1L0xABERkdXMu9YLtCMxC2azKHE1RDfGAERERFYzdagPtGoFskpqcOxSkdTlEN0QAxAREVmNRiXH7JENk6G3czI0dWMMQEREZFWNw2D7z+WjuLJO4mqIWsYAREREVjXYV4fh/i4wmkR8/ku21OUQtYgBiIiIrG7e2IZeoO3HsyCKnAxN3Q8DEBERWd304b5wVMlx+WoVjl0slrocomYYgIiIyOqcHRSYdW0y9LIdJ5BZXC1xRURNMQAREZFNrJwShnAfHYoqDVgQ+zOKOCGauhEGICIisgmtWomtvx0DfzcN0oursejD46iqq5e6LCIADEBERGRDXjo1tv1uLNwclTiZXY4/fPILjCaz1GURMQAREZFt9evjjNiFY6BRynEo9Sqe+/w0V4aR5BiAiIjI5kYGumHjwyMhlwn4/JdsfHUqT+qSyM4xABERUZe4I8wbT905AADw2r4UGOo5FEbSYQAiIqIu81h0CPpoHZBZUo1Pf86QuhyyYwxARETUZRxVCiy7q6EX6J8/XERFrVHiisheMQAREVGXmjs6AP08nVBSZcCWQ2nAlSPA6V0Nf5pNUpdHdkIhdQFERGRfFHIZ/nLPIPzn07cxL/6PwI8l/3tS5wvc8woweIZ0BZJdYA8QERF1uRhZAt5WvQlvlDR9Qp8H7FwAnNsjTWFkNxiAiIioa5lNEL59DgAgE65/8tr+QN8+x+EwsikGICIi6loZ8YA+F82yj4UI6HMaziOyEQYgIiLqWpUF1j2PqAMYgIiIqGs5e1v3PKIOYAAiIqKuFRTVsNrrBoNgIgRA59dwHpGNMAAREVHXkskblroDuD4EmUUAEFF718sN5xHZiOQBaNOmTQgJCYFarUZkZCSOHDnS6vkbN25EeHg4NBoNBg0ahG3btjU7p6ysDEuXLoWPjw/UajXCw8Oxd+9eWzWBiIjaa/AM4IFtgM6nyeFCwQNLDMuw7GQgzGbeMZ5sR9KNEHfs2IFly5Zh06ZNmDhxIt555x1MmTIF586dQ2BgYLPzN2/ejJUrV+K9997DmDFjkJCQgMcffxxubm6YPn06AMBgMODuu++Gl5cXdu3aBX9/f2RlZUGr1XZ184iIqDWDZwBh9zas9qosAJy9kYMwHNiSCMPZfGw8cBF/unbzVCJrE0RRlCxijxs3DqNGjcLmzZstx8LDwzFr1iysX7++2flRUVGYOHEiXn31VcuxZcuWITExEUePHgUAvP3223j11Vdx4cIFKJXKDtWl1+vh4uKC8vJy6HS6Dl2DiIg6ZsfxTKz4/DR0agV+WX03FHLJByuoh2jP+7dk/6oMBgOSkpIwefLkJscnT56M+PiW936oq6uDWq1uckyj0SAhIQFGY8MN9fbs2YMJEyZg6dKl8Pb2RkREBNatWweT6cYbatXV1UGv1zd5EBGRNOZEBsBFo4S+th4ns8ulLod6KckCUFFREUwmE7y9my5z9Pb2Rn5+fouviYmJwZYtW5CUlARRFJGYmIjY2FgYjUYUFRUBAC5fvoxdu3bBZDJh7969eP7557Fhwwa8/PLLN6xl/fr1cHFxsTwCAgKs11AiImoXuUzALaGeAIDDqVclroZ6K8n7FQWh6QoAURSbHWu0evVqTJkyBePHj4dSqcTMmTOxcOFCAIBc3rBawGw2w8vLC++++y4iIyMxb948rFq1qskw2/VWrlyJ8vJyyyMrK8s6jSMiog6JHnAtAKUxAJFtSBaAPD09IZfLm/X2FBYWNusVaqTRaBAbG4vq6mqkp6cjMzMTwcHB0Gq18PRs+M/i4+ODgQMHWgIR0DCvKD8/HwaDocXrOjg4QKfTNXkQEZF0bh3YBwBwMqsM5dVGiauh3kiyAKRSqRAZGYm4uLgmx+Pi4hAV1frmV0qlEv7+/pDL5di+fTumTZsGmayhKRMnTsTFixdhNpst56empsLHxwcqlcr6DSEiIqvzddUg1MsZZhE4dqlI6nKoF5J0CGz58uXYsmULYmNjcf78eTz99NPIzMzEkiVLADQMTS1YsMByfmpqKj7++GOkpaUhISEB8+bNw5kzZ7Bu3TrLOb///e9RXFyMp556Cqmpqfjmm2+wbt06LF26tMvbR0REHXfrgIZeIM4DIluQdB+guXPnori4GGvXrkVeXh4iIiKwd+9eBAUFAQDy8vKQmZlpOd9kMmHDhg1ISUmBUqnEpEmTEB8fj+DgYMs5AQEB2L9/P55++mkMGzYMfn5+eOqpp7BixYqubh4REXXCrQM9EXvsCg6nXm11fihRR0i6D1B3xX2AiIikV2MwYfja/TDUm/Hd8lsR6sUNbal1PWIfICIiotZoVHKMDXYHABxK5Twgsi4GICIi6rZuHcj9gMg2GICIiKjbalwO//OVYtQab7yjP1F7MQAREVG3NchbCy+tA2qNZiSml0pdDvUiDEBERNRtCYKA6Mbl8NwVmqyIAYiIiLo1zgMiW2AAIiKibi16QB8IAnAhvwIF+lqpy6FeggGIiIi6NXcnFYb6uQAAjqRxOTxZBwMQERF1e423xdh3Nv8mZxK1DQMQERF1ezNG+AIAvj9fgNyyGomrod6AAYiIiLq9gd5ajAtxh1kEPv058+YvILoJBiAiIuoRHo0KBgBsP56JunpuikidwwBEREQ9wt2DveGtc0BRpQHfnuFcIOocBiAiIuoRlHIZHhobBADY9mOGxNVQT8cAREREPcaDYwOgkAlIyijFmZxyqcuhHowBiIiIegwvnRpThvoAAD5iLxB1AgMQERH1KAsmNAyDfXkyB+XVRomroZ6KAYiIiHqU0UFuCOurRa3RjM+SsqQuh3ooBiAiIupRBEHAggnBAICPfsqA2SxKWxD1SAxARETU48wa6QutWoGM4mocucj7g1H7MQAREVGP46hSYNqwhsnQ8ZcYgKj9GICIiKhHGuLbcIf4C3kVEldCPREDEBER9UjhPloAQEo+AxC1HwMQERH1SAO9GwJQvr4WpVUGiauhnoYBiIiIeiStWokAdw0A4AJ7gaidGICIiKjHCuurAwBcyNdLXAn1NAxARETUY4X3bRgG40Roai8GICIi6rHCfNgDRB3DAERERD1W2LUeoJSCCpi4IzS1AwMQERH1WEEeTlArZag1mpFRXCV1OdSDMAAREVGPJZcJGHRtOTxXglF7MAAREVGPZlkJlsd5QNR2DEBERNSjhV3bEfo8e4CoHRiAiIioR+NeQNQRDEBERNSjNa4EyyqpQUWtUeJqqKdgACIioh7NzUmFvjo1ACC1gMNg1DYMQERE1ONZ5gFxR2hqIwYgIiLq8TgPiNqLAYiIiHq88Gs9QClcCUZtxABEREQ93v/2AqqAKPKWGHRzDEBERNTj9evjBKVcQEVdPXLKaqQuh3oABiAiIurxlHIZQr2u3RKDE6GpDRiAiIioVwjv23hPME6EpptjACIiol6Bt8Sg9mAAIiKiXoE3RaX2YAAiIqJeobEH6EpRFWqNJomroe6OAYiIiHqFPs4O8HBSwSwCZ3PZC0StYwAiIqJeQRAETOjvAQD46mSuxNVQd8cAREREvcacSH8AwBfJOair5zAY3RgDEBER9RrRA/rAW+eAsmojDlwolLoc6sY6FICysrKQnZ1t+TghIQHLli3Du+++a7XCiIiI2ksuE3DfqIZeoM8Ss29yNtmzDgWghx56CAcOHAAA5Ofn4+6770ZCQgL+3//7f1i7dq1VCyQiImqPxmGwg6lXUVhRK3E11F11KACdOXMGY8eOBQDs3LkTERERiI+Px6effooPP/zQmvURERG1S/8+zhgV6AqTWcSXJzgZmlrWoQBkNBrh4OAAAPjuu+8wY8YMAEBYWBjy8vKsVx0REVEHzIkMAADsSsrm3eGpRR0KQEOGDMHbb7+NI0eOIC4uDvfccw8AIDc3Fx4eHlYtkIiIqL3uHeYDB4UMKQUVOJ1TLnU51A11KAC98soreOedd3D77bfjwQcfxPDhwwEAe/bssQyNERERScVFo0TMkL4AGnqBiK4niB3sGzSZTNDr9XBzc7McS09Ph6OjI7y8vKxWoBT0ej1cXFxQXl4OnU4ndTlERNQBR9KuYv77CXDRKJGw6k44KORSl0Q21p737w71ANXU1KCurs4SfjIyMvDmm28iJSWl3eFn06ZNCAkJgVqtRmRkJI4cOdLq+Rs3bkR4eDg0Gg0GDRqEbdu2NXn+ww8/hCAIzR61tVwJQERkT6L6e8LHRY3yGiO+O8c9gaipDgWgmTNnWoJHWVkZxo0bhw0bNmDWrFnYvHlzm6+zY8cOLFu2DKtWrcKJEycQHR2NKVOmIDMzs8XzN2/ejJUrV+LFF1/E2bNnsWbNGixduhRfffVVk/N0Oh3y8vKaPNRqdUeaSkREPVTDnkB+AIBdSVkSV0PdTYcC0C+//ILo6GgAwK5du+Dt7Y2MjAxs27YN//znP9t8nddffx2LFi3CY489hvDwcLz55psICAi4YYj66KOPsHjxYsydOxf9+vXDvHnzsGjRIrzyyitNzhMEAX379m3yICIi+9O4Guxg6lUkppdIXA11Jx0KQNXV1dBqtQCA/fv347777oNMJsP48eORkZHRpmsYDAYkJSVh8uTJTY5PnjwZ8fHxLb6mrq6uWU+ORqNBQkICjEaj5VhlZSWCgoLg7++PadOm4cSJE63WUldXB71e3+RBREQ9X4inE34zyh+iCCzfeRKVdfVSl0TdRIcCUGhoKL744gtkZWVh3759lhBTWFjY5knDRUVFMJlM8Pb2bnLc29sb+fn5Lb4mJiYGW7ZsQVJSEkRRRGJiImJjY2E0GlFUVASgYS+iDz/8EHv27MG///1vqNVqTJw4EWlpaTesZf369XBxcbE8AgIC2tQGIiLq/v5vxmD4uWqQWVKNl74+J3U51E10KAC98MILeOaZZxAcHIyxY8diwoQJABp6g0aOHNmuawmC0ORjURSbHWu0evVqTJkyBePHj4dSqcTMmTOxcOFCAIBc3jC7f/z48XjkkUcwfPhwREdHY+fOnRg4cCD+9a9/3bCGlStXory83PLIyuJYMRFRb6FTK7HhgeEQBGD78SzEnSuQuiTqBjoUgObMmYPMzEwkJiZi3759luN33nkn3njjjTZdw9PTE3K5vFlvT2FhYbNeoUYajQaxsbGorq5Geno6MjMzERwcDK1WC09PzxZfI5PJMGbMmFZ7gBwcHKDT6Zo8iIio9xjfzwOPR/cDADz3+SkUVdZJXBFJrUMBCAD69u2LkSNHIjc3Fzk5OQCAsWPHIiwsrE2vV6lUiIyMRFxcXJPjcXFxiIqKavW1SqUS/v7+kMvl2L59O6ZNmwaZrOWmiKKI5ORk+Pj4tKkuIiLqnf48eSDC+mpRXGXAyt2neYsMO9ehAGQ2m7F27Vq4uLggKCgIgYGBcHV1xV//+leYzeY2X2f58uXYsmULYmNjcf78eTz99NPIzMzEkiVLADQMTS1YsMByfmpqKj7++GOkpaUhISEB8+bNw5kzZ7Bu3TrLOWvWrMG+fftw+fJlJCcnY9GiRUhOTrZck4iI7JODQo435o6ASi5D3LkCfJbIHaLtmaIjL1q1ahXef/99/O1vf8PEiRMhiiKOHTuGF198EbW1tXj55ZfbdJ25c+eiuLgYa9euRV5eHiIiIrB3714EBQUBAPLy8prsCWQymbBhwwakpKRAqVRi0qRJiI+PR3BwsOWcsrIyPPHEE8jPz4eLiwtGjhyJw4cP8xYdRESEcB8dnr57IF759gLeO3IZD4zhohd71aFbYfj6+uLtt9+23AW+0Zdffok//OEPliGxnoq3wiAi6r0yiqtw26sHoVbKcH7tPTdceEM9j81vhVFSUtLiXJ+wsDCUlHCjKSIi6r76uqghCECt0YziKoPU5ZBEOhSAhg8fjrfeeqvZ8bfeegvDhg3rdFFERES24qCQo4+zAwAgt6xG4mpIKh2aA/T3v/8d9957L7777jtMmDABgiAgPj4eWVlZ2Lt3r7VrJCIisio/Nw0KK+qQU1qDYf6uUpdDEuhQD9Btt92G1NRUzJ49G2VlZSgpKcF9992Hs2fP4oMPPrB2jURERFbl66oBAOSwB8hudagHCGiYCH39aq+TJ09i69atiI2N7XRhREREtuLPAGT3OrwRIhERUU/l59YQgDgHyH4xABERkd3xdWEPkL1jACIiIrvzvx6gWokrIam0aw7Qfffd1+rzZWVlnamFiIioSzROgi6pMqDaUA9HVYenxFIP1a7vuIuLy02f//W9u4iIiLojF40SWgcFKurqkVtWg1AvrdQlURdrVwDiEnciIuot/Nw0uJBfgZyyWgYgO8Q5QEREZJcsewGVciK0PWIAIiIiu+TnyqXw9owBiIiI7BJ3g7ZvDEBERGSXGpfCMwDZJwYgIiKyS36uagCcA2SvGICIiMgu+bk6AgDy9bUwmUWJq6GuxgBERER2yUvrAKVcgMksokDPHaHtDQMQERHZJZlMQF+Xa8NgnAdkdxiAiIjIbnEpvP1iACIiIrvVuBQ+mxOh7Q4DEBER2S1/9gDZLQYgIiKyW9wLyH4xABERkd3yZQ+Q3WIAIiIiu+X3qxuiiiL3ArInDEBERGS3GnuAqgwm6GvqJa6GuhIDEBER2S21Ug5PZxUAILusWuJqqCsxABERkV3z/dUwGNkPBiAiIrJr3AzRPjEAERGRXbNMhGYAsisMQEREZNf+txSeN0S1JwxARERk1xo3Q8xmD5BdYQAiIiK7xjlA9okBiIiI7FpjALpaUYdao0niaqirMAAREZFdc3VUwlElBwDklXMekL1gACIiIrsmCALvCWaHGICIiMju+XEzRLvDAERERHbPl3sB2R0GICIisnv+15bCH08v4V3h7QQDEBER2b17h/pAJZch/lIxvjtfKHU51AUYgIiIyO4FezphUXQIAOCvX5/jcng7wABEREQE4I+TQtFXp0ZmSTXeO3xZ6nLIxhiAiIiIADg5KPD/7g0HAGw8eBHZpdUSV0S2xABERER0zfRhPhgX4o5aoxnr9p6XuhyyIQYgIiKiawRBwIszhkAmAHtP5+PYxSKpSyIbYQAiIiL6lXAfHRZMCAYA/N+eszCazNIWRDbBAERERHSdp+8aCHcnFS4WVuLL5FypyyEbYAAiIiK6joujEg+NDQQAxHMYrFdiACIiImrB2BB3AMDxjBKJKyFbYAAiIiJqwchAV8gEIKukBvnltVKXQ1bGAERERNQCrVqJwb46AA33CKPehQGIiIjoBkYHXRsGYwDqdRiAiIiIbsAyDyi9VOJKyNoYgIiIiG5gdLAbAOBCvh7lNUaJqyFrYgAiIiK6AS+tGsEejhBF4JdM9gL1JgxARERErRgdfG0Y7ArnAfUmDEBEREStGHstACVyHlCvInkA2rRpE0JCQqBWqxEZGYkjR460ev7GjRsRHh4OjUaDQYMGYdu2bTc8d/v27RAEAbNmzbJy1UREZC8a5wElZ5ehrt4kcTVkLZIGoB07dmDZsmVYtWoVTpw4gejoaEyZMgWZmZktnr9582asXLkSL774Is6ePYs1a9Zg6dKl+Oqrr5qdm5GRgWeeeQbR0dG2bgYREfViIZ5O8HRWwVBvxunscqnLISuRNAC9/vrrWLRoER577DGEh4fjzTffREBAADZv3tzi+R999BEWL16MuXPnol+/fpg3bx4WLVqEV155pcl5JpMJDz/8MNasWYN+/fp1RVOIiKiXEgThV/sBcRist5AsABkMBiQlJWHy5MlNjk+ePBnx8fEtvqaurg5qtbrJMY1Gg4SEBBiN/1ueuHbtWvTp0weLFi1qUy11dXXQ6/VNHkRERI3GhHBDxN5GsgBUVFQEk8kEb2/vJse9vb2Rn5/f4mtiYmKwZcsWJCUlQRRFJCYmIjY2FkajEUVFDXfrPXbsGN5//3289957ba5l/fr1cHFxsTwCAgI63jAiIup1xlybB5SYXgKzWZS4GrIGySdBC4LQ5GNRFJsda7R69WpMmTIF48ePh1KpxMyZM7Fw4UIAgFwuR0VFBR555BG899578PT0bHMNK1euRHl5ueWRlZXV4fYQEVHvM9hHB0eVHPraeqQWVkhdDlmBZAHI09MTcrm8WW9PYWFhs16hRhqNBrGxsaiurkZ6ejoyMzMRHBwMrVYLT09PXLp0Cenp6Zg+fToUCgUUCgW2bduGPXv2QKFQ4NKlSy1e18HBATqdrsmDiIiokUIuw6jAhl4gzgPqHSQLQCqVCpGRkYiLi2tyPC4uDlFRUa2+VqlUwt/fH3K5HNu3b8e0adMgk8kQFhaG06dPIzk52fKYMWMGJk2ahOTkZA5tERFRh43hhoi9ikLKT758+XLMnz8fo0ePxoQJE/Duu+8iMzMTS5YsAdAwNJWTk2PZ6yc1NRUJCQkYN24cSktL8frrr+PMmTPYunUrAECtViMiIqLJ53B1dQWAZseJiIja49fzgKjnkzQAzZ07F8XFxVi7di3y8vIQERGBvXv3IigoCACQl5fXZE8gk8mEDRs2ICUlBUqlEpMmTUJ8fDyCg4MlagEREdmLEYGuUMgE5JbXYv1/z+ORcUEIcHeUuizqIEEURU5nv45er4eLiwvKy8s5H4iIiCwe35aIuHMFAABBAO4Y5IVHJgThtgF9IJO1vICHuk573r8ZgFrAAERERC2pN5nx3flCfPxTBo5eLLIcHxPshn8/Ph4KueSLq+1ae96/+Z0iIiJqI4Vchnsi+uLjx8bhhz/fhkW3hMBRJcfx9FJ8mZwrdXnUDgxAREREHdCvjzNWTxuMP90xAACw8cBFmLhJYo/BAERERNQJ8ycEwdVRictFVfj6FHuBegoGICIiok5wdlBg0cQQAMBbP1zkrTJ6CAYgIiKiTnp0YjC0agXSCivx7dmW72dJ3QsDEBERUSfp1Er89lov0D+/T2MvUA/AAERERGQFv5sYDCeVHBfyK/Dd+QKpy6GbYAAiIiKyAldHFR6NCgYA/POHNHCbve6NAYiIiMhKFt0SAo1SjjM5ehxMuSp1OdQKBiAiIiIr8XB2wPwJDfezfPvQJYmrodYwABEREVnRgmsB6Hh6CcqrjRJXQzfCAERERGRF/m6OCPVyhllEk/uFUffCAERERGRltw/sAwA4mFIocSV0IwxAREREVnbboIYAdCj1KleDdVMMQERERFY2JtgdGqUchRV1uJBfIXU51AIGICIiIitTK+WY0N8DQEMvEHU/DEBEREQ2cBvnAXVrDEBEREQ20BiAEtNLUVlXL3E1dD0GICIiIhsI9nRCsIcj6s0i4rkcvtthACIiIrKRxl4gzgPqfhiAiIiIbITL4bsvBiAiIiIbGd/PAyqFDNmlNbh0tUrqcuhXGICIiIhsxFGlwLgQdwAcButuGICIiIhsiPOAuicGICIiIhtqDEA/Xy5GrdEkcTXUiAGIiIjIhkK9nOHnqkFdvRk/Xi6Wuhy6hgGIiIjIhgRBwK3XeoH+80uOxNVQIwYgIiIiG3tgtD8EAdhzMhdx5wqkLofAAERERGRzIwPd8ER0PwDAyt2nUFxZJ3FFxABERETUBZ6+eyAGejujqNKA5784w40RJcYARERE1AXUSjlef2AEFDIB/z2Tjy+Tc6Uuya4xABEREXWRCD8XPHnnAADAC1+eQX55rcQV2S8GICIioi70h9v7Y7i/C/S19fjL56c4FCYRBiAiIqIupJDLsOGB4VApZDicehV7TnIoTAoMQERERF0s1EuLpbeHAgC2HLnCXiAJMAARERFJYP6EIDgoZDidU46kjFKpy7E7DEBEREQScHdSYdYIPwBA7LErEldjfxiAiIiIJPLbW4IBAPvOFiCnrEbaYuwMAxAREZFEwvrqENXfAyaziG0/pktdjl1hACIiIpLQ7yaGAAD+/XMmqg31EldjPxiAiIiIJHRHmBeCPByhr63Hbt4tvsswABEREUlIJhPw6IRgAMAHx67AbOaS+K7AAERERCSx+0f7w9lBgUtXq3DkYpHU5dgFBiAiIiKJadVK3D/aH0BDLxDZHgMQERFRN7AwKhiCABxMuYoX95xFeY1R6pJ6NQYgIiKibiDIwwmLrq0I+zA+HZNeO4jtCZkwcU6QTTAAERERdRPPTxuMjxeNQ6iXM0qqDHhu92nM2ngMJzJ5qwxrYwAiIiLqRm4Z4In/PhWN1dMGQ+ugwOmccvxmczzeiEtFvcksdXm9BgMQERFRN6OUy7DolhD88MztmDXCF2YR+Mf3aZj77k/IKqmWurxegQGIiIiom+qjdcCb80biH/NGQOugQFJGKab+4wj2nMyVurQeTxBFkbOrrqPX6+Hi4oLy8nLodDqpyyEiIkJWSTWe3H4CJzLLAABDfHUY7KPDoL5ahPvoEOLphOJKA9KLq5BRXIX04moUV9bBW6eGn6sGfm4a+LpqMNBbC3cnlbSNsZH2vH8zALWAAYiIiLqjepMZ//w+DW8duIiOLg5TyWX4/e398YdJ/eGgkFu3QIkxAHUSAxAREXVnuWU1OJVdhvN5FUjJr8CFfD0ySqrh4eSAYA9HBHk4IdjDER7ODiisqEVOaQ1yy2uQWVKNrJIaAEC/Pk5YN3soxvfzkLg11sMA1EkMQERE1NOYzSJkMqHVc0RRxDen87Dmq3O4WlEHAJg7OgArp4bB1bHnD4u15/2bk6CJiIh6gZuFHwAQBAHThvniu+W34aFxgQCAHYlZmLnxGKrq6m1dYrcieQDatGkTQkJCoFarERkZiSNHjrR6/saNGxEeHg6NRoNBgwZh27ZtTZ7fvXs3Ro8eDVdXVzg5OWHEiBH46KOPbNkEIiKiHsVFo8S62UOxa8kE+LiokVFcjQ37U6Uuq0tJGoB27NiBZcuWYdWqVThx4gSio6MxZcoUZGZmtnj+5s2bsXLlSrz44os4e/Ys1qxZg6VLl+Krr76ynOPu7o5Vq1bhxx9/xKlTp/Db3/4Wv/3tb7Fv376uahYREVGPMDrYHevvGwoA+DD+Ck5nl0tcUdeRdA7QuHHjMGrUKGzevNlyLDw8HLNmzcL69eubnR8VFYWJEyfi1VdftRxbtmwZEhMTcfTo0Rt+nlGjRuHee+/FX//61zbVxTlARERkT5789wnsOZmLIb46fLl0IhRyyQeIOqRHzAEyGAxISkrC5MmTmxyfPHky4uPjW3xNXV0d1Gp1k2MajQYJCQkwGpvfNVcURXz//fdISUnBrbfeesNa6urqoNfrmzyIiIjsxeppg6FTK3A2V48P49OlLqdLSBaAioqKYDKZ4O3t3eS4t7c38vPzW3xNTEwMtmzZgqSkJIiiiMTERMTGxsJoNKKoqMhyXnl5OZydnaFSqXDvvffiX//6F+6+++4b1rJ+/Xq4uLhYHgEBAdZpJBERUQ/QR+uAVfeGAwA27E+1i9ttSN7HJQhNZ62LotjsWKPVq1djypQpGD9+PJRKJWbOnImFCxcCAOTy/23mpNVqkZycjOPHj+Pll1/G8uXLcfDgwRvWsHLlSpSXl1seWVlZnW4XERFRT/LA6ACMDXFHjdGEF748g96+S45kAcjT0xNyubxZb09hYWGzXqFGGo0GsbGxqK6uRnp6OjIzMxEcHAytVgtPT0/LeTKZDKGhoRgxYgT+/Oc/Y86cOS3OKWrk4OAAnU7X5EFERGRPBEHAutlDoZLLcCDlKr45nSd1STYlWQBSqVSIjIxEXFxck+NxcXGIiopq9bVKpRL+/v6Qy+XYvn07pk2bBpnsxk0RRRF1dXVWqZuIiKi3CvVyxh8m9QcAvLYvBeaO3m+jB1BI+cmXL1+O+fPnY/To0ZgwYQLeffddZGZmYsmSJQAahqZycnIse/2kpqYiISEB48aNQ2lpKV5//XWcOXMGW7dutVxz/fr1GD16NPr37w+DwYC9e/di27ZtTVaaERERUcueuLUf3j9yBenF1fjxcjEmhnre/EU9kKQBaO7cuSguLsbatWuRl5eHiIgI7N27F0FBQQCAvLy8JnsCmUwmbNiwASkpKVAqlZg0aRLi4+MRHBxsOaeqqgp/+MMfkJ2dDY1Gg7CwMHz88ceYO3duVzePiIiox3FUKTBrpB8++ikDn/6c2WsDEO8F1gLuA0RERPbsXK4eU/95BAqZgB9X3ok+WgepS2qTHrEPEBEREXVPg311GBHginqziF1J2VKXYxMMQERERNRM481Stx/P7JWToRmAiIiIqJlpw3ygdVAgo7ga8ZeKpS7H6hiAiIiIqBlHlQKzR/kBAD5NyJC4GuuTdBUYERERdV8Pjg3Eth8zsP9sAa5W1LU6GVoURZzN1eN8nh7lNUboa4wNf9bW45ZQT/wm0r8LK785BiAiIiJqUbiPDiMDXXEiswyfJWXhD7eHNnm+3mRGQnoJ9p8twP6z+cgtr23xOl+dzMU9EX3h5NB9Ykf3qYSIiIi6nQfHBuJEZhm2J2Rhya39ka+vxdG0Ihy9WIQjaVdRWm20nKtRyhEZ5AZ3JxV0GgVcNErsOJ6FokoDTmaVIaob7SnEAEREREQ3NH2YL/769TlkllQj+u8HkFNW0+R5N0cl7gz3RsyQvoge4Am1Ut7k+cySGnx1MheJGaUMQERERNQzaFRy3DfSD1t/zEBOWQ1kAjDM3xXRAzwxMdQTo4PcoJDfeE3V6CA3fHUyF0kZpV1Y9c0xABEREVGrnokZBB9XDYI9nDChvwdcNMo2vzYyyA0A8EtmKcxmETKZYKsy24UBiIiIiFqlVSux5Lb+HXptWF8tHFVyVNTWI7WwAmF9u8ctprgPEBEREdmMQi7DyEBXAOhWw2AMQERERGRTkYENw2BJ6QxAREREZCcig90BAInsASIiIiJ7MTLQFYIAZJZUo7Ci5c0SuxoDEBEREdmUTq3EIG8tAOCXbtILxABERERENte4HD6xm8wDYgAiIiIimxsdfG0idCYDEBEREdmJyMCGidBncspRazRJXA0DEBEREXWBAHcN+mgdYDSJOJVdLnU5DEBERERke4Ig/G8/oG4wEZoBiIiIiLqEZR5QRonElTAAERERURdpXAmWlFEKURQlrYUBiIiIiLrEEF8XOChkKK024nJRlaS1MAARERFRl1ApZBju7wpA+vuCMQARERFRl4m8Ng8oUeJ5QAxARERE1GW6y0owhaSfnYiIiOzK6GA3PH9vuGVCtFQYgIiIiKjLuDqq8Fh0P6nL4BAYERER2R8GICIiIrI7DEBERERkdxiAiIiIyO4wABEREZHdYQAiIiIiu8MARERERHaHAYiIiIjsDgMQERER2R0GICIiIrI7DEBERERkdxiAiIiIyO4wABEREZHd4d3gWyCKIgBAr9dLXAkRERG1VeP7duP7eGsYgFpQUVEBAAgICJC4EiIiImqviooKuLi4tHqOILYlJtkZs9mM3NxcaLVaCIJgOT5mzBgcP368ybnXH/v1xy39Xa/XIyAgAFlZWdDpdJ2qs6V6OnLejZ5vrW03+5jtZXvbi+3t2Hlsb8vH2d7e0972vPeKooiKigr4+vpCJmt9lg97gFogk8ng7+/f7LhcLm/2j+T6Y7/++EZ/BwCdTtfpf3At1dOR8270fGttu9nHbC/b215sb8fOY3tbPs729p72tve992Y9P404Cbodli5detNjv/74Rn+3ZT0dOe9Gz7fWtpt9zPZ2HtvbsfPY3paPs71sb3traw9btre9771txSGwLqbX6+Hi4oLy8vJOJ+6egO3t3dje3o3t7d3srb3XYw9QF3NwcMD//d//wcHBQepSugTb27uxvb0b29u72Vt7r8ceICIiIrI77AEiIiIiu8MARERERHaHAYiIiIjsDgMQERER2R0GICIiIrI7DEDdVEpKCkaMGGF5aDQafPHFF1KXZVNXrlzBpEmTMHjwYAwdOhRVVVVSl2RTCoXC8v