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@hiromis
Last active August 10, 2021 01:45
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git/mariner/segmentation.ipynb
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{
"cells": [
{
"metadata": {},
"cell_type": "markdown",
"source": "# Mariner Takehome\n\n### Take Home Problem\nShould you join the Mariner team, some of your time will be spent training models on customer datasets, presenting results, and putting models into production. The purpose of this question is to work through this process with you on a toy problem.\n\nFrom the [mvtec ad](https://www.mvtec.com/company/research/datasets/mvtec-ad) dataset, please choose a category (e.g. Carpet, Capsule), and download these examples. Your download should include examples of both good and defective products, including segmentation mask labels. Note that the mvtec dataset is targeted at unsupervised learning, but here we'll be using it for a simple supervised learning task.\n\nUsing you DL framework of choice, train a semantic segmentation model on your chosen dataset. If training a segmentation model is too time consuming, please train a classification model.\n\nPrepare a short results presentation (5-10 slides), walking through a quick analysis of the data, your modeling approach, the results, and any recommendations you would make before taking this model into production.\n"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from fastai.vision.all import *\nimport wandb\nfrom fastai.callback.wandb import *",
"execution_count": 1,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "path = Path('data/pill')\n\nimage_path = path/'test'\nmask_path = path/'ground_truth'",
"execution_count": 2,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "labels = [f.name for f in image_path.ls()]\nlabels",
"execution_count": 3,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 3,
"data": {
"text/plain": "['good',\n 'color',\n 'faulty_imprint',\n 'contamination',\n 'pill_type',\n 'scratch',\n 'crack',\n 'combined']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "no_combined = labels[:7]\nno_combined",
"execution_count": 4,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 4,
"data": {
"text/plain": "['good',\n 'color',\n 'faulty_imprint',\n 'contamination',\n 'pill_type',\n 'scratch',\n 'crack']"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Updating masks\n\nCurrently, `ground_truth` masks are gray scale images where 0 is good, 255 is defect. To use the fast.ai's unet_learner, I pre-processed the images so that the mask pixel value looks as below:\n\n```\n{0: 'good',\n 1: 'color',\n 2: 'faulty_imprint',\n 3: 'contamination',\n 4: 'pill_type',\n 5: 'scratch',\n 6: 'crack'}\n```"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "! rm -rf data/pill/segmentation",
"execution_count": 5,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "segmentation_path = path/'segmentation'\nsegmentation_path.mkdir(mode=0o755, parents=True, exist_ok=True)",
"execution_count": 6,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "i = 0\nfor folder in no_combined:\n if folder == 'good':\n for file in (image_path/folder).ls():\n img = load_image(file)\n # Create a mask with all zeros (i.e. \"good\")\n mask = Image.fromarray(np.zeros(img.shape).astype(np.uint8), mode='L')\n mask.save(segmentation_path/f'{folder}-{file.stem}_mask{file.suffix}')\n shutil.copy(file, segmentation_path/f'{folder}-{file.name}')\n else:\n for file in (image_path/folder).ls():\n shutil.copy(file, segmentation_path/f'{folder}-{file.name}')\n for file in (mask_path/folder).ls():\n mask = load_image(file)\n mask = np.asarray(mask)\n mask = mask.clip(max=i)\n assert(np.max(mask) == i) # A quick sanity check of the max pixel value (== i)\n mask = Image.fromarray(mask) \n \n mask.save(segmentation_path/f'{folder}-{file.name}')\n i += 1",
"execution_count": 7,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Create DataLoaders"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "labeled_images = get_image_files(image_path, folders=no_combined)",
"execution_count": 8,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "len(labeled_images)",
"execution_count": 9,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 9,
"data": {
"text/plain": "150"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "fn = labeled_images[0]\nfn.parts",
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 10,
"data": {
"text/plain": "('data', 'pill', 'test', 'good', '001.png')"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "def label_func(fn): \n return segmentation_path/f'{fn.parts[3]}-{fn.stem}_mask{fn.suffix}'",
"execution_count": 11,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "dls = SegmentationDataLoaders.from_label_func(\n path, bs=1, fnames=labeled_images, label_func=label_func, codes=no_combined)",
"execution_count": 12,
"outputs": [
{
"output_type": "stream",
"text": "/home/hiromi/tools/miniconda3/envs/mariner/lib/python3.9/site-packages/torch/_tensor.py:575: UserWarning: floor_divide is deprecated, and will be removed in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values.\nTo keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). (Triggered internally at /pytorch/aten/src/ATen/native/BinaryOps.cpp:467.)\n return torch.floor_divide(self, other)\n",
"name": "stderr"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "dls.show_batch()",
"execution_count": 13,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 216x216 with 1 Axes>",
"image/png": 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24nps0DLa5xxjCkE8Ois1RUtomX9fEXpe3oLxMRd37nWRDLcrqb+9CDgvV6l2qVovgEeQOCsIZUaR9YMVhdjNRxua6lC4I6/9yyAqyrQwa462TkeavK3sIHb04J5Z7Btd7fsiGalRlnVly7R4vzqBNEHJ3/set5NiRjo7peGJF7LGEjm1VlgIwsbHl3MbJAnLlTrSeUM98tgfH2wlpYRtYTRMoEU9a/zputjdNDgJSvihBwA8uuyckpgbAil+d3RSEhIYtDN/cuE52itlarS3Vi5VnGigBjKShdD6+v19meH9Rsl8olGIH3Wf+jtJGbXO6MhKP1py2omm/671usCtICzn+Lo8s5ww298wb07xcStthFnjDX2Ot824psrSx2EYsNls3OplK+UnSCVE72k/tnHYrkcOT7H/JY47jKREmdywCpSPYYMeJjRw4qjEYNsiRuvjMUCcIhRJdLL/lj41jEiTC1OQlinyg+QQy9+IY0eNLXv7pd+WAt+SlNhn+Q3xm0UrbKDg/Pa+puqXKhQfl95DtLG8eFl0rW4gcvTte8YPl2JOLkd64KjgcdpX2VK05Km12ylIdz0cJ1aXgRb3oKa9E5Y8cLAP3ENXkmljQJjEdvc0++QyEBWoHqM0bV7vfNMosovRmSiNIMjH1lKQoRC3LQg9Hbq5H6O/aVrlMIw4PzvDMBR8/nyFaZqQs7N8oYGBPKEgoFtT0gUdkm30tc6rh/ZlGlPFLY/yQDkwtQ9mC7y63sKpmg6o8jVPM2bMjUeUzocJG5b7ae22BK9ej6zYcZgchQcZI5OGfsBTY83CQL5C0EPBcpSBopRZqoR8zRo+RcftKVc6aor5b5y+i6L0wss6YfIlEymtS7+lSF7DoHHVcRgxDEXvieAOg6DuMI7YbLfYbDY4OdmBQbi+usL9fi8DO0+Y5hmojMoV0zThcDhgmis4xZozn4dhxMluh2mesN9X8BKG0fTcNMEFtUMU+0YRQ+8NFburZQNGSbnDOQi9SFLN/Thk+bHfG/FOVRhYHRdg4AnLzqWUiPUBKC4c3Cm4HtDsXMlkG70pAGWKwQBQG0JZ70k9hlbcaXxnRk21GQvUsBM0KfJ21irQporOlkVIt+MG290W2+0Wu+0W43aL3XaDzbgBFcI4bDCMA7iKMIIrChHKMKAMBcNmIy5KkQnRi5dfY64VXBl1nlRwKqbDhP39He7u99jvD9gf9tjf3+N+f8DhcMA8z6iVcXZ2hm+++QZ397f46cefwNPUKKz0pATPfJLcuwuNcwRH+b6MTtwzXnEWrA5NszCGgCaZTePeCGsSjHBPpECf59Zfjwpx3gkcEYq4QSUtxzaC3XEWkFRFIhQi1CxtXdkeCeJzz2QrnN2SlZ/DhKxc5EI3jiN22x3Ozk9xcnqC7WaLk90O25MNNuOIMowowyAonCxRE/GrE+bDXrY57Q+olVFOtyBS9KaCkSUUwTy6fz5PE+r5CSoLz6dpxjxNmOcZ81xxv9/j9uZW6isFAxE246h5uLXpe7ZGxPmokxaRzfuJeY1Zw8TmZoKiAskAr+48yajWCq+DlvnEjSXu8Sk/9LAAA088ZDt8SetgMgU1Cwc17TcuQHq89maSrcMUcmpJzCuI7oswZuJ6K9mgRiQJBonk5v5ku8X5+TnOzs9xenaK05MTbLcirFQKSGsoQ8FQBpQygIYYAbdQZcBAhDoP2BPAd3cgAoahYCwDxlGelaPQRQAqV4AJXGdxV8oIlAFVLV8jlpUxTTOYKypX3N2eYrvd4urqCjc3t7i7vxdFUGtY7NBupJ3qbttzBCO7A4Tskye5U3cPPgHNI0JqrVEZbapnRqawpi3SxjC2wpt/fdileDhOzOIL2vsq3B+ljsBWRuNmmnW4QFvF2Q41s5NgtAx25thaJ1NVLtxdBFhHrBTCZtzg5PQEFxcXuLy8xOmZCMM4DoLIirKFGKWMgL7KYSgDymDRBdtSXpMxMaOsArvbAbudCP1YxE8uBWUYlc4ZBaPmeMgzzABKgWOcyoXlYmy3irpgnJ6e4vLyEtM84/7+HtfX1/j86TOuPl+hMnBxcYHpcMDN7Q3u7u51y39Yrd5y0QpfG7arAGdj5/zuzu3IfnJ2f+GrrV7Q6+8PcomR5lxy9Xokiw1LM5zvddbdJj/uhiWXvvUEAjbzBG7hDbgemCJYIP94V93Ma/iqEGEYBx/0Z5eXOLu4wO5ki9FyGaigkKCXCaO4GAU0jiBI2E2QOYY7vCbrMIMJ2NIJeFNRpwnzfo+6n8HTjO3pqXirRCi0cVdQPKtZ8MZiqfqDvOtjEB9a3QYGo1TGOAyoAE5PT/D8+TMcXr/Eh3fvcXt7DzBQzs/x7Pkz3N7c4OrqCrd39xIZsS1aC3TrhNiE1JE7jXvD7yPP+8isuJZRQzfuUn4pusfF+OHcCaTJmqKUJbSIMKlfVUVohnEE14q51q7NWMqt7TKPtJPjvZw+dLHGZiFP6+27ZpOzYSg4OznFxeUFnj17hstnF9idnGokYUAZAFBBAeTUxyJoS0SCLAQMo/iyIHh8mcxqFErejGstmApQZjk7oU5C4zyDK4F5B4a9BsA2R1o8txingmdgVHVoMLC2JYJcK4vbAeU/KsZxBH81YzPe4HB/QAVQZkI5O8PJbotPnz/j/YeP4Nl41y6MWHpleHkdSqGV4X6IejfBnsihs1ZIc1/zBG4xqmsV+/V4iC09b3vKAHhMlN3cM+ZpioWFTskjwmGM0c4k/7j5PSO8WdcVBtnxdeJ/Dthuttjttvjq+XM8//ornJ6dYjOOGMcBVEZBV5IwWFEElrc/FXGdoFYPFUSD1y2CbC9pidwKJkZhE0DbCj+AWMJh2MkvpYwYhlFcChoaxZBuFTe1RBVgCfOVoeURWICECqOoqzEXBleAa8Vud4KhjDIxnCvmueJwOOCwvwcRYZ4rrq6vMU+zILvyUf5vmYl50OHjm4emQUq7n8aJotq2WDeJz8Js3m/zkP12dPHkUSE204ykmYiewPTZiE8+TupDdDvfTT5xI9hofvf1A5IQUFuvfCuFsN1scXl5gZcvX+Di4gK7kx3GUWO4JP6sILBM2IZhkK1KitziCsWiQ6HB66eGZJdodyzIfD1STKmMoQBls0EZR32UQGXwcBvy7J4YwACgiretbZtwE1UfYJuXeN4xFxAqKlli0oDNRlFaD4KptWK/3+Ow3+Pi8gJX19f4+OETrq6usD9MkeVHQPisaezdd033zB0xtE4D4/3ibsR71Hb+tW5o63u3wrx2PYrER+9r3LGPIQY6GkH5nWStj2OLCvKNGyZmTaZUd26MCmG33eL58+d49eolLi8vsNluNIogAzoOtuGy6ObLjczVFF5JHdtCBGYV3EaxIn4sv5lWKV0VgLkc+t4MLuqTl8hrKGBAfWpZzHNkgCVNcS3uujUHbZOG8ZhU+GWSVrV9s3xF+w3WV7ZB49HM2GxHzNMO5/UMX734Ct999x0+fPyItz//gg8fPmJ/kHBgVi5eLAfG8n0aRac5hK9186yafOhkg8ZNnQocjXtxXICBJ2Sx+fJEWtFq/wpj15d0++XK1lRE0Dz24/U5yU4DGS0icNvNBs+ePcPrb1/j+fPn2G5l8aGUAWNR18DcBhViguzwKNC9fRQWxdb6bFOBhKdIVuG0j+b05dBhXl4WXU0LNzTo54pm5FRx1L76b4XMC5ZISoX0wcKYnr+dTkuqPAHMKChg0na0/+AKDITKM2otGKigYhASTggnJ1s8uzzHh/cf8e7dB3z89BH39/tmFTBAKBn+YNvKWJMruveYo7tukNOzOZYsSr+04/98JE51iZAm38xpZyfSH/OytFpXLsjZnOgeuFxPNlGkAf6vv/4Kr16/wLNnX2mUYRQzDYSrUCRkBkXdIg6olrPQnYouJzEjhqzalVhIoCIoCxOmvEPDcMdWvIpDIxtyUnHTCmbklU1SOK+zwSlJewAKm1swK7IXoM6N8ks31H9G0aaLbh6QcF1hmUxWGgSdlYYNGOcXFzg5PcXXL1/i/ft3+OXNL/j46RMOh8mFuTHvfXg1y0Ma6BQkWorMUgzM5nXtmVzw8qF0PbKzo2s9aGxpb+wLIScGOUFeJqtl6oQBvtZnQmuIM44DLi4u8M233+DFqxfYbTcYyoihFAzj6JESS1j3pWOLEZMilQozKQqSTk6LS2Rx6RyHdIoCVzDpNiiPg2oMXTehgoorplQyK4oWSABE6yNzudRFqSqoZQBVEfyaJYcKmAWhYcqqjCulpHEo4Qm5Oa7uKhUdF1tkIRpRBsY8F12t/AbPLi/x7u07vPn5F1xf3+hkPQa5jxXHOFskK7kBSWLd6HC+nQRoId1tIw85FI8udiw9CEqmwTakGFzr/zoEX9fcZC7IBDmTakJZcHp6itevX+HVN69wfn6OQd8nXXQZlwowFMl5ABV/k6Uga0YDAkFXybKRIvYBDyQVJBNFYg2tmf6JAFoN9gpgU1BSBM4HIEZf1fQaWlVgng5grhqnBuZ6AEDSJ0VgUaaqL4FRDjICebOVoKrWxZbEs/0fMJgKDQVVlWPWhaXziwHb3RYXFxd4+/Yd3r59i9vbe1SNTK0JMGCTTNVnExbOJdIHNpnpzDeS+9FIyUN7nR+NEwdK+mJd9nMzg3rXwwokZcsEJupDWzn8IyJgM27w1VfP8e133+H518+xHUeQ+rRUJDlpGAcMVHTmbzXLoHpGFg+YqxxSTTRKCAsFQE0qSC5YQn9R1IYLgvtrjrwqkIU0sNEGiMQSWC50LBwYwxQXUVU4SymWQyS7swm6G0UVo8oCIlgmdUwMGooqWH+kgCZrKTrXmtw2UjFmVVQQiNTSFGCgLYbnz2Rl8/wUb35+i0+fPmM/TeoO9VLSD6xLSrhcmbSE2vkJl7kkTkcO5WquR1fs1nwYpLGgxc0k/F0/rQOZbEfLFNoppeD8/AzffPsNXr54gdOzEwxjcffAknCGcUApo7uS4LQJkgNrzSngWsGD+mz2GlaP06pgcTxBmNWvNQ80rIwJDqDq4OCTUMgPKTEKpGZBd0HUSgSggAZZ4iZmjDTowYQxCAYmuq4kjohNuohE8jMK6lUQE1BRPUuvlX4VMFiX2rkUWegR/wmFNyjPn2M3jHh/eoKf373H7d29v0i9H/e27UBWP8SFEw/zkw3JvbMhXBvGAceuJyTFa9WGxiacC5eBnNhmHBeds/ra02XkOcJmkInbd7/6Ds+eX2Kz2UporMT5ZBZKGsqQFMmXPQQt6qTOgQiHuBpDGDEeAJph+cQe9WX4oS+ZiYSqYTHtMzk2O3KzH3ZRZVWM2GPCrrxsdVq+DPsEyl0aj5uaXRV4tr5ZNb7jhI2P2SSyI14Ii0zybEmbU5TDrkIEDCMwS/LQOE04AfDq+XOc7nZ48+49Pn6+wjzPblmWMd0Y1x5hLdrReB1sbZdGyJOwoH85UL4ezWLLYG6+cL8iR6mgC9KSErSGov1IRDg9OcHrly/x6vVLnF2cY7vdasKMrMYN4ygLFMW2+li9Fe5n1RlcZ0khZfELi9bveRVMAM09WCp5tUEPJkkGstOJ/JNrsj5v9hKQY5lm2b1RNlvYRDJCemopWOqnUmQZmwjA0HhpzeTO4awqvTYINXE9dsH4oDmza/JZ8+CahQCAIn3fjOB5wrwZMU4zeL/H5ckptt/tcH72CW/ff8Dt3Z33m0GmN+tCnT5mryNLyTAMoEI4HA7tXIoZ0+GAY9fTzmLT8ZFAOjcyaO20ngtHZzLFXUlSaShEuDg/x7ffvMbziwtsNdY7DAPKWHTSZrFfcyusphyiEzSu04Q6z6BhlKVZbYxUKE3RCKyImrexq9sB6BJx7gjrpoCInQZCzOo2qDkusnInBUtjdFMEFaRKVpQP3PyqfNOoBxl6onhUpIa06zP6W3RIxyJi1YbKMRoE1gktEUuqKQp4s8GmigWotUoO89kpdqc7nJzs8NPPv+Dz1bWKRJ/MnsbYPncY5t1TquY6YywhkuEI9vLVXo8enlJtcgRDm0BiUmTIdPfIvXQlGvjFZhjw/PkzvH71EqebDQYApVaUyhiG0qIvoBtLoVqcFh4sXGY+jwuv5kUEfMIGXLDVVg0lzFXnCXzYo4Iwbk8koUcRXPqsW5fcGjHMz52hCd+FQBjELJfwsO0qYA+zzfOMyjNG2gmtusoWLoiZWBEmf1so1KCowBIVedcIFN0Blxp2VUm+PWxFkALQwd4/Ig1dgkC6VD9NE2gYsDnZYdztsDvZ4ac3P+P9h484HCYHPFEadr5BW/aMRDUVMRxSplbG4XBIgo3u/+vXw0JcCsjT9jjgv1MLo41oUUXXfCABEWG32+H161d4+eJr7LZb0DxjGAs2mx3Gk12kRuoO5LzGHssNsXPB0JPGLajMbp4aZUqnB0kV1QWf64x5v8d8dQUMo7RfCkBDRBi0qsgotqp0QYXhQuhhJAr6CpH7oM7LYpMWxR1iT0Ly6jUeLKRyFFdDwJysX+a9KTcZAKUQaRq8WHlUoddFoYEADDofmSZYumgZB2w2L7A7OcHJyQnevPkF9/u92wNPKTXZCexJiz1Gi8bbkf37p18PCrEkhkR1OTdUlClchLVT0OPKLoS4BOfnZ/jVr77DixdfYdR9aAMRhnGDcRgwbmR3hZwnbM/rtvrkw7ibG7MDYBxQmGCLDICa0y7bzBWASBYzWLYUzfOMMgzuWpDGb32A3G6amJKjEFMSYIrAPzXD0o6U5VOYinv4y/oIkgUKiow222zJ/lQs+zoSKlGufCqAOcoispOUSvtCpWJAEVQfBtQyoIyjeSgoXCVC9OwSJ6c7bLcb/PDDT7i5vfOdO3ZyfutTWKgy8SHHiFsOpeu4WD9h2ZkdwJo0uvZj94zdbc2oLf9eXl7iL/7i13jx8gXGzYhaZ5RSsBkHkAmuoS/SS0nUDDUox2Yak+EscIE1vOTw2hwVqpl/1kSZwwHz/Z3sYzNnrIg5r7aI0hm6OAZL2mnOVFB0MbaRMq2aP6p0iG8L30EjP+qihfvTsowtqCzCbAn2DLYUaFfOvOyfE9uJAFSKY3eBxBd1JxhAysUg2FFTI1j/k5VFgGbCuDnHv/6LX2Oz2eAPf/geVzc3ke9h1imHJFzBelnxzmN5HQfJx88nti4eaSNoMFgxLbcHgoGlEJ4/f45f/2d/gRdff43tdgRYFy0GC5+l1TbYRMkEWSWrWyGDr8IZ2RLu8rgkbDFUFMBipwAkRsoeXQaXgmFTQOPGoyA2uZP/+jf9hI8aAGquV4u+Jt9xGhFp0rvljGSEtjq0j5R8a+2b1WsrhMYjS9c00y1VWqhQYxn6DBhps2+EsTgIEeUqBOISQqyJSlWdnpPdDt98+xoE4A/f/4Dr61sMw4B5njFNU6o0rfFSbivzpbsfarZ6PSkVs/G1SLbt1LnGpEIZ6yasybmDh8ieXT7Dr3/9a3z99VfYbDc+cESyQlWS72sIZZorwOp+DHyJ2MJLhmod+gvfzKxZWCtR5ymlcvzq9uxMUG6zRdluYEvSgqLRN/PpWgE23wZpwDiiBaoE4hNqX5kBnuUgFKvVdo245TMgsABaDqO1KYvNwLPsmLad1vJbdRZ5hIWLD1vEOIbY0UzRR/mf8H7wGHsFyoiTkxO8eP0SDOCnn97g7m6PeZ6SPDnXlC+Uh+rI9ZD4yvVoiC1bOA//6Ol3yWB1jdovZlIKnl1e4Nd/8Ss8/+oSm2E0XUzoG7Ff9x8prdczvIz5tMKIKsirTZbsxiwlVqINAMDidpiZIyLwsJHlaxa6hJLIkUCmDTEJSaDoSmMhLa6yO5mGAtIdHXIaezzJxlPlAxjqW5s7AJQSuRjSw4payX3+QGtVcCJQFeF1/0nrIrM+6nJ4+E0tqqOkJS9Zn/TgjgJCpSpCXqtMTEkmf6enp3j9zUuUoeAP//RH3N65zwIg/HNKNFl2YMPDZMdaWFpej789ya4VH8tIGMeNbMXxe/FuZELB+dkZvvvuW1xcnMsRpirosgJHPtnr8BMWMajzATxN8pllpSjWFmRbj86nFA3NJZHstBh6gx8GlXBJYt+k0lFGESZzIouF2RRbWXch62ibYFeeJcZcdZJYZ/B8wHzYYz5McmiKLXKwpF8eDnvMBzkYhWd5r7GshhnLCf/+r38Rlwq6vE4kaF2AiGCYRTGroehaBt21ov325e42nbO1IGZB1Z20NjU/WiaiBVQ2GHYnGLYblFF2zYzDiJOTU7x8/RL/6l9/h7PTU09aMv7ZUJj7JfJtLpuxnYL/IRGr1xPOncihoiRjRgg0ttf8AGfCbrfFt999g8tnF5qcrpMOQkw+0j2rhllW3fhwQFWTSJtBDzCR8xmIaiyd2pGj3nza0qPtWFTBk3jcxEPRk51upjzAuW/szA6XRhdI6uznPojFkrKVgcHCePMsSTnqHs3TAfd3e5SxgIbBGAcuhN/89VsAstDw7/7ye9BQ8Pf/+Ep+J8J8mML9UjQUMsVnBUh2OlWKuG2xeHqAkAmw29Y0mTfFt3R9UQJxEeSsjMFBu+hsuDJhu93i1etXOOz3+Kc//CjJ9gGz3nS4dGme04Gln3F35Ho0iy2bNNdYCCPcD0+reDH5ED/4xYuv8fz5Mznafhj0zLLRz3eg9Ewz82egThX1fo/pfi/1bTcYdjuAZR0BZPRpDZbFRqQn38jnkulXSa8Kvx5648kVAgUgRT57sw8BnsvrISFmEGmSkLs9Mtysy96Ws8tg8HQAg0QR2Sa7BeM4YJ4OID1E5Td//RbDsAHzBpUrDnd3GsEZ8G//838CjRuAK6b93o/L+o//969EkWYW92ywVT6yPae6Yp18fFhozky+ZN1FdM9CkDVcAAZkcsuNUBaCRnBksYoB7E5O8OqbV7i5ucNPb96KhXHh1DwNCuUJtSJNESW3fA9dT9ie5HIl/eyPOTI5cgkhJ/CZbtzcbjficuhGTcsT8O3wKvSSLsguEMRy4g3XKiZ5f8BYK3DKriTixsXEJNAoBDpikpI7UCebSJkJre6ecCGUmumbnEbppkwmyaPVNgByPgQR/MBsUiVjCALX/QHMjGG7BW8s+27AOM6o0wH/3V+/A0rBfJBwWuUJ8zTjcDigzlPMGw77ZLQqQBv8u3/zPZgZv/39N2AUDDSisSQWY06TzPg/wecOnNyIJDyBlebqyS4TjfM5WoMk44zmAh6B84tLfPerb3F7e4cPHz/Dsu08pm5VelQrhPzhmERcj0cnOC+akgvZaln9SyS7j1++eoHT0xNZwNgIEg/2QsSQsXBYgo/wHbzDoC52kSSQOyko+b4Fw6B+oC6f2vycdTCI82CIaZ4nOZVSJkccL3e0LWpDcV+SQD5zIMAVot16rqtYQ/Xd1FK6yh64ecJ8c4vD7T3qPGNzeorNxTlokKXi6XDAf/9f/YTDQV0rMMrhIIsGRfvrCfIWRze/VAW7CAr+T//uA4gKfvv715oXxS6A+fBwwNweczxyJMLCkSZbVtIwk0V5wucw7oghowIMsrVqHEdcPr/EN9++xN3dPW7v7kXgzVsjW2jSWtRSZgcj7PP69fjhKS5cqSo6/gwgs9SvvpLTdsbNBuM4avpkikAkNyXcTmOOMk0nVaUUzLo0ypOuqg3iH7OZeFUFzwzrKifSyVidwPOsbsYgh5IoMlWKcJ+s0ql66WfUlI8LDiYXUsUsKEVMvWyclvMn5gNw2B8wHSZQlZOBeJJt8v/tX/4Tpv0e8yTHCmCWOHYtjDIOEq8GfPMn0eD7Ban7l/n/P/71W/zt777GPMdEknkGYdAkqOrHEqSpCdjcsDx5NzeLCPF6swFxzKgJm03MzIWTyft2u8XXL17i86cr7N+8ky1P+pj7vQl3TVHQ1H78esIxVvnzMZ0wLZTOnp6c4MWrl9jsthjG0bfQq2zCjbN914mGrKEroqpfWoYBdRgBiF9cuQKHCWU4oAwHse60AQZqGahk+WzY2tTKByqgoWBMOQmCsPogQV5CqTnMYvEkWhJqJw9SKSibUXdkEFAt0FdR64AybrC7vMTm5IC6P2DY7VC2G/zNv/ked7cTCHJ6kuwVhLsyZaBmspdPm/cThFpSfOFIBGiUCfL+HtP9HlxnlHEjPjVBFMUtocSwLZbuSq/WDFBFQAEwh/lX1C5JLkh0USJRLOfPnZ+f4/XrV/j86RpX13Mzj1p1ehWImuXpI9cjPrGYRJWGByozhJZ9YV9//RXOz84wah6E5UCED2Fcp1St+KxmTk3YSCcpVACaVYm4oh4OqOUOvBk0bEUSrUAcyOc5vFCzyclZTQn2Fl1uFowkQQAW/7QfuAygOsvuZK7AMOpSOYELq4m3HcVy8ImEn05RdztwZZQyqIDblinz2yWxhpLAOt+cdUlyU+hqKAQUOyBGdmjIJlIWl+X2Fvu7e4wnO4ynpxg2o+KS1CeAOPtk2xNCGZYJqoZN6LXDUOVe1bSE4oBklrAQJEQ5FlxcXuD5Vxe4ubuXkGknUqQy5JtvqStw5HrEnTCTctwrSUYHAGO323o0ovhmztbseWzQwgYOypGcEnPVAcN2h+0FK5pUWJZpnWu850MFP3wtZ0vjX8mLUizWOUaEpKgLoSbODh6xeoqWqcyoPGG6vcE8VWxOT7A5G/RoKgnnhRKpBPgxAcWXhP/mL3/E/q5KJAGqpG4xdAeKWq/wFNRtIIvWxhg0SA0CSM5bvjsc1MoxpptbzPu9hPnOz1CGjU8+s29ddXYq+dYxumQ+ckBkuAQWIiWLaEiZImELVBqw3e3w/KvneP/+E67nOeqwQeOc4IROwI/7sI9HJ1zdQjPDT27dYyLC5eUFTk52GDeaD+GpkDJ7N6eeIS6VO/ZkkyEVNmWEpwTuTlA2G/As8Vg+TL6ZEgxduRvSRMOS5X2qt+ifnIRZgCRElmNBGm4yVyRmzBp/tTh1TTwptilfw3dFhN9ix+bjSNRBhKsUOfTFwo925IAoFeCbANJEzvxYn3yloZaohijQPFdRdABlGDFstpju77HnG3GpTuSsN9lNrRNStRQVM6q6R6wxOkduh1AVXsCtasPDYudgyJiP44jLywtcXpzh9m4vB08245JX6QIebQ5y7Hra4SlZLQgd3MNNzmYc8fz5M02t3KD4CTgmGNz4OpbjKiZkFiFETO2ENxzoM0iiOVcGbcT0ySF9gJzNwM6w2Bpv5IdbIWUiIcfCy+LvaupnjmGqfyy0SHLQ5mLAhvXhHKkwM0P+0gF3AeSgQEaBngk3z+