197LHHpC6nS1RXVyMoKAjPPPOM1KXYVEVFBcaMGYMRI0Zg6NCheO+996QuyaaysrJw++23Y/DgwRg2bBg+++wzqUuyudmzZ8PNzQ1z5syRuhSb+PrrrzFo0CAMGDAAW7Zskbocm+Ay+B6gsrISwcHByMjIgJOTk9Tl2Mxtt92Gl156CdHR0SgpKYFOp4NC0Xvv1uLp6YmioiKpy+hSq1atQlpaGgIDA/Haa69JXY7NmEwm1NXVwdHREdXV1YiIiMDx48fh4eEhdWk2kZeXh4KCAowYMQKFhYUYNWoUUlJSevXPqwMHDqCyshJbt27Frl27pC7Hqurr6zF48GAcOHAAOp0Oo0aNws8//wx3d3epS7Mq9gD1AHv27MGdd97Zq3+YnD17FkqlEtHR0QAAd3f3Xh1+7FFaWhouXLiAqVOnSl2Kzcnlcjg6OgIAamtrYTKZ0Jt/1/Tx8cGIESMAAF5eXnB3d0dJSYm0RdnYpEmToNVqpS7DJhISEjBkyBD4+flBq9Vi6tSp2Ldvn9RlWR0DUAcdPnwY06dPh6+vLwRBaHF4atOmTQgJCYFarUZkZCSOHDnSoc+1c+dOzJ07t5MVd46t25uWlgZnZ2fMmDEDo0aNwrp166xYfft1xfdXr9cjMjISt9xyCw4dOmSlyjumK9r7zDPPYP369VaquHO6or1lZWUYPnw4/P398Ze//AWenp5Wqr79uvLnVWJiIsxmMwICAjpZdcd1ZXu7o862Pzc3F35+fpaP/f39kZOT0xWldykGoA6qqqrC8OHD8dZbb7X4/I4dO7Bs2TKsWrUKJ06cQHR0NKZMmYLMzEzLOZGRkYiIiGj2yM3NtZyj1+tx7NgxyX9rtnV7jUYjjhw5go0bN+LHH39EXFwc4uLiuqp5zXTF9zc9PR1JSUl4++23sWDBAuj1+i5pW0ts3d4vv/wSAwcOxMCBA7uqSa3qiu+vq6srTp48iStXruDTTz9FQUFBl7StJV3186q4uBgLFizAu+++a/M2taar2ttddbb9LfVWCoJg05olIVKnARD/85//NDk2duxYccmSJU2OhYWFic8991y7rr1t2zbx4Ycf7myJVmWL9sbHx4sxMTGWj//+97+Lf//73ztdqzXY8vvb6J577hGPHz/e0RKtyhbtfe6550R/f38xKChI9PDwEHU6nbhmzRprldwpXfH9XbJkibhz586OlmhVtmpvbW2tGB0dLW7bts0aZVqNLb+/Bw4cEH/zm990tkSb6kj7jx07Js6aNcvy3JNPPil+8sknNq+1q7EHyAYMBgOSkpIwefLkJscnT56M+Pj4dl2rOwx/3Yw12jtmzBgUFBSgtLQUZrMZhw8fRnh4uC3K7TRrtLe0tBR1dXUAgOzsbJw7dw79+vWzeq3WYI32rl+/HllZWUhPT8drr72Gxx9/HC+88IItyu00a7S3oKDA0qOn1+tx+PBhDBo0yOq1WoM12iuKIhYuXIg77rgD8+fPt0WZVmPNn889UVvaP3bsWJw5cwY5OTmoqKjA3r17ERMTI0W5NsVZpjZQVFQEk8kEb2/vJse9vb2Rn5/f5uuUl5cjISEBn3/+ubVLtCprtFehUGDdunW49dZbIYoiJk+ejGnTptmi3E6zRnvPnz+PxYsXQyaTQRAE/OMf/+i2Kyys9e+5p7BGe7Ozs7Fo0SKIoghRFPHHP/4Rw4YNs0W5nWaN9h47dgw7duzAsGHDLPNNPvroIwwdOtTa5Xaatf49x8TE4JdffkFVVRX8/f3xn//8B2PGjLF2uVbXlvYrFAps2LABkyZNgtlsxl/+8pdeuYKRAciGrh8zFUWxXeOoLi4uks4baK/OtnfKlCmYMmWKtcuymc60NyoqCqdPn7ZFWTbT2e9vo4ULF1qpItvqTHsjIyORnJxsg6pspzPtveWWW2A2m21Rls109t9zT18VdbP2z5gxAzNmzOjqsroUh8BswNPTE3K5vNlvE4WFhc1Sd2/A9jZge3sHtrcB29s72Xv7f40ByAZUKhUiIyObrWKKi4tDVFSURFXZDtvbgO3tHdjeBmxv72Tv7f81DoF1UGVlJS5evGj5+MqVK0hOToa7uzsCAwOxfPlyzJ8/H6NHj8aECRPw7rvvIjMzE0uWLJGw6o5je9letpft7Snsrb3Xs/f2t5k0i896vgMHDogAmj0effRRyzkbN24Ug4KCRJVKJY4aNUo8dOiQdAV3EtvL9rK9bG9PYW/tvZ69t7+teC8wIiIisjucA0RERER2hwGIiIiI7A4DEBEREdkdBiAiIiKyOwxAREREZHcYgIiIiMjuMAARERGR3WEAIiIiIrvDAEREvU5wcDDefPNNqcsgom6MAYiIOmThwoWYNWuW1GW06Pjx43jiiSds/nmCg4MhCAIEQYBGo0FYWBheffVVtHeDfQY2oq7Hm6ESUY9hNBqhVCpvel6fPn26oJoGa9euxeOPP47a2lp89913+P3vfw+dTofFixd3WQ1E1H7sASIimzh37hymTp0KZ2dneHt7Y/78+SgqKrI8/+233+KWW26Bq6srPDw8MG3aNFy6dMnyfHp6OgRBwM6dO3H77bdDrVbj448/tvQ8vfbaa/Dx8YGHhweWLl0Ko9Foee31PSqCIGDLli2YPXs2HB0dMWDAAOzZs6dJvXv27MGAAQOg0WgwadIkbN26FYIgoKysrNV2arVa9O3bF8HBwXjssccwbNgw7N+/3/L8pUuXMHPmTHh7e8PZ2RljxozBd999Z3n+9ttvR0ZGBp5++mlLb1Kj+Ph43HrrrdBoNAgICMCTTz6JqqqqNn8PiOjGGICIyOry8vJw2223YcSIEUhMTMS3336LgoICPPDAA5ZzqqqqsHz5chw/fhzff/89ZDIZZs+eDbPZ3ORaK1aswJNPPonz588jJiYGAHDgwAFcunQJBw4cwNatW/Hhhx/iww8/bLWmNWvW4IEHHsCpU6cwdepUPPzwwygpKQHQELbmzJmDWbNmITk5GYsXL8aqVava1WZRFHHw4EGcP3++SS9VZWUlpk6diu+++w4nTpxATEwMpk+fjszMTADA7t274e/vj7Vr1yIvLw95eXkAgNOnTyMmJgb33XcfTp06hR07duDo0aP44x//2K66iOgGpL0ZPRH1VI8++qg4c+bMFp9bvXq1OHny5CbHsrKyRABiSkpKi68pLCwUAYinT58WRVEUr1y5IgIQ33zzzWafNygoSKyvr7ccu//++8W5c+daPg4KChLfeOMNy8cAxOeff97ycWVlpSgIgvjf//5XFEVRXLFihRgREdHk86xatUoEIJaWlrb8Bbj2eVQqlejk5CQqlUoRgKhWq8Vjx47d8DWiKIqDBw8W//Wvf92wXlEUxfnz54tPPPFEk2NHjhwRZTKZWFNT0+r1iejm2ANERFaXlJSEAwcOwNnZ2fIICwsDAMsw16VLl/DQQw+hX79+0Ol0CAkJAQBLz0ij0aNHN7v+kCFDIJfLLR/7+PigsLCw1ZqGDRtm+buTkxO0Wq3lNSkpKRgzZkyT88eOHdumtj777LNITk7GoUOHMGnSJKxatQpRUVGW56uqqvCXv/wFgwcPhqurK5ydnXHhwoVm7bxeUlISPvzwwyZfw5iYGJjNZly5cqVNtRHRjXESNBFZndlsxvTp0/HKK680e87HxwcAMH36dAQEBOC9996Dr68vzGYzIiIiYDAYmpzv5OTU7BrXT4QWBKHZ0Fl7XiOKYpO5N43H2sLT0xOhoaEIDQ3F559/jtDQUIwfPx533XUXgIaAtG/fPrz22msIDQ2FRqPBnDlzmrXzemazGYsXL8aTTz7Z7LnAwMA21UZEN8YARERWN2rUKHz++ecIDg6GQtH8x0xxcTHOnz+Pd955B9HR0QCAo0ePdnWZFmFhYdi7d2+TY4mJie2+jpubG/70pz/hmWeewYkTJyAIAo4cOYKFCxdi9uzZABrmBKWnpzd5nUqlgslkanJs1KhROHv2LEJDQ9tdBxHdHIfAiKjDysvLkZyc3OSRmZmJpUuXoqSkBA8++CASEhJw+fJl7N+/H7/73e9gMpng5uYGDw8PvPvuu7h48SJ++OEHLF++XLJ2LF68GBcuXMCKFSuQmpqKnTt3WiZVX98zdDNLly5FSkoKPv/8cwBAaGgodu/ejeTkZJw8eRIPPfRQs96q4OBgHD58GDk5OZaVcitWrMCPP/6IpUuXIjk5GWlpadizZw/+9Kc/db7BRMQAREQdd/DgQYwcObLJ44UXXoCvry+OHTsGk8mEmJgYRERE4KmnnoKLiwtkMhlkMhm2b9+OpKQkRERE4Omnn8arr74qWTtCQkKwa9cu7N69G8OGDcPmzZstq8AcHBzada0+ffpg/vz5ePHFF2E2m/HGG2/Azc0NUVFRmD59OmJiYjBq1Kgmr1m7di3S09PRv39/yx5Gw4YNw6FDh5CWlobo6GiMHDkSq1evtgwhElHnCGJbB7qJiOzIyy+/jLfffhtZWVlSl0JENsA5QEREADZt2oQxY8bAw8MDx44dw6uvvso9d4h6MQYgIiIAaWlpeOmll1BSUoLAwED8+c9/xsqVK6Uui4hshENgREREZHc4CZqIiIjsDgMQERER2R0GICIiIrI7DEBERERkdxiAiIiIyO4wABEREZHdYQAiIiIiu8MARERERHaHAYiIiIjszv8H0IEV77HCItQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run the learning rate finder\n",
    "learn.lr_find()\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "      <progress value='0' class='' max='10' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      0.00% [0/10 00:00&lt;?]\n",
       "    </div>\n",
       "    \n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table><p>\n",
       "\n",
       "    <div>\n",
       "      <progress value='0' class='' max='325' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      0.00% [0/325 00:00&lt;?]\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "RuntimeError",
     "evalue": "CUDA out of memory. Tried to allocate 98.00 MiB (GPU 0; 10.75 GiB total capacity; 8.15 GiB already allocated; 14.12 MiB free; 8.31 GiB reserved in total by PyTorch)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[14], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m lr \u001b[39m=\u001b[39m \u001b[39m0.02\u001b[39m\n\u001b[0;32m----> 2\u001b[0m learn\u001b[39m.\u001b[39;49mfit_one_cycle(\u001b[39m10\u001b[39;49m, \u001b[39mslice\u001b[39;49m(lr))\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/callback/schedule.py:119\u001b[0m, in \u001b[0;36mfit_one_cycle\u001b[0;34m(self, n_epoch, lr_max, div, div_final, pct_start, wd, moms, cbs, reset_opt, start_epoch)\u001b[0m\n\u001b[1;32m    116\u001b[0m lr_max \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39marray([h[\u001b[39m'\u001b[39m\u001b[39mlr\u001b[39m\u001b[39m'\u001b[39m] \u001b[39mfor\u001b[39;00m h \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mopt\u001b[39m.\u001b[39mhypers])\n\u001b[1;32m    117\u001b[0m scheds \u001b[39m=\u001b[39m {\u001b[39m'\u001b[39m\u001b[39mlr\u001b[39m\u001b[39m'\u001b[39m: combined_cos(pct_start, lr_max\u001b[39m/\u001b[39mdiv, lr_max, lr_max\u001b[39m/\u001b[39mdiv_final),\n\u001b[1;32m    118\u001b[0m           \u001b[39m'\u001b[39m\u001b[39mmom\u001b[39m\u001b[39m'\u001b[39m: combined_cos(pct_start, \u001b[39m*\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mmoms \u001b[39mif\u001b[39;00m moms \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m moms))}\n\u001b[0;32m--> 119\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfit(n_epoch, cbs\u001b[39m=\u001b[39;49mParamScheduler(scheds)\u001b[39m+\u001b[39;49mL(cbs), reset_opt\u001b[39m=\u001b[39;49mreset_opt, wd\u001b[39m=\u001b[39;49mwd, start_epoch\u001b[39m=\u001b[39;49mstart_epoch)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:264\u001b[0m, in \u001b[0;36mLearner.fit\u001b[0;34m(self, n_epoch, lr, wd, cbs, reset_opt, start_epoch)\u001b[0m\n\u001b[1;32m    262\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mopt\u001b[39m.