EPD3Fe3EADoC5U0aR+ccmin6a4JgbNYTXMmOcJh8O9gF0pKOMG22cXKHcbzPsD5vuD0LUdQYOlNBPYcywsakDaPc11gC2pI8YO5MJsgu4iY9alDCilYrvd4dmzS3z4eIW7/R4ZIEzA7DGLZ3MS7rXraVv27buOtu24bQqCcHp6ojuTB1+pJQ2HOSMQfrDMhu1QEUPR7NBDQ0QabKciaZaDLg2D/KwGI8SdH9bVNAveu+bYIoc0zhXASLonT3zyQhZ0UuEwE2q0FfKDUGB+NzFYz4uwkotAvfGtyGEw00GOaCWuKJDk+2Hcqi+b31oqp9Cb1RG5LJhn9tdRyKLF5C7b3/7uBZgraCCxeGNBqQNGT7yyeDkDdJD87S1QtjFFI12NE+tZEJM8AwBdkLBFFVP6tBMcygPPaCbg7OwUp6c77A8HkQmyI4OzK9GGMR/yjJ/0ugMfAw5CsoYIUwnn5+e6O3lIh3yoHwzdaGOmtdhQR73hS0GXccU0s+UcDCMA890GR2hJLdREIIQCwHcfqyIFXDafReADXSTPWFla7WSfmhhJsWO46YOrqBwqyFHeJkO2fMaA9E8PmrBwFIhReVaLsQEgC0eVK7gC02EPMDCe7DDXSekTHkgCf8Hf//5bMIfPScOAgq12rqLqm5sYwLyfUA8zNtsNNuen2BRZ8rZQKLtbBji0+p4/jSglF8KFV5G5gACSneJEcsjN7vQEFxdn+Pz5BpNObpdi2iP08etp5070yJuaNL9sGEZcXJ77kVKA+nNQ9AOQt7+gZ455Fiw+5DwddOJWUQ9idjbbLXizwbCR2Kn71kAQmKyqxJ0NnT087wVMdQL5dShUtkzYRN8084trc9ql9E8YZFhSmP0githhbQF+xlwr5mn2e8MwYrPZqOsgyD4UWeQZx1GeYZINsHXGb3//Ws/hGIQehsZ+rbfVTb65RqUMwLgBTghcGfO9nmR/OEg9paCMg7t7QqvxlML9QnW+BaOzN6v85SiFNN52hvTlxTl+2bzHXOcQVkIIlgIlDEweuJ607GzjkOlkjkRuAmG33eBkt7NgFTzRJ6QddlhfchqsBe131QWJ2dGizlUWBli2S20sLlt0p4OHnyiEK3HDQkKsAmiH6UXHFFncSui6PYWFMDcDQNSlbpIITghM5MqK2wFfMSPxq9NgTnoMqx3y7VEHkr4M44jNbsTh/qBaNePv/uG1oHVlTbgx5lo/q46PDVd1AaIyoIyMsh2xoYJiy9eFULY7WVghfXeIPU9hOdLgt3z2s+JsHHV10E4UVRmRaJUI8fmlnCF9d7/3as2fbn2wdiFk7Xo8ASjY1NwzLTE/+WS3wzAMOqju0MqQmgwUQtHkETEXwmRHZFKCzZTNcrgJEXQGndb/ATSbPlVhLG1EfOEK8AA0g610mcuiA191TV+E3noqtPoaIqkvjRASAnvM1FDKUamq40Li90rToiy+f9EFT2hWRoEwyHYtPZ3zP/zuJVAnUJG6pDc2X+gQSz9UzhmICiqkce9dwbAdMe62sks6Hf7tYc5kftl7ZhM5k4EYijiaiiXV1Y77AnRuNMjevZGx3e5werLDp0/XYJ5j3tKJK2cgPHI9MZ84T5j8lg6A+GwnJyfySgGz8QzUuWK+v8fh5hrT7S3q4SAEG6051ggdQ0WiMg7Y7HbYbGV7eBkHjBvJvYChqcGFbiaNnSVGs56FZkKlbVZm8Fz1NErxHSQfOXOLJZqgKZ3Cj/DdZKh0lQuqCH68k+UeqHBqDoO0T/jNf/NGXSyGnBY0a2RFwmkDye6ZcTPKEnWt+Pf/9ZvELpv9z6oQrK41+/wB6F3A6rwatluZQG42GE9OsTk9xXiyRRl0Y6i9F4SjPwTA34mXtp7ZO1gIpHsQoRItCu75z2r1zOoMQ8HJyU7j5OQKI8VtDAFqJonr1+NIHNLVaUSgYClCUBznr4NWZ0y3t5jv7mS5k87k5TR2fCpZeCunBkoH7NVZhgqsAlIUncJNMWG2iIJEGYqfpBM+qZQXX5A4Jkw1VReKLyiSvWdTDuu3GJSqqO+irsWr+8ysVoerHptlSsjKpyEGETxrVh5jv590F03qqpLg6Z9OH6XxUUuX+cOKpkRAGVDIEFzrUl+cq0YTnG9zGHMOh0mhunEr8n4+NscqWUtZSJTvsgtkh3Eo8mpgt2bhPMSc5+F0zMdzJ5yBhvfpr/JkGOQdxiWtGEnDijJzBZOYDNZdGE61CjRz8n5McyVrU0zwTM40W4RgtmVqiyAYycVjDWR0s+Q9zIcDppsbVCrA6SmG7Qa1uDZh1pBc0UGUyAccxYqZ/PTSFumXbQ8B4qhVshliisAU/O3vXuJv/os/aPkQYEk7HXT5Gpimg+yRg/DtN3/1c0gyAb/9/WtPPw35Jvh+xzTwEWUQEXEXiMw1iKEVNyFP4EJ/bfXPd0WTTYwtnTUazfOKOKdO/g5lwMnJqaTT8gHt4obPLNBGhdavx0Ns1jG3TcknVDSVt2Wqb8dtqIVRZCeDvnIAPss1VbAJgamdajfleQElBqPluNNp3rDFLe3tR2r2Of4dbu5AVbLFMOnuiM0Wterp6JTNm6GULktrDnMgBvtElAjSV08LY7BOeszpowGyMYIojTel/7P3d5omHPZ72JECMqHSZexS8Ju/+hl//w/fINaCTamTVYAha5xcZPFzbz0DiHMseJ6jPD5uSVgZVd+3pzF4H0+KoJFN9tis94DNdotxMy6tvE9SDTD+BYsdQTGwVov5L0MRn7RW8c8GfUUAiORtmvOI4WSLshkBC7sl8xd5DfadQoChZn/UlTROg63KwkyodfZZvcWSYyyVqYBmnA3g/YR5rkCpoEMFlYP6tLFpMiYwsto0mELR4D4eV9lRXHWWTYNmtBEBlSSCIPIs8V/3bPJKlN5UC8XMmKYJ036PaX8f4KCxZOIBQ9m2p0hqtMhcF+jYhGGP8WImFC6OG9Z+Euv0p5UwMS6B6GaUxBUpsIl4Ky8RxrRFDTZBHofURnIbuKXmITR+8mJH3n8GwA+0jt3CJpyGeLL4MG63wGaDYWcnXNoqVGaU9zUiF4BrsgXUrZBimjJHu5gFNtOFAHmRnYJxtwOPW2xOT0GbETQOQCXIiuCQ6LN3fZQmmUmoiAgBGKjTAdP9HsNuh9E3ZhZU2vjCSZ1l+5FYXV8w1nrClZKDXPbhQ4NgJ+KXUlB0mZoAd828f/o+Z6vb5xTOL8DkvqQ2UQilqiDbZM2E3HfzmJLoXMGtbrI8HJgdn1TSC4C5OtJa3oYJAuc2jc4mkrB+PcmdYFiiDGBnfjncQ88XIxEQskQekmVTLltYaqEdose2DX6FLmaAbLVJZ7JWZyCKrZhZxyVJRd5JUSE2Ox3El88lBjDsdiIUG93rN9jBefFuZ2tDBFuiBayIJwhc/VUBNBSU7dZDPVwr6r3kLQynp8BQgLliur0DA7I9yaIIJArBmJ0vpC4KgbDZnPjpS6T0jKOch1HnWNTIgiCTQWr4Sy7MkLa4YsaobhdsvulC3OGviqMlAinIJK/FRc3OlVN/OdBVci9IeUeD7d7OLiFig26iIHB//XokASgZPPOBIYw0/zJW5+CbFiW7TITWE0ME0JwFkhDUWHqDSvkzHUSAt9vogqGgj0/12a8tbHseA9hRiXSGSDyAyuT+eey+lv16o6826msQiqGz+KAieCRb75W9FaJsZbfFZrMxmwnabHUzrfiGdZ6xv5H0ze3lhYfryI8cMDWzxQ7dWaIoSQghLoO6TymcBos3u1CHafbZPZmCmGhIWVkOTyhKSBNDd/bANR186GPPIXjMsMURa0E+2Mqtgp5u4fLYtJczgSUvS0mYj12PHmPle/m0U9S5EfIZaVAENeK8B61H951lt0AsmWZcu93Xrfa+Ty1SKa0NwysdVW3CGlRBUOFiy/TioAUEzZ8Vhg/DKMfpl1g1E9pSCEkPmqjMicFGs0zYLHJohxBKIVnsqQyMp2cYuMpGSgBgsyhprxxRRO81yb5Q8cPGmRk8SSpnneRA8Thayz1cZDRzl4H1GwW2ujXQcY5ThkyiKNWWJuUE2Du9gVl35ORIi40xA1QtSKN5HDZGJvCty9BOMe3+PxeJm+eF4ELkmVPW17nOmPRkdJdcgnaqBFHWZ2UiSpBpQmOCSSR78oXhetaaMdwjB0EDA6DKEp7ywRH4b7bC2AC6wBR1lWKxREwyYwCh6t46G0rJdsuDDLc2ZhrZ4rBsCCgu2LjbClIVp94tB1SYo18yOS46oTWAm+cJ82HCdHeHaZLPZRxT+lIcQEjUoqsJjH1UYy/zgeRuOP653Nhv8at8sl0/OVmnfZ+HZ7hB0wVYgIXVErgsuepl98J68i9B4rBUMDNnb3bP7cyzvAxbVRkZBWzwbXIW8mQfDE1jEidtGhIHKRHrNDYDLLs3xTAPEZ8GoGd9EWzbkh/1o0JlAiyJZfqbfQajVs3o4tmtQCSIcyiKnglncdKwHFUPvpYVSEDcBFcqjQeHgqk/T7o0TKTnT4jy1PmAeZoxTQf8h//jhaRxDtZfjfnoe6CzELK6EIGitihkZSQ016SIJ3A0x8N7zgzX7CT4UOV3Pz0BoAy1lBzKiMM8idzohlkrnse7H/9j19N2dqRmPKif3IJZlztjmTIFxAF4onkmiNQtSKjKmXRDykS9LC2r4Nq2HmjCjm2vZ3tW2yXAFlhMkWy7v23HIT1LwuxqvHiGZWm6AGh8bwQaQ5HUkUqRp8o5GjxNYHMHSpFqZiNTNqu2kiN8EyE20WQdcMli+7vfvwSGGZ7cb7ToSilRSix13zWZZIvZGs/NHXR3DDEHSvwPE8/tjex+6GsTAPZzNspmFPdKXY5xlFey3d/eygnz3iY7L1Otj+DwE153kKMRgi5Bt/W51iqnu9jWocF2dFg9GkGIG1qFqXIIAtwPRewkUK5WZtlOz4rEFu5LqE0pwMxAxDBTCqEGvERA0hnA5kwYQpkCS26QKWX4dwDHap4zJQl2ncHzDPKd2IpqmhBkSugbXBLvmRmFirhpc8VkQsz2PpG8WOIP6R9yIDCf3McwzV0qS1zfVsXsKACfFwCw2XcIdLhr5lJ4WVN0lZvKcWBM2YqSEUmS2DQdcHtzG6/f7Vw+ZyW3fFm7nnS0a6hECr2kmmudsd/vF0+bG2JVFITJ8oSQ5Gtl6uNRNdUaCiJA0dMGTJlWSPfpsTPTGBr0ZP9QFTQfQ8D2OtpsgSjMs4m6KZ0d02oCQkWiJVVMJGlMF2XwLVQhBGLV5nkGDWnDu/vbRS1bxcxV3iVChL/7h+8AzNFvfSYyA0MjyFJPjZXKa666944tTDeLIo8aKSm+3u/uhrlm0DWAcKWyhSUdK+P9AJRZclXGUQCG5dDE/f0d7u7vMM3melDbf0Q/OI/RyvUkn3jtq6Oltnt3t8c0zcmX0smSAZMKT7aci1ckmPAiM4fjQBQiM9a+RcqVgXqHJSTRgvMiOIlwvWzZAi6MpMCga0vavlx6NoMNqB2qklDE3jAqpwgNnlpqQPibv/oZ9zcBEEQlTemEs7KYNIArYWZRir//BznE2iIaADs/TJiVjep2WQIAuTB66IzEwrBl8hW2ELgQxTUG1+tW8bS9d8xIsu2c9FEsg+zG0Sy9oiFQJsJhLwcp1pTg1DsslG49hMZPW7ELeXJBzC4UM+Og211sR4Q5D3kd3ydtgCNZAGPYjmalR8taRMFq18gWWtFVZLUAtMctxVrU6YB5f4j9cmVoUcoUwQcuz4yNsTaYoWjs/zN2qZ87mAUK9pkgMXRVs9h8QZUnca1qS1Xj3REBKCp0VQMdaRnI47TV6zVrkVddSQ9Bkckn60ZdkoWZZg2AQ7H9oETliw5CWi+EHUgo7+eDnr2Xj8uVCfb+cI+7+3txZ5DcVOdhfDAAOnY9nE+MQDvPRuo1g4U59/d7TNMBALuvFU5CZx688iDOBIk4i32FzNiLh6/sfW+F7PhrVtm3JUvxr5plYW203h9wuLlBnc0kzu7aBJIbnRIKY4KcJaEI5iJtCTc2GfFd1iJAUMSxOiML0J6zvYOmqGjMmwACY57kiNvf/u5V8zwhVkErhxC4qUe8msC4aW6gjqQZS+kfUWz7hilrgAQrOFfW/XxoV1EjHZPiaSKUcQSN8lZXm5XM84zDYcbdvfjLHlN23lqDWTlw9HpQiNcf7APRcu0PE25vb2WCZ4k0zSxQB4CNMQQ7pETy0jkxPQRSYorV3RI5nKR6MjY0q0s6n9SGsvsiZ6/RZpQcjnRotpRe+lusmWOiXEqxm02NwSqTbOCq0WCDALVJHBIqP0mLVd9+qmYgmWwW/3HWRY1mF4jZg+ATkqCBWTaPpgT97N+DdbVVvYVCAOkrh1lXhQjsK2kWUpNxMMGWX6qGEINu8jG0F7yzKhs5agNznXB/f4/9fkpS5NoFav+3FLbuelCIAxI5NaC+oOuzGsl5xtXnK0yHg6Iww9MfAeTJVo402zzYfDdpzhemAZD6bVJH1g1mE5rqM3IP66km510OZRxQttvI8TQXhqMfrdmynQsmYzrARi8la6WMFr9SFaiL7NiSsM/0a/WVQHOjVFOFh0Sa2mlplKLQJvyhK6rQrJM2OwpWOWypkcUthREB5VhRdtkWKlMWqdOy+2yMpAyrFmTrJ2BlS/mFNH/GMhrtcMi54ub2DtOc5lCNkHZjkuRs7XpYiJNpMFMUGmLoJAyqzLi+vsX9Xl42YosihkSsmhuWgzVUxuoqkJe3mbY6ELDVp4hnJRNJkVklQjBnndNSZt4K8tH/2a8N8wVfWvbJnO0Bc7+V1fePlE/5meFnLpP5p+QDa+z+7T++lgHV2LFNaMnrUKUrdoKShuiSYgv9GrXxkWbUw4Q6HSTcaVbDAQW6CZZCAUvR1+Da9iqpd9YjE1j76Rbeog8ez5VkKw+N+jOmPHbwIQOFMM8SH776fO3+MLKnZV/IYv151rN+PSzEZooS8tkVJoodqe/u97i6+oxpmjyEk8Wp8TlVkFnRLpBXEcklUTUeJhBhTj2ko4HQhX/lCcpJj1nNmoav2MUgcjQytYAiiVsUQarKrAOW8CIKuDDYPr3GCdNxKnrYYsTQdQKrqC0z94q/+/2rxP+8eJFkSaBdfh80vTQjJFzOk98sL/KqHOjrOUSGhL4knsJ5yhdzotoYtFk4EeJaxXLMFeBacXd3g48fP+L6+g4hvUmwGvTpXIwj16MhtlYMEwYqwf4aJ2LUecLH9x/x7OIS4zhiHEZUqnJiI8wk2FvrDW2NJYlYzRtw9ltfrXxAD0KwlR0sy8zif1Ww5gWQ+t4WWCcmMeVFBjX6x/DQh617OSPDD6YkHLKBkhpuZzOZD+aKSYuiYDEzq8jtlgWo06TumU5SPeGGzQMR0dXz4IjIJ1HNO6uhLJKwgUKXuDIGknJ4YTozxMivtlXdhiAWhjze5ItSMRaBH7rXsDAO+ztcffqIN29+xl7f4QzlZ1y0+vEhMX7cJ07w64sN7ud5z2Caen1zi6vra1lhmmv4xwmLqjYtY+nsQkZBm+3GO+CgW9VVcC3MY14GmzBWZ6pBDzPAM8sRAPqCmEjeJlclVxhmgKye6LTTpOhjppqQVu5MUJLPKSXkyAGLhJgLZScZEZG+Jkzaq1A0n/Pcgp288J+lnx5vtYgIVdlck9wR+ZmcZ4XsJZjFXR6LggkZZta15x5DDwBxF4PhfXYaK0Dqcs3TjOurz3j39i0+frhqoldrl/XZxg8PlH7EnciPcop4UIM02iqYgcM048OHj9jf3WOeDmFaK9KmTXvQJmqzxh810cVnw+YLZpzWgSMdyBRecrRzZgoneZ7k9JxZ8zv0RZJFJztDIRns5Bf7kbGU8UzyRsT9CRtSWU+cYCs162dLWleRs71JpMJVoEIiO0qGMuqxBxrbZstHUTRVC4DEE9YTPSOV1GjVZWUmjejV8EGNR7ZB1i1BBidSz4BUqmG+iG6CKN7/+GeWJuLrhAKmwV/r8OnjFe41tLaUtV6olHMUY7p2PSrEy0q9akcv0Ro1KZVx9fkanz59wn46YJon1FmD6l42o/O87JBpC1m2mC6R2tkOubMWl/WUFwmm5/V4P8tNV9fAmiUm8aU4asAGCwGkLthsmyDjfuYrKVp7QJ/g7kEoLXQJesDf/1/fquAWOQdtt8U4DhgGOc5KXemgKSW7N4To4TN2+J+7K5WBWt3tEaRPrlfKN2lDjqr4nvhvdw0gPJUenoRvYVBXMCnPJNNAIjmD5PPVNT5+utHDzrvxNhfPLK1byWb6vXo9nMWWENO7kkyG/Z+UYHO+DtOEd2/f4/z8DEMRZBlAcrIjpEy8ElVjh+QGN4gOj0AjFkEL1zDpMnu2LTlV3A6KvVs0jhLO4ipHmCbkG0Y7VVNeNCMv+lY/jpAGpjnQPwadCZRcGFkwTNxRBRC/MN4v8