\u001b[39mset_hypers(lr\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mlr \u001b[39mif\u001b[39;00m lr \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m lr)\n\u001b[1;32m    263\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_epoch \u001b[39m=\u001b[39m n_epoch\n\u001b[0;32m--> 264\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_with_events(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_do_fit, \u001b[39m'\u001b[39;49m\u001b[39mfit\u001b[39;49m\u001b[39m'\u001b[39;49m, CancelFitException, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_end_cleanup)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:199\u001b[0m, in \u001b[0;36mLearner._with_events\u001b[0;34m(self, f, event_type, ex, final)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_with_events\u001b[39m(\u001b[39mself\u001b[39m, f, event_type, ex, final\u001b[39m=\u001b[39mnoop):\n\u001b[0;32m--> 199\u001b[0m     \u001b[39mtry\u001b[39;00m: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mbefore_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  f()\n\u001b[1;32m    200\u001b[0m     \u001b[39mexcept\u001b[39;00m ex: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_cancel_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[1;32m    201\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  final()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:253\u001b[0m, in \u001b[0;36mLearner._do_fit\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    251\u001b[0m \u001b[39mfor\u001b[39;00m epoch \u001b[39min\u001b[39;00m \u001b[39mrange\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_epoch):\n\u001b[1;32m    252\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mepoch\u001b[39m=\u001b[39mepoch\n\u001b[0;32m--> 253\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_with_events(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_do_epoch, \u001b[39m'\u001b[39;49m\u001b[39mepoch\u001b[39;49m\u001b[39m'\u001b[39;49m, CancelEpochException)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:199\u001b[0m, in \u001b[0;36mLearner._with_events\u001b[0;34m(self, f, event_type, ex, final)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_with_events\u001b[39m(\u001b[39mself\u001b[39m, f, event_type, ex, final\u001b[39m=\u001b[39mnoop):\n\u001b[0;32m--> 199\u001b[0m     \u001b[39mtry\u001b[39;00m: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mbefore_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  f()\n\u001b[1;32m    200\u001b[0m     \u001b[39mexcept\u001b[39;00m ex: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_cancel_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[1;32m    201\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  final()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:247\u001b[0m, in \u001b[0;36mLearner._do_epoch\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    246\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_do_epoch\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[0;32m--> 247\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_do_epoch_train()\n\u001b[1;32m    248\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_do_epoch_validate()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:239\u001b[0m, in \u001b[0;36mLearner._do_epoch_train\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    237\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_do_epoch_train\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[1;32m    238\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdl \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdls\u001b[39m.\u001b[39mtrain\n\u001b[0;32m--> 239\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_with_events(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mall_batches, \u001b[39m'\u001b[39;49m\u001b[39mtrain\u001b[39;49m\u001b[39m'\u001b[39;49m, CancelTrainException)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:199\u001b[0m, in \u001b[0;36mLearner._with_events\u001b[0;34m(self, f, event_type, ex, final)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_with_events\u001b[39m(\u001b[39mself\u001b[39m, f, event_type, ex, final\u001b[39m=\u001b[39mnoop):\n\u001b[0;32m--> 199\u001b[0m     \u001b[39mtry\u001b[39;00m: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mbefore_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  f()\n\u001b[1;32m    200\u001b[0m     \u001b[39mexcept\u001b[39;00m ex: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_cancel_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[1;32m    201\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  final()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:205\u001b[0m, in \u001b[0;36mLearner.all_batches\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    203\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mall_batches\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[1;32m    204\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_iter \u001b[39m=\u001b[39m \u001b[39mlen\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdl)\n\u001b[0;32m--> 205\u001b[0m     \u001b[39mfor\u001b[39;00m o \u001b[39min\u001b[39;00m \u001b[39menumerate\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdl): \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mone_batch(\u001b[39m*\u001b[39;49mo)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:235\u001b[0m, in \u001b[0;36mLearner.one_batch\u001b[0;34m(self, i, b)\u001b[0m\n\u001b[1;32m    233\u001b[0m b \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_set_device(b)\n\u001b[1;32m    234\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_split(b)\n\u001b[0;32m--> 235\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_with_events(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_do_one_batch, \u001b[39m'\u001b[39;49m\u001b[39mbatch\u001b[39;49m\u001b[39m'\u001b[39;49m, CancelBatchException)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:199\u001b[0m, in \u001b[0;36mLearner._with_events\u001b[0;34m(self, f, event_type, ex, final)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_with_events\u001b[39m(\u001b[39mself\u001b[39m, f, event_type, ex, final\u001b[39m=\u001b[39mnoop):\n\u001b[0;32m--> 199\u001b[0m     \u001b[39mtry\u001b[39;00m: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mbefore_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  f()\n\u001b[1;32m    200\u001b[0m     \u001b[39mexcept\u001b[39;00m ex: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_cancel_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[1;32m    201\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  final()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:216\u001b[0m, in \u001b[0;36mLearner._do_one_batch\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    215\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_do_one_batch\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[0;32m--> 216\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpred \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mmodel(\u001b[39m*\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mxb)\n\u001b[1;32m    217\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39m'\u001b[39m\u001b[39mafter_pred\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m    218\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mlen\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39myb):\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/container.py:139\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m):\n\u001b[1;32m    138\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m:\n\u001b[0;32m--> 139\u001b[0m         \u001b[39minput\u001b[39m \u001b[39m=\u001b[39m module(\u001b[39minput\u001b[39;49m)\n\u001b[1;32m    140\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39minput\u001b[39m\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/container.py:139\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m):\n\u001b[1;32m    138\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m:\n\u001b[0;32m--> 139\u001b[0m         \u001b[39minput\u001b[39m \u001b[39m=\u001b[39m module(\u001b[39minput\u001b[39;49m)\n\u001b[1;32m    140\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39minput\u001b[39m\n",
      "    \u001b[0;31m[... skipping similar frames: Module._call_impl at line 1051 (1 times)]\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/container.py:139\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m):\n\u001b[1;32m    138\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m:\n\u001b[0;32m--> 139\u001b[0m         \u001b[39minput\u001b[39m \u001b[39m=\u001b[39m module(\u001b[39minput\u001b[39;49m)\n\u001b[1;32m    140\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39minput\u001b[39m\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torchvision/models/resnet.py:136\u001b[0m, in \u001b[0;36mBottleneck.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m    133\u001b[0m out \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mbn3(out)\n\u001b[1;32m    135\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdownsample \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m--> 136\u001b[0m     identity \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mdownsample(x)\n\u001b[1;32m    138\u001b[0m out \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m identity\n\u001b[1;32m    139\u001b[0m out \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrelu(out)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/container.py:139\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m):\n\u001b[1;32m    138\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m:\n\u001b[0;32m--> 139\u001b[0m         \u001b[39minput\u001b[39m \u001b[39m=\u001b[39m module(\u001b[39minput\u001b[39;49m)\n\u001b[1;32m    140\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39minput\u001b[39m\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/conv.py:443\u001b[0m, in \u001b[0;36mConv2d.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    442\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m: Tensor) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Tensor:\n\u001b[0;32m--> 443\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_conv_forward(\u001b[39minput\u001b[39;49m, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mweight, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mbias)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/conv.py:439\u001b[0m, in \u001b[0;36mConv2d._conv_forward\u001b[0;34m(self, input, weight, bias)\u001b[0m\n\u001b[1;32m    435\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpadding_mode \u001b[39m!=\u001b[39m \u001b[39m'\u001b[39m\u001b[39mzeros\u001b[39m\u001b[39m'\u001b[39m:\n\u001b[1;32m    436\u001b[0m     \u001b[39mreturn\u001b[39;00m F\u001b[39m.\u001b[39mconv2d(F\u001b[39m.\u001b[39mpad(\u001b[39minput\u001b[39m, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_reversed_padding_repeated_twice, mode\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpadding_mode),\n\u001b[1;32m    437\u001b[0m                     weight, bias, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstride,\n\u001b[1;32m    438\u001b[0m                     _pair(\u001b[39m0\u001b[39m), \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdilation, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mgroups)\n\u001b[0;32m--> 439\u001b[0m \u001b[39mreturn\u001b[39;00m F\u001b[39m.\u001b[39;49mconv2d(\u001b[39minput\u001b[39;49m, weight, bias, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mstride,\n\u001b[1;32m    440\u001b[0m                 \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mpadding, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mdilation, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mgroups)\n",
      "\u001b[0;31mRuntimeError\u001b[0m: CUDA out of memory. Tried to allocate 98.00 MiB (GPU 0; 10.75 GiB total capacity; 8.15 GiB already allocated; 14.12 MiB free; 8.31 GiB reserved in total by PyTorch)"
     ]
    }
   ],
   "source": [
    "lr = 0.02\n",
    "learn.fit_one_cycle(10, slice(lr))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "      <progress value='0' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      0.00% [0/1 00:00&lt;?]\n",
       "    </div>\n",
       "    \n",
       "\n",
       "\n",
       "    <div>\n",
       "      <progress value='0' class='' max='325' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      0.00% [0/325 00:00&lt;?]\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Exception ignored in: <function _MultiProcessingDataLoaderIter.__del__ at 0x7f8432dc4f70>\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/nikhil/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/utils/data/dataloader.py\", line 1328, in __del__\n",
      "    self._shutdown_workers()\n",
      "  File \"/home/nikhil/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/utils/data/dataloader.py\", line 1301, in _shutdown_workers\n",
      "    w.join(timeout=_utils.MP_STATUS_CHECK_INTERVAL)\n",
      "  File \"/home/nikhil/anaconda3/envs/ptc/lib/python3.9/multiprocessing/process.py\", line 149, in join\n",
      "    res = self._popen.wait(timeout)\n",
      "  File \"/home/nikhil/anaconda3/envs/ptc/lib/python3.9/multiprocessing/popen_fork.py\", line 40, in wait\n",
      "    if not wait([self.sentinel], timeout):\n",