j/82w+os7x3xF5mWTTmLAia47DKJ7NkqryhzEIDg+UtqXraZRlHWOJT7IGMwbVJHgyVq/ZXXQNiaAYfe7dN4CpHRqOMlx4yjooZltwkr9atdcbnzx/x049vmmOrgp3GS2vEpCK5QSvIbdcTN4om7dCPpm3WOWr4w7i6vsG7t+/kPApLKyxAHHRloTQEoLpcJJ+2J0EaiD4n89qsHrGaXNvUWAjgAcNGBXjc+jYqa4BQ9eTOWH42bLB8WusfQ8x10YkOdAlZyKbklsjZGzSqsrMonSSIh/m2+LuFBqZpj/3+Dr/93WuMGsXyiE0xvKA0LKyGR31w84MdLCKew10/HOULwd5TYnwhLWehxew2xLuszQ+XECMz+w6gAsLt3Q3e/PgTPn66joAAtePXjLW27LfYp5Cr1xOEOB52hXHti+9eUvtZa8Xbdx+wOznB118rC+sGrAdJ00CSNUMmgFojATY5yx01jHb0tQgEs+/dM2a0zo9kwRHIV/ZIE+Erz8Asu7LRuCo2UCq+dkxWqpc91GQWQJGJivPADxUf5WwFc6NID9ZDUfQFa/KUJLxPc8X+7hb1MMlB5ZaHbMts3k8TAG9Q+FBIX/ZYYlDUSrrKEyR7ThFVUguQdp2Y4Car4/dDCMjHybaNFTkGQSeuh8M93v78C37+5b1snDC+ElBoaNyQLG5uczh1+Mj1tFTMNKix61YHtSYdMcVUN2S/P+DnNz+DwLh89gy73QnqdoNxo2ElIueZi44nlAQNzAQmOcK0KKSbd2Gn7VDU0HRYDp4sMaNmRp3FPxbcLRrLZQUk2bNmfrW/pSi6J/Q5a3QQ3WW1D2RWWQU8Bo89VVNU93DYY39/L6/GqrPulJnw9//ntxhGay+EyXZyiBtnfMhjJoJs+iTJ6OrDN7HtQd2mhHI5Bm2xd+1PHhk78srLlwLfX2Iu0Tzj44f3+P77n3B9c4+I4+tQIM1dkpwBaFJ0k4O5ej3hPXbcfFeuwFdogEZ88sUM3Nze482bXzDNE55dPsMpnaOUgqrr6eEFy2y8ONKm0EojRARbQfPO6SAZc/0XI9f7YElBsmO5MGCvfG0bqaldcSQ8AcpKEpxurhAhSUvW9iZUyaFN9UNyJv72dy/wm796g2k2CyAMIz2X7T/+P7/COA7ho1rYF/DoBQBPh3QLYggJ0mgEPI/XM9AsTRbcCj+ZyyOjUnUSLo+HLITrAkgOdfDElXyacXt7ix/++AM+fPi8mChmS5JdhTXcfdiZeBISk/9tiWjFQz2dIIkFCWpl3Nzeg959QgGhDEO8WamKWSddkhSUKL4pMhYTjEEMaG5tFNKlXh1MJGTJ8UXSgSBjywxUmn3buPew8b9Eenx3iLctqFhVKExbxKDO/rwlvQA5w852UAB/+/tX+Jv/8nvUadL3M/8rOaQcjKGQDx4jKQizn98RYyIJN74jHRJ5sQSmABtyy2J5IFXrdM74YoXyFoAcAGnWADoBnNtwnI0/FfAsCT4//fgDfvzpLQ72uq80JskjacCSQXFWXyeJx64nvMeur0aaXUQu8swu+TUgEeTrm1uUQhhsJm5+ofqjZVZ0UV+3GqpYlfkrMezYJuFEDdj1AzuS/ww0SIp5BqYJGAegbPxl2AD7OElxnbT52VNJORhqTll3rKiFsAJmJPRj1bJu+vXr//6P38jJQEPBuCnqI+tlZ5eRKa9OkH0SUlsXRyuX+YfGqhUpM9xUmAsU66baoCojeZdF35K1svCoVlfUtZT+Dpqhdotf3rzBH//wI+7v9u3cjQA7IrbZdQMBGRMp8rash8evJ0zsQnjJv4cGekcpTK6haFoHQ62Mq+tblPIB43aDcbuVhGkawDyAy6wzdgJl2+kCkjA/CWjrccSKlrI4JaSbWddMsFnew1xSBVbGglcZxRREVQBFsCSfl1PdwTPLrpN4jA5ahfizhULI5gkEOZPYTb6BOwE2qRRWcAr5EXgOSSLAl3oNF4MmVqFM+SGcexnj7AtI2kbsLzBkLnK+HOuij6702cT27uYaP37/R/zhDz/i+ubeswBdbho/IbdPrtyi+K0j+5A/8SdM7NqZrVdvDetvuek480DuzbXi0+crbDYjTnanGAaZeYwjABowcNUk77Z+sg5nP9SZoIhC0C09yc9mjsmGVcQAyoByMmi+gJplg1ddFRO67QxfalcBVWJcyF2wrN/xnORxGG+U5FmTYvZ7zPuDJAHVQd7TN2zCv/ddH8rVGuNhSf+WyG5b8H3MGGBdkTTBiB3dVmOExmzy2I6gbYpttEOeLLph15bJ64zbm2v88Mc/4p/+6Qfc3N6H9ct1IACuncDDaTFrkO8/hMWPInHo6VIVOGmSv20ICCFX825oDZYXBL57/xHDMOCbb1/j9OwM4A1G6PuNyJZoKd4vZ3LjYlPV8rEe0Bc+lssrBbuMC5w3imahdoDgJiuM2bKTI4GnZ6m06arivPKjDZidT3J+BIO4Yt7vsb+9wTzNKMOAzWYLmmaMO/Z85zJCFyn0OK6qeRBuDVTA2fhPfs8p5VCyAKMIabJuEPTdO8youlghPEpmP7kQDNLFGdu5fIMfv/8Bf/jjj7i7vW8MZyc1QBqThqWdNWtuP7A96UlxYo6Piopt+wsyTZCKuRvJKSI5Q+HnX95hmg747lff4uz8Qn1R2YdVik2EIlfA46Rsn+E+sdPk02QjIjHNidZBSehoZtIWWUT2LOkl1YeYUIngs9cDICEP+zO2n48hsfM6zeD5gPvraxxu7mT2P26lr/OMstl6eqZU0WbSVRM6u2X77wDIqpkzKzkLlPotIOBjpB/apX/NwWDL9eZOKGWVs9aKw17Sb3/84Qf8+MMvuLvfN3VxcBnNXV5+Xkfbx3D4USFOkJ5QMX6N6GzfTDvxC59OfhNBfvf+E6Zpxne/+hYXl8+AbfVz0eyddPLO5GqQApkIJnOahin+2koULSYP0r4ha7YvM4hl+TqSW0zvWH1TxF0VakvFt/ioYSDD0kFZT+uSODTPMw639zjc3mHWN0SVWsHE2J2dwbfyZHOfoSJZPLazKwji71q2WXPcj+0KsQpia4ycFk+BOvrXD8Iy057cD4n1yukv+8MdPn38iD/8v9/jl7fvdcGmlUizkz6XyHxduBTdmFADoUevR5E4dEjZ2fU50RvWOfF8bQUZgJrWio+frrDfT3j9+g4vXnyN7ckOI28BHlEG0tMsA5ltYAVk01IoRYNNJm0yIwT2k4PEBEeubFve0D333rbuiAWIZWIdBiLYGzbNBvpJQjqAXGdMh3AjZvWdadxg3J2gbLdNtlYgWgXbu6YTgskqpPaNnPQEKq2v71v2m0EzhePM2ZhzKSIzw7cpTdOE/f4eH95/wB//+AM+frzy1TjvbxrxTn797poAJ+4LTb583j8f15NyJ5ZEiL9on+N41zCrgXq99gXBltF2c3uDP35/wM3NDV69fonz8wvg5AQbjJCMMxVe9WUlNKQrh+oHet1sGK1IaEYAatoraZKOTCIt3CPnR3AQqTudPTLQmb/QDROONjPLFcKUXYV43u9x2Mu7OJiBcbPF9vQUmxON1oANImNl1GTQjjkwZHWACF/fJmh54NWjQeQ65HFUGPAoC4fwQtwPrrJdaZ5nzLXi9uYGP//0Bj/99AtublMEwjGgFWATy1YOF7DWPJHh09l85HrSYgc3oqc1JhqMyXbK+nSYGsY2/XIHNlCbmTBNE355+x63t3d4/folXrx6AdAZysAYuMgrFdRftomcCXEsh+vB2va+42LhH22MSV0T2NQl0MAG3MDIbrsgsffJ2BtnMyQFzQicyrPRM0rm2jzJGWTDZoNxt5F8YFsFZVtJy5lrVRccI1cDYH1XHRwx7agt47dZJVtAqM0EKe84ET5l5LNxnyrjsD9gf7jHzdU1fvzhJ7x99zGOoEpXOAQmOwFdD8KpX7z4av07dv1pPrHV35k0M7PzLCta7K2G5i8I6VTTZtHXN7fYf/8T7u/3eP3tNzg9PUUdR/A4YtAX/JWhoGGMK0qasCAWZJrkHW5sQeqHmk1Ho/QCGTXJviTOcOES4CK3CKGgplipJSoYtzucPi8o1yMYwO70FONm68qTFwHqXMUKmUC7WAXKSwiNfFIrq3vsHoQ/wXMMggu8fE5ZtG52q6Zl1jrh7vYGN1c3+PDxI968eYvr61vMOcG+Gc7khzQy9JgAL7HanuM0bmvXIwcKdm4EIXZnOFLkslkohDseJGhokIrddUp5mFwZ+/0eP735Bbe3d/jmm1d49vwrYMdgPYnedxgbAmudZsoE4VV0s0AFZcEw9c1j9Y8QZ6YpklRGpCa2M/X27U+dG5Vm9gy1VFvbIDqCiVGGDUC63c9jg0qpGTw9p0AsTTYTWm9SWgMUG4UYAITydeBoPi8TdBVSFqf293f4/PEDPrz/gPcfPuPztR0AGG0H4qaxbRror6Wwxp1jgvzw9UhSfBIuGxNrhlVQ7Niipm1DJEoI3nDNAK3rKnvd8zzjw8dPuL29xcuXV3j1+hVOz87F7DJUmEscWsMcfh0Q8JJasd9smdmElKByUqsshevxU/lxVwhFO5tUUuqHZ3yZr6PI7rNzAlDlONeB7F67uaaUEHyU0qxduvz5HKD6fec89ytxkdDjZYxFSpuctMS+1C8H/t3jw7u3+PHHN/j48Qr3h0kjnLkxxBJyEuTWyj0kmG3JZbmnuSJPyGILRLaZeYBYXgRIz6mJa5UyUDkbnCximW5DjLv7PX786WdcXd3g9euXePbVV6gnFaO+QUhm7UKpCQCBPC8AyBRWb1kEMW88ldKVJbtNIhikgf20AGDah6pHyiZhR8RbhW/24u6EVsoL0uNv/eg0RcE47IWAlLPAJs6+s5sgiamaRioDoqTpCqbRT+Gb5gkSs7agdKLKu/Nub67w/t17/PTTz/j46RrzvIxqJGMUffN7WfB6YW6/R5htTUipe3b9evSQbelsNJxNiM+cU5t9KMVQK9MVbkQWMIM07p4F5lmWq29u7/D8w0e8evUSF5eXui9tlJfdEEHeoES+8wEwYTCUrJ5Nwcw6adPpnUKl7FUz4auYGY64QBxxKkqteb1uARiWRBPsV7QhQ0nzVoq7UWTojrD+ggOWN2IHQbC3rTEVAXdHmoRrishysN8AUrdJFC0pB0uq6cwV+7s7fPrwAT/9+Abv3n/C/f7g6ZxZIBzpUz/bYV8TuCPCbID3gJA+5mL8SUnxcit0jw19VtrK6GSXzbit9y6z5t8i/R5PucDsDwe8ffcBV1fX+Oqr53j58gXOLy4wbDYYSsEwFozDxpN6AultySGhoZpzo0liyOJHyCk5MRkrHH7w4jyFtMZOmpvceDKJH7YSXdIpQSKbDPM3bAWtglyfmauabeT0B/mt6sYpjXk3m11BsEMNbckb6u/afGKujGm6w83VJ7z56We8ffsB1zd3fhrQYvy7774EvmKR2/L8wPeHhfSx6/GT4oFEZCLWibey8JGLNMjlYPbm27eJERxh2tJJuFWY7u73ePPzW3z69Blff/0cL16+xNnZGRgbdwGICIO+K83ixuSEpsAXkyujE8s6l/PNqdbJsErmKliyD2EGN1ECSKjPEtJTT2oSfuu7H1NQ7H18SqGd7UvQNzLJwdj+oG7fiEgIHK1tEOY6g2c9aalWTIcJM8vBLHc3d3j/4T3e/vIeV9e3yXXIsWbr89LSLm/010MCG4GBLFqP19FejycAsRuo5L9oxY1/nJ8KlHagMhRmhh2NZHpwnP48XQhHBiyrRze397i7/xmfPl3h1asXOD8/x8npKTYbibtW3siZEu42QPIyYI3G5EzoiWXjomY8FgMQ77mwlT79IaeOSqqzCG8lgHwLj7FAB4QDIGyyyGBBffOVazoDDpIpFmMZaZLkLlRM3zLGVD0fba6MaX+P29sbXH3+jA8fPuLTp2vc3N61fm83ZGlY1wW5L/Tg9xjLBSgurt6PXr+euNuZUtPmYyIWEtAnkNDi8fDj4MwAElPIJlFpAHpu2YApNXLwHeHq+gZ3d/cYxwHn52f4+utnuLi8xHZ3inEzYhgKhhKLCaCiEzVDL3LEJpZdIrLjgeARAPVUKSkfNDoTShuLFEBSCueVUm6Hi9iKYvWMY8/PDX8bboHEF5i9H/5uQCQFQ9qEVeAnXu4Pe9zd3uDTx4/45edf8OnTjfq8nfAaKK0IznLVbE1g+98ecjOOXF7t09yMJ5w7kVAEy86xm127msBV8hesLJqQnPmlSTZjHuhCHWGcYZBN/3WW18bKoSqMPct5F3f3e3z6dIXLizM8e/4M5xfnOD0TdC7DAB63LngDFXnjlitVaL67NhQDIfJkCm3xAvLVsHAhI3vDO5WXi73jCAFVS2AkuPNmrgEzuE6yA3ojrxGQ24lGkkWKWU9TolJwf7jD9dW1xHrfv8fnz9fpcGsO8my4OhlIw/IIArf8Oy68C39kWeRPlPun5U40Lkl88ZBZR0d8TUiEnhHaUWOcSzUaPjTeCORlhOFLtQhiWLQ/HPDuwyd8/HSF3W6Li4tzPHt2gctnz7HdzRgGOfGnDgUDD/6ydduhICgpQtCkd9rys0b7ZVJDPrl2TyHzikzwGXaULXRPYHRS7plfG+Gw0HxL0qnTrGyzCZtZQ+hbrCoOhz0Ohz2uP3/C+/cf8enTFW5u93IAOnPLu6xnnfClhE//Ld9pXYs11Oyt8zEVOfZ8ANhD15OE2E1l63FFQwl0kdHbzGdDo8UGqVUOdzlaeY4apLC/ZmCdUn9K/MAZ080tbm/v8O79B5ydvsXFxTkun13i9OwU2+3WUz+LbqAsdsAfgHipoK742cTfIgSWnqmOvXXdznGLyZv9Ts5FSuTmA/+kvEUiTC3N1RiAzVYiw7PuACSA54rDdMD9/T2uP3/Gx4+fcHV1jevrW+xzfgOHOwezPMSN0rUjmxdOskvp1S1pzrC+GJu18Xr4Wov299cT99iFCc3YuPCRshlMjzaWOv2egx5Nzdnl0EEuVLo37fS4kawDxWeQnoFwmPHx8BmfP1/jzc9vcXqyw/nZKc4vznB2dobdyQnGzUY3sBYQDfEqAEPoavFo9adrDXWiTJcJrWl28MsWcTy7ziSf9ODuObbvM8t5L8aLyrHdap4mTPczDtMBtzfX+PTpCp8/XeFa3w3nB8EsD6ZIgJFNP8MtZ9OdXrAf5P6iVNT2uMA+dC398bj+hBOAcmdsHZ+bUtm8NMjSuAYRq83+ViD4SmdZVsystGODjlHyWOX3bM4Z8f4J1vPNDhWHwwGfr64xvC3YbjY4Odni9OwUp6enOD05xXa3xbgZMWqeAxChO6hSlWIHt8h9mRiaGaFQWmZ4MhHUlyYzlLY0zS64OYw3z7KBoFZ5GeP93S3ubu9wc3eHm+sb3N7e4u5+j2mKUy9bdyGZt5WxydsCGsFsXIW1a02qmhFtxqT9/ti1dDMeeupP8olzdb7kHC5Zg8SZBkYqQ8HTnOUldbJ3oVkezc+nHiUPBbGq1vtxlith9QejGQyeKqZpxu3dPT58vEIphM04Yrvb4uxkh93JCXYnO2xGST4aBwnfbbY7DMPobXgILofTtG1mYLAT4SvrRJZApfhRs4CE0GyiOk0z6nzA/X6PW42+2L/9YfKQmCN7y5Fgdvx4xMBbslYbYeLF4y1i95c6e227aPl9lL7FZTzNceTjYvykFbt4o2M2jS3B+VtDGuUud0Qzo0fz9pLyzX1dSKFCsr/M8mAXWo+G77y4SWHWTQlYZvfTVHF3f49Pn65k0aTIYdRy9OqIzWbE2ekJtrsdhmHAMJC/VMUaGscR8zxhmib5vtlg1IiCdF2EcJ5nfz3E/v4e94cDpsOE/f6AaZpwOMyY6+yrbC543A6/A27yHiwvOQPz8iJ/3m0aWZ2twObR6DHX4Of4NOyYn7wuyNSM+sMI/qQEIP9mSMfpb1q46KyRT8B798GYnFvqt71bQe7LUkI9RlImC1UlVtOyxhgochTLhMunZJKZcagVhwnAPXk/3pGYezvNR9yLEIJx3KDOs5/FS6Sv2VL0rMxAhbzy1l74Yq4EoxEFbmhcwVxOXe2s4oN2mBLfcnVJoK3dHP7Tp1Z4+zRnoSXg4Sfa05zWr0cSgHrzS+hCwus00fEiRnN4hHGTVpgSApw1pJtscFIkdASu8Mni0v3sWlyj1GtF6uxjOt4zAMyYjS/trwDuF31pGZSFJ9uxvnj2BVzFGt5kenuEXKPBOc9mN4+XDaVJaLToS0NV25b2wRaLANt1vaKMud1UzRq85etJ0YkIuEtd4zjKa2Zn4VqDlmvK5f0NLnOHssKf1kVxYQ3HSP5fgc04Yq56CDWtNarlFxlS7eSpGXZTsEZusqTrYCyELytjCIZHI5o+WZ2PYJaVy7SoknnrqYqmN48BXAHiZdRriJprywMrv4XY5if6+gxBg0e2OtqP5/Iy2Wih4aHuPHBp4riaaRO4au9/SGjGieFr8RAHks7c2WO9G6GVJr+Mmt+nedIJW6rUiyjUJuReDgaaexbGYkCPpuJOqZJ5bj+sXuaLJpHzP7HgQP4vDihhK9TWZ892bVD6bPq1PNO3ZXy7p5VWygRqrvQsFCr1P1ZeO58G2SVIq4RN+/2YJGFfsmJxPSjEFPU1zfj27J6YLDNtN4TBGcRKl8KZHvL72ZXoOsLyLt0VNlMqLxOboRTfMd0jRUNpVgJQc1QrkJmZ0XmpYO4qLACXmxVAC7D5fSRg6Pu71svMluaZVnjWQKC3TsvfHkJLG+goawLaClxG3jVBNZU4Rgu5WD3k9DwoxD7Z6vohqMBm8ZcsSgqtOuiehCtqp17e0czDpTRrbe3fkPHWp8mTqabT9torryTZ7ER7v7jTcQAtTJgLsfbbEcK7vmYhMHdrRZ4XA3rUmXoQwTIyUfdv2ZqMXVrg8u5Ri8hHKVr5TrSy/zPaIDM/zftJltej7kT+k+tR/RNGG8p6xzh4RLl8W23+GgS3zUWObEJQjk7Kcuw67czw8JSs9jECGaxYZ7ZdyfqOc/r/mlrJ/ezL9T69GRzP10lPg+I5tQNe54rNaO432OVNp+epL7Xy4CMXp//HOo5DFEyYfZSo25DbKIhp6tLCuhWjUOo2WrK8HnYnvN5k6jkLV2a6PpPuN24yEMf8LkRgaVT0h+5zGhTVEDIWsgmL/POByylxTpcmlreVaTNrMNnV4NVSX6Qzqb24oXEzTKhz0ZYcaihyrDwCnCa3oTjk9K6v2/Z9zfeC7uyuc6KT0rMx/ggBRHuqUDvsKvir85Us3FrmuAw/4WWMHIibpLqdGTcx3jRC9jc92zr+Ud9CiikPRkpc8ZZy7gYpknltR7SX0581tUl0L0xsMpnZxPQWWKXGaVC6+kiCD1eSUJ9cZn6tKhhCObsuLHpFGR3t1lIi3Cmgtr+UiGzmOgnMOp3rCLAVymBIPLE20Vu5VhE7rsdfi5s+R0gs9qeZ6ZAy1AqbmVPKdHTIRiGAzTzEpZKaW63pzkjbk70mpFmBDDIe5EBXT6cpaD/2GNaibNvQQ1ZnwYb0SyhHV8OCDS1VebIYSkKNQq6QqXUXZz2lMg1o+M1ct2lwX98DwJqA0j/9S5HYiW3QNH4L1JNv+X10eRAaIYUaIPJPXlkzKcyrNRkhcqOZq34j9/iYqcSRe/l5XpbTxZDQMUMWWQhKE/bVxZRjV7AtBLVF1PSxQbywLsvIAGwdSGSJ+l+bhtv6+743Ats22FgVDuuZmwhrnXbBLJrOnW7H4AHWPS7EdKzj6BjEwXgfgExQ53u2RIXW5gOdWZknypxgoO9RL8PoQz3WF6OhjwM3Bj5+b+rPIcFgdo/6UrTrC3p+LBiw2pnWMi1L5OHN3D3Gnmwd+jWYZDz1r7kXrYlorQIlPiQ0t98bTcy/M1xZlxQ2JeV91njwetq7nRmN2UHqqJPYIYWhlI9enhU0Zl2bWPG78jOLhJCVxYx8rvCakCz85IaEVsL65XVDF2OzHaeVZ9CmCqWQ7h6xgeqSmLrur+F+f4NyyR6lkZUczTC5JTZWcvDYi+fvaZhcSdLwtfiaPi34beK5ZgUpAKp5lJsn/C6t8CZdTwix9Zvo08NE/vrTPGsN0jrUbPyGzmA1UGWjnKnPSpD+pt9jRSjR1ACq3VhmafDRb9Qosbk2G02gtz77ahXZiuYsZ7ytjXDDKzR19DrWRgS6kVhoRkd+ks6e182kWB9ajgecxT2/nIPWb/R1tpaovZKWJD9zKSpmJvLYL69HV+wKkWdnmZm2f9VPkgkK3DykRm0w7IyHxQIOwtTXpkJTAh3d/jdvl9t79gQh+YGWvtjWGQi6ICjVqYJsasCysyJ2miyNuaF+r3ZtK+TGyvmyNlZpLHMdjdlNjSzGoNNJMnRdoeyYqBwzYm0d/RO5lNmwNcFeUiLtqQ2jhxTiCQlANZ9XBizCRXnlbk1jhXB2LlP3S+6E0u0KCka8mNtcCGY/1n8NH1rm2ZIBI5GwMO+RZijuARkhudpEBgieJ+zuUmOTyd5Fs3AdGiqPoYuRw6rcbBHXdrBjxWxNSairzzQB8XIf9ltt88thSVc3ykZb6n4LJfaMDIDNozg31By3mxpuePvPROLgsSEoe8Xu8zqtitjpnseEGfCt7lEFwoQlJHOtI/hrBTIzqDU1rRinoSRyQaTE5FCdTsOdYUiv1WrL+2QnDXyojH6q7BtF1+KbbfbjOrrkxM7gSaChI7FPvizkSY3RahGene4urym1a31qFTj71WY9+gl/4/aooLdQQt75qJ39P+dNAzHk2H1chB/1iWMQmg6u+DAAO7NaF8aERUUiQE/uu9kLDedWLJpPLTWaGZt5Tt0iSNf9ZoLaKFI2y5oK6DjeCmNeicqo5YPmCtxe3vdUU1Aa5ZfHSHXWzxcYGHG2LXVlkIStmyz1wmtGDqYD1JTLhnAZ3aCmPhkpcgyhxWgmaOiHlfMOHaM7JVMduR52J2yQm6Xb1iz7REpvGkAbcvsOiu4KS5uZIHU16HjUpOUn4l5MEJPtQktjQ0e8SFqLKVUPPZeli0zQo5pEVHQ2C2NGsRz0bR62oefk2bS/LWhpmrT+t5DZ41pP6gKkuet+GMxgWwI6Z+Gi7mjXNyAAARYKLo08NZ8XXfTrYXcCLRMcdDhrdlDcl/QOqnsQCE1+r0UF40xC5wZVCe0DadtMb+OcjB4Rs0KmnFVYHV1p80k7JjqudD8EMncji06n+soSedkFbBCSlo+EJeppX4PwtcbRhAcXRZXl1sSxanw4W51pOuwbg5sxDTCMyJIjSuLF0rLZ9Uh0ohW0OJEqCS5lYn0E9X4eDehraPXBWN6BJYus4EDHrFSmd/ZXAusNRrtNWhvUrp7408SvF8O/xtcO/BpowloP2Y2GfKVQqtSOAUIfbYojuNrT4HPPGkOXuumLVYgxtYgUKEVWjCepnpWRSvXGmNrktJl6ZLgj+2cWOJWgJXisXU9Y7IhBzDoiv0RikL9gJVvGjAb6L4teFhDqOrdE3fy7MbxF1dD6lkoCmvfDObNC55SuhX1pkLZrrdWnqGpFT1bQL/+0gvJNey6oIWhmbbl5hpsKMuj548nAGUb5s1oolN7qIawAaPyeWl+MWMccE878tP3WnpJP/rMI+XFpfjQ6EYdft22a0FEurD80RqHhsul8SmRBO1tdhlNWiLd+J64tNzLas/0Zy8uqXWjy84mMjIAmOGssTToh31NVjaHqn2nHTP+mSY39ls01Be/dTektZ9aGXgMTLTG5Vuofhb9++pUgyC1wH9ul1f5nQHSJbVppy61dj+dOHOO8oq8hT2+tLfwTLknqtnbUNTxrXiOIR0jPNjWqXCkXfSB9rlUsYVwD6I2tTnJB7b1FXkT3u1e/TllPYnMJpx4LLnGiJfenpf+R5rWmgOSc77ASYPEnfNHIBSA1TWvPBlo3e/x8fnWcUAYezJ94wh67hJO9pQajsxYNOvQmoZnSakURysq1OAXpbx6cfnSUQavQkyxEYnp0o4PjtSsFdwPx5JvFso1N/tf9wHUtawFxbdknSj7uF64LwEPy62mSnRL7xMu0vR/zjAJJAHPuxiI8np6Jwxo5LIjJgzVtYBPq9WBnnpAUnxEya33863lMiwI68+wDmVaSa+OPNlyzpeos0I2Pwl5XTL5iQ6bwb4kuwhhuAN3/OSkqYvm1Bz64nO7zCpNT6gtFkSQ7Rwcm925ZrLvD8cSaAhz5IY1H92PGgZWqQvvS4o+OzuJohfSs7d6BT+KlRLRO/luzSLYkfXE9aaOotRGJHiEJ3uc8MKt2KBfgeCb9GixN5cxkLurK5QAbckc2Q5kk3MTt8z4E3NaUONC4SxmgrMUFUqXfDUHsbysz1FbAy15R5mWyfqusQO/4GbUL5h25GJ0MettryhFnc4TUO/0m3Am3iBKY5Xo8KpFI9p9J63g4SvH4uROtdMFId0+B0C432+9Olf22HO3Q1xCq9YGwIrz4tZEMfzgpCVk/yJnSkEHK/mRaF2Oe5ChTSE0jS+hiRpuyDDQujUtqpiVLcFMu1702ohm3szQEfx+6IkC3tCr9wkYWdpvE9WsKdhIo+U5l42/S6qaRPoUgZKbdh7e8nrZRFFjdURyIpOb1SZV1TG5nVbn26HzzU0igR5cb7Y1Bs/Pa2joDPWJWn0al+xjoIghjy+W5U77+n8xs7lrjIz7JRIYVerjMyt3VxIhQ8kC+TmRa+I/H2q42dYHQvP2qrc+EO9VHZt0Jtg0mImBa1sq4goRCHLseP4uNpfXGsDDaRBY/0jSZBWm9ieU2GKxIk/3YBRM86ExGTVO9lEt3uL3vasXp2TWDYQhhTemPnlFnTRiI+FuUokFKzzVUEum76dqfepfDn+bEqUbxre5QkKWJ5ZbH6WkD9QYxl7jRMbf9Lbs3DHj8eu0cb9bvmfI8IWwbTf9nBQuOu/EKiPXrCYsdKzmvFA1qK4pA0fEwtZnUTHuWOOjzxW2XRze8M0ZES5vV3ib+dEWaSUjQ7GPZ6EDy25IRYIYIb7P4wa2bYg9xoElmgHXJ2qR+lN0yJKKSWZWvYUWWHkxr5RJ32nLtilR6HsevNUucwCpuPvL4gubuORsrCn5xiy6L69Fl52Y27zTnSkNyMwblhLr2CFVOz3D8ZiiRR1rVO/q3Fv6WO5vNiNPTU9j76lyT3WdASEjnDuT2mmiFWT4kOeWurvyxKQAfAFstXA5Dl/GXw1uLfuavR4SQ5YzlZDCxUmFUxC0Pj7Z55MrnmsaTAQAt4LLysuU5JVkAQ86ItuNw9TeZnP8zkbghsTHVOac0CYmOiCt6A1wr/mvuQM+IRkioeSQ65wRhnmcAHMdT2fNdo3mOGac0yptB7Xcr479rXY66HckLC2DKbzrbIBU1nx10jZeLK5m3xf3lPV78FCaZYH3SQk28dK261rfI4ynd66bibOUCPJwFiP/1VtP6n2PXXiH3qb0rZD7p8Iov15frP+Hrabudv1xfrv+Ery9C/OX6s7++CPGX68/++iLEX64/++uLEH+5/uyvL0L85fqzv/4/V9IMia9jLGwAAAAASUVORK5CYII=\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "os.environ['WANDB_NOTEBOOK_NAME'] = 'segmentation.ipynb'\nwandb.init(project='mariner');",
"execution_count": 14,
"outputs": [
{
"output_type": "stream",
"text": "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mhiromi\u001b[0m (use `wandb login --relogin` to force relogin)\n",
"name": "stderr"
},
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": "\n Tracking run with wandb version 0.11.2<br/>\n Syncing run <strong style=\"color:#cdcd00\">serene-field-5</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n Project page: <a href=\"https://wandb.ai/hiromi/mariner\" target=\"_blank\">https://wandb.ai/hiromi/mariner</a><br/>\n Run page: <a href=\"https://wandb.ai/hiromi/mariner/runs/1m364rv7\" target=\"_blank\">https://wandb.ai/hiromi/mariner/runs/1m364rv7</a><br/>\n Run data is saved locally in <code>/home/hiromi/git/mariner/wandb/run-20210809_193446-1m364rv7</code><br/><br/>\n "
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Monkey patch\n\nNoticed that `WandbCallback` is not properly using the class labels:\n\n![](images/before.png)\n\nI am planning on actually finding out where the disconnect is and create a PR to fastai, but for the time being, I monkey patched the function:\n\n![](images/after.png)\n\nThe line that seems to be the issue:\n\nhttps://github.com/fastai/fastai/blob/2cf7bd388c36b7b951a4f5754fb20ad13b50cf43/fastai/callback/wandb.py#L252"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "def modified_wandb_process(x:TensorImage, y:TensorMask, samples, outs):\n res = []\n codes = no_combined # TODO: Hardcoded codes. \n class_labels = {i:f'{c}' for i,c in enumerate(codes)} if codes is not None else None\n for s,o in zip(samples, outs):\n img = s[0].permute(1,2,0)\n masks = {}\n for t, capt in ((o[0], \"Prediction\"), (s[1], \"Ground Truth\")):\n masks[capt] = {'mask_data':t.numpy().astype(np.uint8)}\n if class_labels: masks[capt]['class_labels'] = class_labels\n res.append(wandb.Image(img, masks=masks))\n return {\"Modified Prediction Samples\":res}",
"execution_count": 15,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "def modified_log_predictions(self, preds):\n inp,preds,targs,out = preds\n b = tuplify(inp) + tuplify(targs)\n x,y,its,outs = self.valid_dl.show_results(b, out, show=False, max_n=self.n_preds)\n wandb.log(modified_wandb_process(x, y, its, outs), step=self._wandb_step)",
"execution_count": 16,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "original_log_predictions = WandbCallback.log_predictions ",
"execution_count": 17,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "WandbCallback.log_predictions = modified_log_predictions",
"execution_count": 18,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Training"
},
{
"metadata": {
"scrolled": true,
"trusted": true
},
"cell_type": "code",
"source": "learn = unet_learner(dls, resnet34, cbs=[WandbCallback(log_dataset=True, log_model=True), SaveModelCallback()])",
"execution_count": 19,
"outputs": [
{
"output_type": "stream",
"text": "/home/hiromi/tools/miniconda3/envs/mariner/lib/python3.9/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.)\n return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)\n",
"name": "stderr"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "learn.loss_func",