      "  File \"/home/nikhil/anaconda3/envs/ptc/lib/python3.9/multiprocessing/connection.py\", line 931, in wait\n",
      "    ready = selector.select(timeout)\n",
      "  File \"/home/nikhil/anaconda3/envs/ptc/lib/python3.9/selectors.py\", line 416, in select\n",
      "    fd_event_list = self._selector.poll(timeout)\n",
      "KeyboardInterrupt: \n"
     ]
    },
    {
     "ename": "RuntimeError",
     "evalue": "CUDA out of memory. Tried to allocate 50.00 MiB (GPU 0; 10.75 GiB total capacity; 9.38 GiB already allocated; 16.12 MiB free; 9.58 GiB reserved in total by PyTorch)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[11], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m learn\u001b[39m.\u001b[39mload(\u001b[39m'\u001b[39m\u001b[39mstage1_weights\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m      2\u001b[0m learn\u001b[39m.\u001b[39munfreeze()\n\u001b[0;32m----> 3\u001b[0m learn\u001b[39m.\u001b[39;49mlr_find()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/callback/schedule.py:293\u001b[0m, in \u001b[0;36mlr_find\u001b[0;34m(self, start_lr, end_lr, num_it, stop_div, show_plot, suggest_funcs)\u001b[0m\n\u001b[1;32m    291\u001b[0m n_epoch \u001b[39m=\u001b[39m num_it\u001b[39m/\u001b[39m\u001b[39m/\u001b[39m\u001b[39mlen\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdls\u001b[39m.\u001b[39mtrain) \u001b[39m+\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m    292\u001b[0m cb\u001b[39m=\u001b[39mLRFinder(start_lr\u001b[39m=\u001b[39mstart_lr, end_lr\u001b[39m=\u001b[39mend_lr, num_it\u001b[39m=\u001b[39mnum_it, stop_div\u001b[39m=\u001b[39mstop_div)\n\u001b[0;32m--> 293\u001b[0m \u001b[39mwith\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mno_logging(): \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfit(n_epoch, cbs\u001b[39m=\u001b[39;49mcb)\n\u001b[1;32m    294\u001b[0m \u001b[39mif\u001b[39;00m suggest_funcs \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m    295\u001b[0m     lrs, losses \u001b[39m=\u001b[39m tensor(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrecorder\u001b[39m.\u001b[39mlrs[num_it\u001b[39m/\u001b[39m\u001b[39m/\u001b[39m\u001b[39m10\u001b[39m:\u001b[39m-\u001b[39m\u001b[39m5\u001b[39m]), tensor(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrecorder\u001b[39m.\u001b[39mlosses[num_it\u001b[39m/\u001b[39m\u001b[39m/\u001b[39m\u001b[39m10\u001b[39m:\u001b[39m-\u001b[39m\u001b[39m5\u001b[39m])\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:264\u001b[0m, in \u001b[0;36mLearner.fit\u001b[0;34m(self, n_epoch, lr, wd, cbs, reset_opt, start_epoch)\u001b[0m\n\u001b[1;32m    262\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mopt\u001b[39m.\u001b[39mset_hypers(lr\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mlr \u001b[39mif\u001b[39;00m lr \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m lr)\n\u001b[1;32m    263\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_epoch \u001b[39m=\u001b[39m n_epoch\n\u001b[0;32m--> 264\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_with_events(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_do_fit, \u001b[39m'\u001b[39;49m\u001b[39mfit\u001b[39;49m\u001b[39m'\u001b[39;49m, CancelFitException, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_end_cleanup)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:199\u001b[0m, in \u001b[0;36mLearner._with_events\u001b[0;34m(self, f, event_type, ex, final)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_with_events\u001b[39m(\u001b[39mself\u001b[39m, f, event_type, ex, final\u001b[39m=\u001b[39mnoop):\n\u001b[0;32m--> 199\u001b[0m     \u001b[39mtry\u001b[39;00m: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mbefore_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  f()\n\u001b[1;32m    200\u001b[0m     \u001b[39mexcept\u001b[39;00m ex: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_cancel_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[1;32m    201\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  final()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:253\u001b[0m, in \u001b[0;36mLearner._do_fit\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    251\u001b[0m \u001b[39mfor\u001b[39;00m epoch \u001b[39min\u001b[39;00m \u001b[39mrange\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_epoch):\n\u001b[1;32m    252\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mepoch\u001b[39m=\u001b[39mepoch\n\u001b[0;32m--> 253\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_with_events(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_do_epoch, \u001b[39m'\u001b[39;49m\u001b[39mepoch\u001b[39;49m\u001b[39m'\u001b[39;49m, CancelEpochException)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:199\u001b[0m, in \u001b[0;36mLearner._with_events\u001b[0;34m(self, f, event_type, ex, final)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_with_events\u001b[39m(\u001b[39mself\u001b[39m, f, event_type, ex, final\u001b[39m=\u001b[39mnoop):\n\u001b[0;32m--> 199\u001b[0m     \u001b[39mtry\u001b[39;00m: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mbefore_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  f()\n\u001b[1;32m    200\u001b[0m     \u001b[39mexcept\u001b[39;00m ex: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_cancel_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[1;32m    201\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  final()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:247\u001b[0m, in \u001b[0;36mLearner._do_epoch\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    246\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_do_epoch\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[0;32m--> 247\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_do_epoch_train()\n\u001b[1;32m    248\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_do_epoch_validate()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:239\u001b[0m, in \u001b[0;36mLearner._do_epoch_train\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    237\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_do_epoch_train\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[1;32m    238\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdl \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdls\u001b[39m.\u001b[39mtrain\n\u001b[0;32m--> 239\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_with_events(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mall_batches, \u001b[39m'\u001b[39;49m\u001b[39mtrain\u001b[39;49m\u001b[39m'\u001b[39;49m, CancelTrainException)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:199\u001b[0m, in \u001b[0;36mLearner._with_events\u001b[0;34m(self, f, event_type, ex, final)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_with_events\u001b[39m(\u001b[39mself\u001b[39m, f, event_type, ex, final\u001b[39m=\u001b[39mnoop):\n\u001b[0;32m--> 199\u001b[0m     \u001b[39mtry\u001b[39;00m: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mbefore_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  f()\n\u001b[1;32m    200\u001b[0m     \u001b[39mexcept\u001b[39;00m ex: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_cancel_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[1;32m    201\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  final()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:205\u001b[0m, in \u001b[0;36mLearner.all_batches\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    203\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mall_batches\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[1;32m    204\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_iter \u001b[39m=\u001b[39m \u001b[39mlen\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdl)\n\u001b[0;32m--> 205\u001b[0m     \u001b[39mfor\u001b[39;00m o \u001b[39min\u001b[39;00m \u001b[39menumerate\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdl): \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mone_batch(\u001b[39m*\u001b[39;49mo)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:235\u001b[0m, in \u001b[0;36mLearner.one_batch\u001b[0;34m(self, i, b)\u001b[0m\n\u001b[1;32m    233\u001b[0m b \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_set_device(b)\n\u001b[1;32m    234\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_split(b)\n\u001b[0;32m--> 235\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_with_events(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_do_one_batch, \u001b[39m'\u001b[39;49m\u001b[39mbatch\u001b[39;49m\u001b[39m'\u001b[39;49m, CancelBatchException)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:199\u001b[0m, in \u001b[0;36mLearner._with_events\u001b[0;34m(self, f, event_type, ex, final)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_with_events\u001b[39m(\u001b[39mself\u001b[39m, f, event_type, ex, final\u001b[39m=\u001b[39mnoop):\n\u001b[0;32m--> 199\u001b[0m     \u001b[39mtry\u001b[39;00m: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mbefore_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  f()\n\u001b[1;32m    200\u001b[0m     \u001b[39mexcept\u001b[39;00m ex: \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_cancel_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[1;32m    201\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mafter_\u001b[39m\u001b[39m{\u001b[39;00mevent_type\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m);  final()\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/fastai/learner.py:216\u001b[0m, in \u001b[0;36mLearner._do_one_batch\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    215\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_do_one_batch\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[0;32m--> 216\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpred \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mmodel(\u001b[39m*\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mxb)\n\u001b[1;32m    217\u001b[0m     \u001b[39mself\u001b[39m(\u001b[39m'\u001b[39m\u001b[39mafter_pred\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m    218\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mlen\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39myb):\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/container.py:139\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m):\n\u001b[1;32m    138\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m:\n\u001b[0;32m--> 139\u001b[0m         \u001b[39minput\u001b[39m \u001b[39m=\u001b[39m module(\u001b[39minput\u001b[39;49m)\n\u001b[1;32m    140\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39minput\u001b[39m\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/container.py:139\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m):\n\u001b[1;32m    138\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m:\n\u001b[0;32m--> 139\u001b[0m         \u001b[39minput\u001b[39m \u001b[39m=\u001b[39m module(\u001b[39minput\u001b[39;49m)\n\u001b[1;32m    140\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39minput\u001b[39m\n",
      "    \u001b[0;31m[... skipping similar frames: Module._call_impl at line 1051 (1 times)]\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/container.py:139\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m):\n\u001b[1;32m    138\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m:\n\u001b[0;32m--> 139\u001b[0m         \u001b[39minput\u001b[39m \u001b[39m=\u001b[39m module(\u001b[39minput\u001b[39;49m)\n\u001b[1;32m    140\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39minput\u001b[39m\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torchvision/models/resnet.py:136\u001b[0m, in \u001b[0;36mBottleneck.forward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m    133\u001b[0m out \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mbn3(out)\n\u001b[1;32m    135\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdownsample \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m--> 136\u001b[0m     identity \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mdownsample(x)\n\u001b[1;32m    138\u001b[0m out \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m identity\n\u001b[1;32m    139\u001b[0m out \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrelu(out)\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/container.py:139\u001b[0m, in \u001b[0;36mSequential.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    137\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m):\n\u001b[1;32m    138\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m:\n\u001b[0;32m--> 139\u001b[0m         \u001b[39minput\u001b[39m \u001b[39m=\u001b[39m module(\u001b[39minput\u001b[39;49m)\n\u001b[1;32m    140\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39minput\u001b[39m\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/module.py:1051\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m   1047\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m   1048\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m   1049\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m   1050\u001b[0m         \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1051\u001b[0m     \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1052\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m   1053\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py:167\u001b[0m, in \u001b[0;36m_BatchNorm.