"execution_count": 20,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 20,
"data": {
"text/plain": "FlattenedLoss of CrossEntropyLoss()"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "learn.lr_find()",
"execution_count": 21,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": ""
},
"metadata": {}
},
{
"output_type": "stream",
"text": "/home/hiromi/fastai/fastai/fastai/callback/schedule.py:270: UserWarning: color is redundantly defined by the 'color' keyword argument and the fmt string \"ro\" (-> color='r'). The keyword argument will take precedence.\n ax.plot(val, idx, 'ro', label=nm, c=color)\n",
"name": "stderr"
},
{
"output_type": "execute_result",
"execution_count": 21,
"data": {
"text/plain": "SuggestedLRs(valley=0.00010964782268274575)"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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RoC+wFVgG/Mw5V+0agmZ2tZktMLMFeXmaMliaj99+vx+lByq474PVXpci0mBeBsE4YDHQERgCPGJmidUd6Jyb4pzLds5lp6frk57SfGSlxXHZ6EymLtzM8i1a5EZaJi+D4HLgNVdlLbAe6ONhPSINcuMpPUmNjeR/3lpBXmEpa3MLWbhxN//+agcfrNiu2Uyl2fNy+Ogm4BTgUzNrB/QGNCG8tDiJ0RH84rTe/Ob1ZYy456Mj9t97wSAmZHf2oDKR+gnk8NGXqBoNlGZmOcDvgQgA59xjwB+AZ8xsGWDArc65nYGqRySQJo3ojMNRWelIjIkgOTaSpJgIbp22lCc/W88FwzP0wTNptgIWBM65C+vYvxU4LVDXFwmmMJ9x0TFdj9g+eUwWt0xfypxvdnFcjzQPKhOpm+YaEgmgs4d0JC0+UstgSrOmIBAJoOiIMH48qiszV+exNldTWkvzpCAQCbAfj+pKZLiPpz9f73UpItVSEIgEWFp8FOOHdGT6ohz27NPaBtL8KAhEgmDymG6UlFfy4hebvC5F5AgKApEg6N0+geN7pvHsnA2UHah2JhURzygIRILkijFZ5BaW8vbSrV6XIvIdCgKRIDmxZzo92sbz5GfrcU7TTkjzoSAQCRKfz5g8JosVWwv49Gt9iF6aDwWBSBCdN6wTHZKiefCjNborkGZDQSASRFHhYVx3Ug8WbdrLbN0VSDOhIBAJsonZGXRMiuaBf+muQJoHBYFIkEWFh3H9yT1YvHkvn6zRinviPQWBiAcmDO9Mp+QYHvjoa90ViOcUBCIeiAz3ccPJPViyeS+zVuuuQLylIBDxyAXDM8hIieEBjSASjykIRDwSEebjxpN7sDQnn39/let1ORLCFAQiHjpvWAZdUmN5UH0F4iEFgYiHIsJ83HBSD5Ztyefztbu8LkdClIJAxGPnDO1IWnwUT36m5SzFGwoCEY9FhYdxsZazFA8pCESagYtGddFyluIZBYFIM5AWH8W5QzppOUvxhIJApJm4YkyWlrMUTygIRJoJLWcpXlEQiDQjB5ezfGeZlrOU4AlYEJjZU2aWa2bLazlmrJktNrMVZvZJoGoRaSlO7JlO9/Q4LWcpQRXIO4JngNNr2mlmycDfgbOdc/2BCQGsRaRF8PmMK8ZksXxLAV+s3+11ORIiAhYEzrnZQG1/k38EvOac2+Q/XpOtiADnDc0gOTaCJz/TUFIJDi/7CHoBKWY2y8wWmtklNR1oZleb2QIzW5CXpyl7pXWLiQzjx8d05V+rdrBmR6HX5UgI8DIIwoHhwPeBccDtZtarugOdc1Occ9nOuez09PRg1ijiicljsoiNCOOvH3/tdSkSArwMghzgA+fcPufcTmA2MNjDekSajZS4SC4/Lot3l23jq+0FXpcjrVy9gsDM4szM5/99LzM728wiGnntN4ExZhZuZrHAMcCqRr6nSKtx5fFZxEeG89ePdFcggVXfO4LZQLSZdQI+BC6malRQjczsJWAu0NvMcsxsspldY2bXADjnVgHvA0uBL4AnnHM1DjUVCTXJsZFcPiaL95ZvZ+VW3RVI4Fh9xiqb2SLn3DAzuxGIcc79n5ktds4NCXiFh8nOznYLFiwI9mVFPJG/v5wxf/43x3Zrw5RLsr0uR1owM1vonKv2L1F97wjMzI4FLgLe8W8La4riRKRmSTERXDmmGx+u3MHyLflelyOtVH2D4Cbg18DrzrkVZtYNmBmwqkTkW5ePySQxOpwH1VcgAVKvIHDOfeKcO9s592d/p/FO59xPA1ybiACJ0RFcdXw3Plq1g6U5e70uR1qh+o4aetHMEs0sDlgOrDSzXwW2NBE56LLjMkmOjeCut1aSW1DidTnSytT30VA/51wBMB54D8iiauSQiARBQnQEvz2zL0ty9jL2vlk8+NEaissOeF2WtBL1DYII/+cGxgMznHPlgKZGFAmiCdmd+ejnJ3JS77Y8+NHXnHTfLKYu2ExFpX4UpXHqGwSPAxuAOGC2mXUFNLBZJMi6tonjbxcNY/q1x9IxOYZbpi1l8rPzNWW1NEp9O4sfcs51cs6d6apsBE4KcG0iUoPhXVN57drR3HJ6b2atzuO95du9LklasPp2FieZ2V8OzgBqZvdTdXcgIh4xM64+vht92ifwx3dXUVJe4XVJ0kLV99HQU0AhMNH/VQA8HaiiRKR+wsN83HFWP3L27Nf6BdJg9Q2C7s653zvn1vm//gfoFsjCRKR+RvdI43v92vH3mWs1tFQapL5BsN/Mxhx8YWbHAfsDU5KIHK3fntmXsopK7v1gtdelSAsUXs/jrgGeM7Mk/+s9wKWBKUlEjlZmWhyXH5fFjs+fo2zjhUQWbYWkDDjlDhg00evypJmrVxA455YAg80s0f+6wMxuomoKaRFpBm5qtxiLeILIorKqDfmb4S3/TDAKA6nFUa1Q5pwr8H/CGODnAahHRBoodvY9xFD23Y3l++Hju7wpSFqMxixVaU1WhYg0Xn7O0W0X8WtMEOijjCLNSVLG0W0X8as1CMys0MwKqvkqBDoGqUYRqY9T7oCImO9scuExVdtFalFrZ7FzLiFYhYhIIx3sEP74Llx+Dlsq27Cs2884Qx3FUof6Dh8VkZZg0EQYNBED7v7nQj79Ko+RRaW0iY/yujJpxhrTRyAizdgvx/Vif3kFf5v5jdelSDOnIBBppXq0TWDC8M48P28jOXuKvS5HmjEFgUgrdtP3emIGf/nXGq9LkWZMQSDSinVIiuGy0Zm8/uUWvtqutaSkegoCkVbu2rHdSYgK5553VmklM6mWgkCklUuOjeTn3+vFp1/v5N1lWslMjhSwIDCzp8ws18yW13HcCDM7YGYXBKoWkVD341Fd6d8xkbveXkFR6QGvy5FmJpB3BM8Ap9d2gJmFAX8GPgxgHSIhLzzMx93jB5BbWMqD6jiWwwQsCJxzs4HddRx2IzAdyA1UHSJSZWiXFH44ogtPz9nAqm3qOJb/8qyPwMw6AecCj9bj2KvNbIGZLcjLywt8cSKt1C3jepMUE8Hv3lhOZaU6jqWKl53FDwK3Oucq6zrQOTfFOZftnMtOT08PfGUirVRKXCS3ndGHhRv3MG2RpqeWKl4GQTbwspltAC4A/m5m4z2sRyQkXDAsg+yuKfzvu6vYs6+s7hOk1fMsCJxzWc65TOdcJjANuM4594ZX9YiECp/P+MP4ARSUHODmqYspPVDhdUnisUAOH30JmAv0NrMcM5tsZteY2TWBuqaI1E/fDoncPX4As1bnccOLX1JeUecTWmnFAjYNtXPuwqM49rJA1SEi1btwZBfKDlTy+xkruOnlxfz1h0MID9NnTEOR1iMQCWGXjs6k7EAl97y7iogw4/6JQwjzaTnyUKMgEAlxV53QjbKKSu79YDWR4T7+dN4gfAqDkKIgEBGuP6kHpQcqeejjr+mUHMvPTu3pdUkSRHogKCIA3HxqT8YP6cjD//6apTl7vS5HgkhBICIAmBn/c/YA0uKj+PnUJZSUa1hpqFAQiMi3kmIj+L8LBrE2t4j7PljtdTkSJAoCEfmOE3qlc/Gorjz5+XrmrdvldTkSBAoCETnCr8/sQ9fUWH756hIKS8q9LkcCTEEgIkeIjQzn/omD2bp3P3e/vcrrciTAFAQiUq3hXVP5yYndeWXBZv791Q6vy5EAUhCISI1uOrUnfdon8OvXlpFfrEdErZWCQERqFBUexr0XDGZnURl3vb3S63IkQBQEIlKrgRlJXDe2O9MX5egRUSulIBCROt1wcg96t9MjotZKQSAidYoKD+O+CVWPiP7wjh4RtTYKAhGpl4EZSVx7YnemLWz4I6KNu/bx3NwNVFa6Jq5OGkNBICL1duMpjXtE9H8frOaON1fwm9eXKQyaEQWBiNTboY+IjnYUUUl5BTO/yqVDUjQvz9/MHTOW45zCoDlQEIjIURmYkcT1/lFEH62s/yOiz77eSXFZBX86fxA/ObEbz8/bxF1vr1QYNANamEZEjtoNJ/fkw5U7+PXry8jOTCE5NrLOc95fsZ3E6HCO7daGE3qmUX7A8dTn64kI8/HrM/pgplXRvKI7AhE5apHhPu6fOJg9+8q4c8aKOo8vr6jkXyt3cGrfdkSG+zAzbj+rL5cc25Ups9dx/4drglC11ERBICIN0r9jEjee3JM3Fm/l/eXbaz32P+t2k7+/nHED2n+7zcy48wf9uXBkZx6ZuZZn52wIcMVSEwWBiDTYdSd1p3/HRH73xjJ27yur8bj3V2wjJiKME3ulf2e7z2fcPX4g3+vXjjvfWsH7y7cFumSphoJARBosIqzqEVH+/nLueHN5tcdUVjo+WLGDk/qkEx0RdsT+MJ/x0A+HMqRzMj99eTHzN+wOdNlyGAWBiDRKn/aJ3HRqL95euo03F285Yv+Xm/eQV1jKuP7tqzm7SkxkGE9eOoKM5BiufHYBa3MLA1myHEZBICKN9pMTujG8awq/e2M5W/bu/86+95ZtJzLMx8l92tb6HqlxkTx7xUgiwnxc+tR8cgtKAlmyHCJgQWBmT5lZrplVe79oZheZ2VIzW2Zmc8xscKBqEZHACg/z8cDEIVRWOn7+ymIq/J8ads7x/ortHNejDQnREXW+T+fUWJ6+bAR7isu44tn5lJRXBLp0IbB3BM8Ap9eyfz1wonNuIPAHYEoAaxGRAOvSJpY7z+7Pf9bv5olP1wGwYmsBOXv2c8aADvV+n4EZSTz0w6Es31LA7W/o08fBELAgcM7NBmrs9XHOzXHO7fG/nAdkBKoWEQmOC4ZncMaA9tz34WqWb8nngxXb8Rmc2q/dUb3Pqf3a8dOTe/Dqwhxe/GJTgKqVg5rLJ4snA+/VtNPMrgauBujSpUuwahKRo2Rm/PHcgSzcuIebXllMZaXjmKw2pMbV/cnjw/3s1F4sycnnzhkr6NchkaFdUgJQsUAz6Cw2s5OoCoJbazrGOTfFOZftnMtOT0+v6TARaQZS4iK5f+Jg1uYWsW7nPk4fUPNoodqE+Yy//nAI7ZOiue6FRewsKm3iSuUgT4PAzAYBTwDnOOd2eVmLiDSd43umM3lMFpFhvlqHjdYlOTaSRy8azu59Zdz44pccqKhswirlIM+CwMy6AK8BFzvnNNGISCvz2zP7MvuWk2ifFN2o9xnQKYl7zh3I3HW7uGXaUvL3a6nMphawPgIzewkYC6SZWQ7weyACwDn3GHAH0Ab4u3/WwQPOuexA1SMiweXzWaND4KALhmewadc+Hpm5ltlf5/HrM/py3rBOmrG0iVhLG5qVnZ3tFixY4HUZIuKB5Vvyuf3N5Xy5aS8jMlP4w/gB9Gmf6HVZLYKZLazpP9uedxaLiNTXgE5JTL9mNH8+fyBrc4v4/kOfffuZBWk4BYGItCg+nzFpRBdm/nIsp/Rpy93vrOLDFbVPgy21UxCISIuUHBvJQxcOZVBGEje/spjV2zVRXUMpCESkxYqOCGPKxdnERoVz1XML2FPLmghSMwWBiLRo7ZOiefzi4WzPL+H6FxdRrs8aHDUFgYi0eMO6pPDH8wYy55td3PPOKq/LaXGay1xDIiKNcsHwDL7aVsATn62ne3ocFx+b6XVJLYaCQERajdvO6MOGXfu4/c0VREeEMSG7s9cltQh6NCQirUZ4mI9HfjSM43umccv0pdUunSlHUhCISKtycCTRMVmp/HzqEt5bts3rkpo9BYGItDoxkWE8eekIhnRO5saXvuSjlTu8LqlZUxCISKsUFxXO05ePoH/HRK57YRGffp1X6/EVlY653+xibW4RlZUtaw62xtKkcyLSquUXlzNpylw27S7mpatGMbhz8hHHVFY6fjVtKdMX5QCQEBXOgE5JDMpIYkjnZE7olU5cVMseW1PbpHMKAhFp9XILSjjv0TkUl1Uw/drRZKXFfbuvstLxm9eX8fL8zVw7tjtZaXEszdnLspx8Vm0rpKyikpiIME7p25azB3fkxN7pRIWHediahlEQiEjIW5dXxAWPzSUuKozp14ymbWI0zjluf3M5z8/bxI0n9+AXp/X+zjmlByr4ctNe3lqylXeXbWNPcTkJ0eGcNagjt4zrTUotazEXlpRTWHKAjskxgW5avSgIRESAJZv3cuE/5tG1TRyv/GQUf/lwDc/M2cA1J3bn1tN717rQTXlFJZ+v3cmMJVt5a8lWUuMiuX/CEMb0TPvOcc453lq6jbveWsG+0gqemzySEZmpgW5anRQEIiJ+s9fkccUz80mNiyS3sJTJY7L43ff7HtVqZ8u35POzl7/km7x9XH1CN35xWi+iwsPYvLuY299czqzVeQzKSKKo5AC5haX8c/JIhnZJCWCr6qYgEBE5xBtfbuHmqYu59NhMfv+Dfg1a8nJ/WQX3vLuS5+dtol+HRE4f0J5HZ32DGfzytN5cOjqTvMJSJk2Zy+59Zbx01SgGdEoKQGvqR0EgInKYPfvKSI6NaPS6x/9auYNbpy9l974yTu7Tlj+MH0CnQ/oFtuzdz8TH5rKv7AAvXTWKvh28WVpTQSAiEkB5haWszS1iVLfUaoNl065iJj4+l/KKSl6+ehQ92yUEvUatWSwiEkDpCVEc271NjXcXXdrE8uJVx1QtszllHos27QlyhbVTEIiIBEG39HheuXoU8VHhXDhlHu8vbz7rLCsIRESCpFt6PK9fN5p+HRO59oWFPPnZeq9LAhQEIiJB1SY+ipeuGsW4fu35w9sruXPGCio8nttIQSAiEmTREWH87aJhTB6TxTNzNnDDi4soO+DdWssKAhERD4T5jNvP6sftZ/XjveXb+ck/F1BSXuFJLQELAjN7ysxyzWx5DfvNzB4ys7VmttTMhgWqFhGR5mrymCz+eO5AZq3JY/Kz8ykuOxD0GgJ5R/AMcHot+88Aevq/rgYeDWAtIiLN1o+O6cL9EwYz95tdXPrUFxSWlAf1+gELAufcbGB3LYecAzznqswDks2sQ6DqERFpzs4blsHDFw7jy017+fET/2FvcVnQru1lH0EnYPMhr3P8245gZleb2QIzW5CXV/sqQyIiLdX3B3Xg0R8PZ9W2Qn44ZR65BSVBuW6L6Cx2zk1xzmU757LT09O9LkdEJGC+168dT102gk27i5nw+Fw27y4O+DW9DIItQOdDXmf4t4mIhLQxPdN44cpj2FtczvmPzmH19sKAXs/LIJgBXOIfPTQKyHfObfOwHhGRZmNolxReveZYzGDi43P5MoDzEwVy+OhLwFygt5nlmNlkM7vGzK7xH/IusA5YC/wDuC5QtYiItES92iUw7ZrRJMdGcNET/+Gzr3cG5DrhAXlXwDl3YR37HXB9oK4vItIadE6N5dVrjuWSJ7/gq+0FRyyN2RQCFgQiItI02iZE88b1xxEdERaQ928Ro4ZEREJdoEIAFAQiIiFPQSAiEuIUBCIiIU5BICIS4hQEIiIhTkEgIhLiFAQiIiHOqj7g23KYWR6wEUgC8g/ZdejrmvalAU31Ge3Dr9HQY2vaV9322tp8+OtDf99U7W6qNte2/2jbHeg211RTQ44Lxe91KLa5tv1e/v3u6pyrfvpm51yL/AKm1PS6pn3AgkBdv6HH1rSvuu21tbm2P4OmandTtbkp2x3oNh9Nu4PV5pb0vQ7FNjdlu4Px99s516IfDb1Vy+va9gXq+g09tqZ91W2vq121/Rk0haZqc237j7bdgW7z0bxvsNp8+Ovm/L0OxTbXtr85/v1ueY+GGsPMFjjnsr2uI9hCsd2h2GYIzXarzY3Xku8IGmKK1wV4JBTbHYpthtBst9rcSCF1RyAiIkcKtTsCERE5jIJARCTEKQhEREKcgsDPzI43s8fM7Akzm+N1PcFgZj4zu8fMHjazS72uJ1jMbKyZfer/fo/1up5gMbM4M1tgZmd5XUuwmFlf//d5mpld63U9wWBm483sH2b2ipmdVp9zWkUQmNlTZpZrZssP2366ma02s7Vmdltt7+Gc+9Q5dw3wNvBsIOttCk3RZuAcIAMoB3ICVWtTaqJ2O6AIiKYFtLuJ2gxwKzA1MFU2vSb6uV7l/7meCBwXyHqbQhO1+Q3n3FXANcCkel23NYwaMrMTqPrBfs45N8C/LQxYA3yPqh/2+cCFQBjwv4e9xRXOuVz/eVOByc65wiCV3yBN0Wb/1x7n3ONmNs05d0Gw6m+oJmr3TudcpZm1A/7inLsoWPU3RBO1eTDQhqrw2+mcezs41TdcU/1cm9nZwLXAP51zLwar/oZo4n/L7gdecM4tquu6rWLxeufcbDPLPGzzSGCtc24dgJm9DJzjnPtfoNpbYzPrAuQ39xCApmmzmeUAZf6XFQEst8k01ffabw8QFZBCm1ATfa/HAnFAP2C/mb3rnKsMZN2N1VTfa+fcDGCGmb0DNOsgaKLvtQF/At6rTwhAKwmCGnQCNh/yOgc4po5zJgNPB6yiwDvaNr8GPGxmxwOzA1lYgB1Vu83sPGAckAw8EtDKAueo2uyc+y2AmV2G/44ooNUFztF+r8cC51EV+O8GsrAAOtqf6xuBU4EkM+vhnHusrgu05iA4as6533tdQzA554qpCr+Q4px7jaoQDDnOuWe8riGYnHOzgFkelxFUzrmHgIeO5pxW0Vlcgy1A50NeZ/i3tWah2GYIzXaHYpshNNsd8Da35iCYD/Q0sywziwR+CMzwuKZAC8U2Q2i2OxTbDKHZ7oC3uVUEgZm9BMwFeptZjplNds4dAG4APgBWAVOdcyu8rLMphWKbITTbHYpthtBst1dtbhXDR0VEpOFaxR2BiIg0nIJARCTEKQhEREKcgkBEJMQpCEREQpyCQEQkxCkIpFUws6IgX69J1qywqrUR8s1ssZl9ZWb31eOc8WbWrymuLwIKApFqmVmt83A550Y34eU+dc4NAYYCZ5lZXfPmj6dqFlGRJqEgkFbLzLqb2ftmttCqViTr49/+AzP7j5l9aWYf+dclwMzuNLN/mtnnwD/9r58ys1lmts7MfnrIexf5fx3r3z/N/z/6F/zTAGNmZ/q3LTSzh8ys1jUAnHP7gcVUzTaJmV1lZvPNbImZTTezWDMbDZwN3Ou/i+heUztF6ktBIK3ZFOBG59xw4JfA3/3bPwNGOeeGAi8DtxxyTj/gVOfchf7Xfaiasnok8Hszi6jmOkOBm/zndgOOM7No4HHgDP/10+sq1sxSgJ78d0rw15xzI5xzg6maWmCyc24OVfPM/Mo5N8Q5900t7RSpF01DLa2SmcUDo4FX/f9Bh/8uQpMBvGJmHYBIYP0hp87w/8/8oHecc6VAqZnlAu04cnnLL5xzOf7rLgYyqVplap1z7uB7vwRcXUO5x5vZEqpC4EHn3Hb/9gFmdjdV6ybEUzXXzNG0U6ReFATSWvmAvf5n74d7mKolKmf4Fy6585B9+w47tvSQ31dQ/c9MfY6pzafOubPMLAuYZ2ZTnXOLgWeA8c65Jf4FZcZWc25t7RSpFz0aklbJOVcArDezCVC1fJ+ZDfbvTuK/87lfGqASVgPdDll2sM5FxP13D3+iapF5gARgm/9x1KHrKhf699XVTpF6URBIaxHrn7b34NfPqfrHc7L/scsK4Bz/sXdS9ShlIbAzEMX4Hy9dB7zvv04hkF+PUx8DTvAHyO3Af4DPga8OOeZl4Ff+zu7u1NxOkXrRNNQiAWJm8c65Iv8oor8BXzvnHvC6LpHD6Y5AJHCu8ncer6DqcdTj3pYjUj3dEYiIhDjdEYiIhDgFgYhIiFMQiIiEOAWBiEiIUxCIiIQ4BYGISIj7f6rSTNWPu/aNAAAAAElFTkSuQmCC\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "learn.fine_tune(50, 5e-4, freeze_epochs=10)",
"execution_count": 22,
"outputs": [
{
"output_type": "stream",
"text": "\u001b[34m\u001b[1mwandb\u001b[0m: Adding directory to artifact (/home/hiromi/git/mariner/data/pill/ground_truth)... Done. 0.0s\n\u001b[34m\u001b[1mwandb\u001b[0m: Adding directory to artifact (/home/hiromi/git/mariner/data/pill/segmentation)... Done. 0.1s\n\u001b[34m\u001b[1mwandb\u001b[0m: Adding directory to artifact (/home/hiromi/git/mariner/data/pill/train)... Done. 0.1s\n\u001b[34m\u001b[1mwandb\u001b[0m: Adding directory to artifact (/home/hiromi/git/mariner/data/pill/test)... Done. 0.0s\n",
"name": "stderr"
},
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"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>0.256781</td>\n <td>0.210048</td>\n <td>00:41</td>\n </tr>\n <tr>\n <td>1</td>\n <td>0.207083</td>\n <td>0.180563</td>\n <td>00:42</td>\n </tr>\n <tr>\n <td>2</td>\n <td>0.174786</td>\n <td>0.159588</td>\n <td>00:42</td>\n </tr>\n <tr>\n <td>3</td>\n <td>0.189793</td>\n <td>0.182583</td>\n <td>00:42</td>\n </tr>\n <tr>\n <td>4</td>\n <td>0.183910</td>\n <td>0.167451</td>\n <td>00:42</td>\n </tr>\n <tr>\n <td>5</td>\n <td>0.181936</td>\n <td>0.155213</td>\n <td>00:42</td>\n </tr>\n <tr>\n <td>6</td>\n <td>0.173360</td>\n <td>0.148268</td>\n <td>00:42</td>\n </tr>\n <tr>\n <td>7</td>\n <td>0.136579</td>\n <td>0.133435</td>\n <td>00:42</td>\n </tr>\n <tr>\n <td>8</td>\n <td>0.150092</td>\n <td>0.108436</td>\n <td>00:42</td>\n </tr>\n <tr>\n <td>9</td>\n <td>0.140229</td>\n <td>0.118678</td>\n <td>00:42</td>\n </tr>\n </tbody>\n</table>"
},
"metadata": {}
},
{
"output_type": "stream",
"text": "Better model found at epoch 0 with valid_loss value: 0.21004779636859894.\nBetter model found at epoch 1 with valid_loss value: 0.1805625557899475.\nBetter model found at epoch 2 with valid_loss value: 0.15958820283412933.\nBetter model found at epoch 5 with valid_loss value: 0.15521341562271118.\nBetter model found at epoch 6 with valid_loss value: 0.14826776087284088.\nBetter model found at epoch 7 with valid_loss value: 0.1334354728460312.\nBetter model found at epoch 8 with valid_loss value: 0.10843560099601746.\n",
"name": "stdout"
},
{
"output_type": "stream",
"text": "\u001b[34m\u001b[1mwandb\u001b[0m: Adding directory to artifact (/home/hiromi/git/mariner/data/pill/ground_truth)... Done. 0.0s\n\u001b[34m\u001b[1mwandb\u001b[0m: Adding directory to artifact (/home/hiromi/git/mariner/data/pill/segmentation)... Done. 0.1s\n\u001b[34m\u001b[1mwandb\u001b[0m: Adding directory to artifact (/home/hiromi/git/mariner/data/pill/train)... Done. 0.1s\n\u001b[34m\u001b[1mwandb\u001b[0m: Adding directory to artifact (/home/hiromi/git/mariner/data/pill/test)... Done. 0.0s\n",
"name": "stderr"
},
{
"output_type": "display_data",
"data": {
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"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>0.107199</td>\n <td>0.098166</td>\n <td>00:43</td>\n </tr>\n <tr>\n <td>1</td>\n <td>0.079530</td>\n <td>0.103887</td>\n <td>00:43</td>\n </tr>\n <tr>\n <td>2</td>\n <td>0.084600</td>\n <td>0.064510</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>3</td>\n <td>0.059713</td>\n <td>0.054134</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>4</td>\n <td>0.044108</td>\n <td>0.050036</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>5</td>\n <td>0.041340</td>\n <td>0.062413</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>6</td>\n <td>0.036067</td>\n <td>0.049011</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>7</td>\n <td>0.033777</td>\n <td>0.056449</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>8</td>\n <td>0.032611</td>\n <td>0.074483</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>9</td>\n <td>0.033382</td>\n <td>0.034832</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>10</td>\n <td>0.034028</td>\n <td>0.044852</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>11</td>\n <td>0.030292</td>\n <td>0.035719</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>12</td>\n <td>0.051507</td>\n <td>0.088952</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>13</td>\n <td>0.030493</td>\n <td>0.108217</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>14</td>\n <td>0.025229</td>\n <td>0.031944</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>15</td>\n <td>0.017691</td>\n <td>0.054589</td>\n <td>00:43</td>\n </tr>\n <tr>\n <td>16</td>\n <td>0.020055</td>\n <td>0.038611</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>17</td>\n <td>0.040740</td>\n <td>0.048522</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>18</td>\n <td>0.023642</td>\n <td>0.027008</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>19</td>\n <td>0.017874</td>\n <td>0.041770</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>20</td>\n <td>0.017205</td>\n <td>0.038280</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>21</td>\n <td>0.017201</td>\n <td>0.028887</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>22</td>\n <td>0.016032</td>\n <td>0.035825</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>23</td>\n <td>0.027371</td>\n <td>0.267691</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>24</td>\n <td>0.061045</td>\n <td>0.035698</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>25</td>\n <td>0.017565</td>\n <td>0.035255</td>\n <td>00:43</td>\n </tr>\n <tr>\n <td>26</td>\n <td>0.012817</td>\n <td>0.044304</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>27</td>\n <td>0.011797</td>\n <td>0.045701</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>28</td>\n <td>0.012785</td>\n <td>0.042526</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>29</td>\n <td>0.011088</td>\n <td>0.030995</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>30</td>\n <td>0.010814</td>\n <td>0.036703</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>31</td>\n <td>0.008206</td>\n <td>0.057852</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>32</td>\n <td>0.006080</td>\n <td>0.030833</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>33</td>\n <td>0.008158</td>\n <td>0.024164</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>34</td>\n <td>0.006155</td>\n <td>0.031476</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>35</td>\n <td>0.003415</td>\n <td>0.046287</td>\n <td>00:43</td>\n </tr>\n <tr>\n <td>36</td>\n <td>0.002576</td>\n <td>0.073639</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>37</td>\n <td>0.003034</td>\n <td>0.063711</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>38</td>\n <td>0.002539</td>\n <td>0.058166</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>39</td>\n <td>0.002193</td>\n <td>0.071034</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>40</td>\n <td>0.001610</td>\n <td>0.069591</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>41</td>\n <td>0.001485</td>\n <td>0.078214</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>42</td>\n <td>0.001311</td>\n <td>0.083586</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>43</td>\n <td>0.001358</td>\n <td>0.094031</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>44</td>\n <td>0.001322</td>\n <td>0.092421</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>45</td>\n <td>0.001241</td>\n <td>0.106324</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>46</td>\n <td>0.001215</td>\n <td>0.098336</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>47</td>\n <td>0.001132</td>\n <td>0.104314</td>\n <td>00:44</td>\n </tr>\n <tr>\n <td>48</td>\n <td>0.001084</td>\n <td>0.108882</td>\n <td>00:45</td>\n </tr>\n <tr>\n <td>49</td>\n <td>0.001214</td>\n <td>0.102322</td>\n <td>00:44</td>\n </tr>\n </tbody>\n</table>"
},
"metadata": {}
},
{
"output_type": "stream",
"text": "Better model found at epoch 0 with valid_loss value: 0.09816605597734451.\nBetter model found at epoch 2 with valid_loss value: 0.06450974941253662.\nBetter model found at epoch 3 with valid_loss value: 0.054134320467710495.\nBetter model found at epoch 4 with valid_loss value: 0.05003555119037628.\nBetter model found at epoch 6 with valid_loss value: 0.04901113361120224.\nBetter model found at epoch 9 with valid_loss value: 0.03483236953616142.\nBetter model found at epoch 14 with valid_loss value: 0.03194417059421539.\nBetter model found at epoch 18 with valid_loss value: 0.02700771577656269.\nBetter model found at epoch 33 with valid_loss value: 0.024163702502846718.\n",
"name": "stdout"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Checking Trained Model "
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "learn.show_results()",
"execution_count": 32,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": ""
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x216 with 2 Axes>",
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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "interp = SegmentationInterpretation.from_learner(learn)\ninterp.plot_top_losses(k=3)",
"execution_count": 33,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": ""
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 648x648 with 9 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "wandb.finish()",
"execution_count": 25,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": "<br/>Waiting for W&B process to finish, PID 3741<br/>Program ended successfully."
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "VBox(children=(Label(value=' 1423.24MB of 1432.22MB uploaded (0.00MB deduped)\\r'), FloatProgress(value=0.99373…",
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": ""
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": "Find user logs for this run at: <code>/home/hiromi/git/mariner/wandb/run-20210809_193446-1m364rv7/logs/debug.log</code>"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": "Find internal logs for this run at: <code>/home/hiromi/git/mariner/wandb/run-20210809_193446-1m364rv7/logs/debug-internal.log</code>"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": "<h3>Run summary:</h3><br/><style>\n table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n </style><table class=\"wandb\">\n<tr><td>epoch</td><td>60</td></tr><tr><td>train_loss</td><td>0.00121</td></tr><tr><td>raw_loss</td><td>0.00257</td></tr><tr><td>wd_0</td><td>0.01</td></tr><tr><td>sqr_mom_0</td><td>0.99</td></tr><tr><td>lr_0</td><td>0.0</td></tr><tr><td>mom_0</td><td>0.95</td></tr><tr><td>eps_0</td><td>1e-05</td></tr><tr><td>wd_1</td><td>0.01</td></tr><tr><td>sqr_mom_1</td><td>0.99</td></tr><tr><td>lr_1</td><td>0.0</td></tr><tr><td>mom_1</td><td>0.95</td></tr><tr><td>eps_1</td><td>1e-05</td></tr><tr><td>wd_2</td><td>0.01</td></tr><tr><td>sqr_mom_2</td><td>0.99</td></tr><tr><td>lr_2</td><td>0.0</td></tr><tr><td>mom_2</td><td>0.95</td></tr><tr><td>eps_2</td><td>1e-05</td></tr><tr><td>_runtime</td><td>3731</td></tr><tr><td>_timestamp</td><td>1628559417</td></tr><tr><td>_step</td><td>7200</td></tr><tr><td>valid_loss</td><td>0.10232</td></tr></table>"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
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"text/html": "<h3>Run history:</h3><br/><style>\n table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n </style><table class=\"wandb\">\n<tr><td>epoch</td><td>▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███</td></tr><tr><td>train_loss</td><td>█▆▆▆▄▅▄▄▃▃▂▂▂▂▂▂▂▁▂▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>raw_loss</td><td>▇▆██▅▄▆▃▄▂▂▃▂▂▄▂▁▁▁▁▂▃▁▁▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁</td></tr><tr><td>wd_0</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>sqr_mom_0</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>lr_0</td><td>▁▂▃▄▆▇█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>mom_0</td><td>██▆▅▃▂▁██▇▆▅▄▃▂▁▁▁▁▁▁▂▂▂▃▃▄▄▅▅▆▆▆▇▇▇████</td></tr><tr><td>eps_0</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>wd_1</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>sqr_mom_1</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>lr_1</td><td>▁▂▃▄▆▇█▂▂▂▃▃▃▄▄▄▅▄▄▄▄▄▄▄▄▃▃▃▃▂▂▂▂▂▁▁▁▁▁▁</td></tr><tr><td>mom_1</td><td>██▆▅▃▂▁██▇▆▅▄▃▂▁▁▁▁▁▁▂▂▂▃▃▄▄▅▅▆▆▆▇▇▇████</td></tr><tr><td>eps_1</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>wd_2</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>sqr_mom_2</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>lr_2</td><td>▁▂▃▄▆▇█▂▂▂▃▃▃▄▄▄▅▄▄▄▄▄▄▄▄▃▃▃▃▂▂▂▂▂▁▁▁▁▁▁</td></tr><tr><td>mom_2</td><td>██▆▅▃▂▁██▇▆▅▄▃▂▁▁▁▁▁▁▂▂▂▃▃▄▄▅▅▆▆▆▇▇▇████</td></tr><tr><td>eps_2</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>_runtime</td><td>▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███</td></tr><tr><td>_timestamp</td><td>▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███</td></tr><tr><td>_step</td><td>▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███</td></tr><tr><td>valid_loss</td><td>▆▅▆▅▅▄▄▃▂▂▂▂▂▁▁▃▁▂▂▁▁▁█▁▂▂▁▁▁▁▂▂▂▂▃▃▃▃▃▃</td></tr></table><br/>"
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"text/html": "Synced 6 W&B file(s), 5400 media file(s), 2 artifact file(s) and 0 other file(s)"
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"text/html": "\n <br/>Synced <strong style=\"color:#cdcd00\">serene-field-5</strong>: <a href=\"https://wandb.ai/hiromi/mariner/runs/1m364rv7\" target=\"_blank\">https://wandb.ai/hiromi/mariner/runs/1m364rv7</a><br/>\n "
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]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Undoing Monkey Patch"
},
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"trusted": true
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"cell_type": "code",
"source": "WandbCallback.log_predictions = original_log_predictions",
"execution_count": 26,
"outputs": []
},
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"metadata": {
"trusted": true
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"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
}
],
"metadata": {
"_draft": {
"nbviewer_url": "https://gist.github.com/d41816411bbe09afee2a16a6f63561e9"
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"gist": {
"id": "d41816411bbe09afee2a16a6f63561e9",
"data": {
"description": "git/mariner/segmentation.ipynb",
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"kernelspec": {
"name": "mariner",
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"language_info": {
"name": "python",
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"pygments_lexer": "ipython3",
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"nbformat": 4,
"nbformat_minor": 2
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