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m    160\u001b[0m     bn_training \u001b[39m=\u001b[39m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrunning_mean \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m) \u001b[39mand\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrunning_var \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m)\n\u001b[1;32m    162\u001b[0m \u001b[39m\u001b[39m\u001b[39mr\u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m    163\u001b[0m \u001b[39mBuffers are only updated if they are to be tracked and we are in training mode. Thus they only need to be\u001b[39;00m\n\u001b[1;32m    164\u001b[0m \u001b[39mpassed when the update should occur (i.e. in training mode when they are tracked), or when buffer stats are\u001b[39;00m\n\u001b[1;32m    165\u001b[0m \u001b[39mused for normalization (i.e. in eval mode when buffers are not None).\u001b[39;00m\n\u001b[1;32m    166\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[0;32m--> 167\u001b[0m \u001b[39mreturn\u001b[39;00m F\u001b[39m.\u001b[39;49mbatch_norm(\n\u001b[1;32m    168\u001b[0m     \u001b[39minput\u001b[39;49m,\n\u001b[1;32m    169\u001b[0m     \u001b[39m# If buffers are not to be tracked, ensure that they won't be updated\u001b[39;49;00m\n\u001b[1;32m    170\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mrunning_mean\n\u001b[1;32m    171\u001b[0m     \u001b[39mif\u001b[39;49;00m \u001b[39mnot\u001b[39;49;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtraining \u001b[39mor\u001b[39;49;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtrack_running_stats\n\u001b[1;32m    172\u001b[0m     \u001b[39melse\u001b[39;49;00m \u001b[39mNone\u001b[39;49;00m,\n\u001b[1;32m    173\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mrunning_var \u001b[39mif\u001b[39;49;00m \u001b[39mnot\u001b[39;49;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtraining \u001b[39mor\u001b[39;49;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtrack_running_stats \u001b[39melse\u001b[39;49;00m \u001b[39mNone\u001b[39;49;00m,\n\u001b[1;32m    174\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mweight,\n\u001b[1;32m    175\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mbias,\n\u001b[1;32m    176\u001b[0m     bn_training,\n\u001b[1;32m    177\u001b[0m     exponential_average_factor,\n\u001b[1;32m    178\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49meps,\n\u001b[1;32m    179\u001b[0m )\n",
      "File \u001b[0;32m~/anaconda3/envs/ptc/lib/python3.9/site-packages/torch/nn/functional.py:2281\u001b[0m, in \u001b[0;36mbatch_norm\u001b[0;34m(input, running_mean, running_var, weight, bias, training, momentum, eps)\u001b[0m\n\u001b[1;32m   2278\u001b[0m \u001b[39mif\u001b[39;00m training:\n\u001b[1;32m   2279\u001b[0m     _verify_batch_size(\u001b[39minput\u001b[39m\u001b[39m.\u001b[39msize())\n\u001b[0;32m-> 2281\u001b[0m \u001b[39mreturn\u001b[39;00m torch\u001b[39m.\u001b[39;49mbatch_norm(\n\u001b[1;32m   2282\u001b[0m     \u001b[39minput\u001b[39;49m, weight, bias, running_mean, running_var, training, momentum, eps, torch\u001b[39m.\u001b[39;49mbackends\u001b[39m.\u001b[39;49mcudnn\u001b[39m.\u001b[39;49menabled\n\u001b[1;32m   2283\u001b[0m )\n",
      "\u001b[0;31mRuntimeError\u001b[0m: CUDA out of memory. Tried to allocate 50.00 MiB (GPU 0; 10.75 GiB total capacity; 9.38 GiB already allocated; 16.12 MiB free; 9.58 GiB reserved in total by PyTorch)"
     ]
    }
   ],
   "source": [
    "learn.save('stage1_weights')\n",
    "learn.load('stage1_weights')\n",
    "learn.unfreeze()\n",
    "learn.lr_find()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'learn' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[8], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m learn\u001b[39m.\u001b[39mlr_find()\n",
      "\u001b[0;31mNameError\u001b[0m: name 'learn' is not defined"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.928260</td>\n",
       "      <td>2.002362</td>\n",
       "      <td>01:37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.930020</td>\n",
       "      <td>1.887904</td>\n",
       "      <td>01:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.929078</td>\n",
       "      <td>1.904317</td>\n",
       "      <td>01:52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.928998</td>\n",
       "      <td>1.668131</td>\n",
       "      <td>01:53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.928017</td>\n",
       "      <td>1.691515</td>\n",
       "      <td>02:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.926705</td>\n",
       "      <td>1.775430</td>\n",
       "      <td>02:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.928038</td>\n",
       "      <td>1.775926</td>\n",
       "      <td>02:04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.927857</td>\n",
       "      <td>1.704160</td>\n",
       "      <td>02:04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.927805</td>\n",
       "      <td>1.764529</td>\n",
       "      <td>02:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.928271</td>\n",
       "      <td>1.798252</td>\n",
       "      <td>02:03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Path('/mnt/sda/nikhil/pbb/models/stage2_weights.pth')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr = 1.096\n",
    "learn.fit_one_cycle(10, slice(lr))\n",
    "learn.save('stage2_weights')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "SuggestedLRs(valley=0.04786301031708717)"
      ]
     },
     "execution_count": 16,
     "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": [
    "learn.load('stage2_weights')\n",
    "learn.unfreeze()\n",
    "learn.lr_find()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.926319</td>\n",
       "      <td>1.770086</td>\n",
       "      <td>02:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.927271</td>\n",
       "      <td>1.749271</td>\n",
       "      <td>02:04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.924816</td>\n",
       "      <td>1.794401</td>\n",
       "      <td>02:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.926261</td>\n",
       "      <td>1.729854</td>\n",
       "      <td>02:09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.925287</td>\n",
       "      <td>1.796544</td>\n",
       "      <td>02:09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.925831</td>\n",
       "      <td>1.816191</td>\n",
       "      <td>02:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.923735</td>\n",
       "      <td>1.778685</td>\n",
       "      <td>02:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.923584</td>\n",
       "      <td>1.790537</td>\n",
       "      <td>02:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>0.923791</td>\n",
       "      <td>1.803821</td>\n",
       "      <td>02:09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>0.923876</td>\n",
       "      <td>1.787736</td>\n",
       "      <td>02:08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Path('/mnt/sda/nikhil/pbb/models/stage3_weights.pth')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr = 0.0478\n",
    "learn.fit_one_cycle(10, slice(lr))\n",
    "learn.save('stage3_weights')"
   ]
  }
 ],
 "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": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}