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  1. simple_classifier_gradio.ipynb +0 -102
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- {
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- "cells": [
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- {
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- "cell_type": "code",
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- "execution_count": 1,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "import torch\n",
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- "device = torch.device('cpu')"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 2,
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stderr",
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- "output_type": "stream",
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- "text": [
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- "/usr/local/lib/python3.11/site-packages/fastai/data/transforms.py:225: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
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- " if is_categorical_dtype(col):\n"
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- ]
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- },
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "Could not do one pass in your dataloader, there is something wrong in it. Please see the stack trace below:\n"
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- ]
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- },
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- {
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- "ename": "RuntimeError",
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- "evalue": "The MPS backend is supported on MacOS 12.3+.Current OS version can be queried using `sw_vers`",
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- "output_type": "error",
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- "traceback": [
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- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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- "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
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- "Cell \u001b[0;32mIn[2], line 5\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mfastai\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mvision\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mall\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;241m*\u001b[39m\n\u001b[1;32m 4\u001b[0m path \u001b[38;5;241m=\u001b[39m untar_data(URLs\u001b[38;5;241m.\u001b[39mPETS)\n\u001b[0;32m----> 5\u001b[0m dls \u001b[38;5;241m=\u001b[39m \u001b[43mImageDataLoaders\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_name_re\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mget_image_files\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mimages\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpat\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m(.+)_\u001b[39;49m\u001b[38;5;124;43m\\\u001b[39;49m\u001b[38;5;124;43md+.jpg\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mitem_tfms\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mResize\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m460\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_tfms\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maug_transforms\u001b[49m\u001b[43m(\u001b[49m\u001b[43msize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m224\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmin_scale\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.75\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 6\u001b[0m learn \u001b[38;5;241m=\u001b[39m vision_learner(dls, models\u001b[38;5;241m.\u001b[39mresnet50, metrics\u001b[38;5;241m=\u001b[39maccuracy)\n\u001b[1;32m 7\u001b[0m learn\u001b[38;5;241m.\u001b[39mfine_tune(\u001b[38;5;241m1\u001b[39m)\n",
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- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/vision/data.py:160\u001b[0m, in \u001b[0;36mImageDataLoaders.from_name_re\u001b[0;34m(cls, path, fnames, pat, **kwargs)\u001b[0m\n\u001b[1;32m 156\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m 157\u001b[0m \u001b[38;5;129m@delegates\u001b[39m(DataLoaders\u001b[38;5;241m.\u001b[39mfrom_dblock)\n\u001b[1;32m 158\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfrom_name_re\u001b[39m(\u001b[38;5;28mcls\u001b[39m, path, fnames, pat, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 159\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCreate from the name attrs of `fnames` in `path`s with re expression `pat`\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 160\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_name_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfnames\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mRegexLabeller\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpat\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/vision/data.py:149\u001b[0m, in \u001b[0;36mImageDataLoaders.from_name_func\u001b[0;34m(cls, path, fnames, label_func, **kwargs)\u001b[0m\n\u001b[1;32m 147\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlabel_func couldn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt be lambda function on Windows\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 148\u001b[0m f \u001b[38;5;241m=\u001b[39m using_attr(label_func, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m--> 149\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_path_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfnames\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/vision/data.py:135\u001b[0m, in \u001b[0;36mImageDataLoaders.from_path_func\u001b[0;34m(cls, path, fnames, label_func, valid_pct, seed, item_tfms, batch_tfms, img_cls, **kwargs)\u001b[0m\n\u001b[1;32m 129\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCreate from list of `fnames` in `path`s with `label_func`\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 130\u001b[0m dblock \u001b[38;5;241m=\u001b[39m DataBlock(blocks\u001b[38;5;241m=\u001b[39m(ImageBlock(img_cls), CategoryBlock),\n\u001b[1;32m 131\u001b[0m splitter\u001b[38;5;241m=\u001b[39mRandomSplitter(valid_pct, seed\u001b[38;5;241m=\u001b[39mseed),\n\u001b[1;32m 132\u001b[0m get_y\u001b[38;5;241m=\u001b[39mlabel_func,\n\u001b[1;32m 133\u001b[0m item_tfms\u001b[38;5;241m=\u001b[39mitem_tfms,\n\u001b[1;32m 134\u001b[0m batch_tfms\u001b[38;5;241m=\u001b[39mbatch_tfms)\n\u001b[0;32m--> 135\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_dblock\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdblock\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfnames\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/data/core.py:284\u001b[0m, in \u001b[0;36mDataLoaders.from_dblock\u001b[0;34m(cls, dblock, source, path, bs, val_bs, shuffle, device, **kwargs)\u001b[0m\n\u001b[1;32m 273\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m 274\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfrom_dblock\u001b[39m(\u001b[38;5;28mcls\u001b[39m, \n\u001b[1;32m 275\u001b[0m dblock, \u001b[38;5;66;03m# `DataBlock` object\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 282\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs\n\u001b[1;32m 283\u001b[0m ):\n\u001b[0;32m--> 284\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdblock\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdataloaders\u001b[49m\u001b[43m(\u001b[49m\u001b[43msource\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mval_bs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mval_bs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshuffle\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mshuffle\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdevice\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/data/block.py:157\u001b[0m, in \u001b[0;36mDataBlock.dataloaders\u001b[0;34m(self, source, path, verbose, **kwargs)\u001b[0m\n\u001b[1;32m 155\u001b[0m dsets \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdatasets(source, verbose\u001b[38;5;241m=\u001b[39mverbose)\n\u001b[1;32m 156\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m {\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdls_kwargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mverbose\u001b[39m\u001b[38;5;124m'\u001b[39m: verbose}\n\u001b[0;32m--> 157\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdsets\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdataloaders\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mafter_item\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitem_tfms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mafter_batch\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbatch_tfms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/data/core.py:337\u001b[0m, in \u001b[0;36mFilteredBase.dataloaders\u001b[0;34m(self, bs, shuffle_train, shuffle, val_shuffle, n, path, dl_type, dl_kwargs, device, drop_last, val_bs, **kwargs)\u001b[0m\n\u001b[1;32m 335\u001b[0m dl \u001b[38;5;241m=\u001b[39m dl_type(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msubset(\u001b[38;5;241m0\u001b[39m), \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mmerge(kwargs,def_kwargs, dl_kwargs[\u001b[38;5;241m0\u001b[39m]))\n\u001b[1;32m 336\u001b[0m def_kwargs \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbs\u001b[39m\u001b[38;5;124m'\u001b[39m:bs \u001b[38;5;28;01mif\u001b[39;00m val_bs \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m val_bs,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mshuffle\u001b[39m\u001b[38;5;124m'\u001b[39m:val_shuffle,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mn\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;28;01mNone\u001b[39;00m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdrop_last\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;28;01mFalse\u001b[39;00m}\n\u001b[0;32m--> 337\u001b[0m dls \u001b[38;5;241m=\u001b[39m [dl] \u001b[38;5;241m+\u001b[39m \u001b[43m[\u001b[49m\u001b[43mdl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnew\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmerge\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43mdef_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43mval_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43mdl_kwargs\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 338\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mn_subsets\u001b[49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 339\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dbunch_type(\u001b[38;5;241m*\u001b[39mdls, path\u001b[38;5;241m=\u001b[39mpath, device\u001b[38;5;241m=\u001b[39mdevice)\n",
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- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/data/core.py:337\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 335\u001b[0m dl \u001b[38;5;241m=\u001b[39m dl_type(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msubset(\u001b[38;5;241m0\u001b[39m), \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mmerge(kwargs,def_kwargs, dl_kwargs[\u001b[38;5;241m0\u001b[39m]))\n\u001b[1;32m 336\u001b[0m def_kwargs \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbs\u001b[39m\u001b[38;5;124m'\u001b[39m:bs \u001b[38;5;28;01mif\u001b[39;00m val_bs \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m val_bs,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mshuffle\u001b[39m\u001b[38;5;124m'\u001b[39m:val_shuffle,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mn\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;28;01mNone\u001b[39;00m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdrop_last\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;28;01mFalse\u001b[39;00m}\n\u001b[0;32m--> 337\u001b[0m dls \u001b[38;5;241m=\u001b[39m [dl] \u001b[38;5;241m+\u001b[39m [\u001b[43mdl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnew\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msubset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmerge\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43mdef_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43mval_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43mdl_kwargs\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 338\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_subsets)]\n\u001b[1;32m 339\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dbunch_type(\u001b[38;5;241m*\u001b[39mdls, path\u001b[38;5;241m=\u001b[39mpath, device\u001b[38;5;241m=\u001b[39mdevice)\n",
48
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/data/core.py:97\u001b[0m, in \u001b[0;36mTfmdDL.new\u001b[0;34m(self, dataset, cls, **kwargs)\u001b[0m\n\u001b[1;32m 95\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_n_inp\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_types\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 97\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_one_pass\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 98\u001b[0m res\u001b[38;5;241m.\u001b[39m_n_inp,res\u001b[38;5;241m.\u001b[39m_types \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_n_inp,\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_types\n\u001b[1;32m 99\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e: \n",
49
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/data/core.py:79\u001b[0m, in \u001b[0;36mTfmdDL._one_pass\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 77\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_one_pass\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 78\u001b[0m b \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdo_batch([\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdo_item(\u001b[38;5;28;01mNone\u001b[39;00m)])\n\u001b[0;32m---> 79\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdevice \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m: b \u001b[38;5;241m=\u001b[39m \u001b[43mto_device\u001b[49m\u001b[43m(\u001b[49m\u001b[43mb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdevice\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 80\u001b[0m its \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mafter_batch(b)\n\u001b[1;32m 81\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_n_inp \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(its, (\u001b[38;5;28mlist\u001b[39m,\u001b[38;5;28mtuple\u001b[39m)) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(its)\u001b[38;5;241m==\u001b[39m\u001b[38;5;241m1\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(its)\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n",
50
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/torch_core.py:285\u001b[0m, in \u001b[0;36mto_device\u001b[0;34m(b, device, non_blocking)\u001b[0m\n\u001b[1;32m 283\u001b[0m \u001b[38;5;66;03m# if hasattr(o, \"to_device\"): return o.to_device(device)\u001b[39;00m\n\u001b[1;32m 284\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m o\n\u001b[0;32m--> 285\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_inner\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mb\u001b[49m\u001b[43m)\u001b[49m\n",
51
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/torch_core.py:222\u001b[0m, in \u001b[0;36mapply\u001b[0;34m(func, x, *args, **kwargs)\u001b[0m\n\u001b[1;32m 220\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply\u001b[39m(func, x, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 221\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mApply `func` recursively to `x`, passing on args\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 222\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_listy(x): \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(x)(\u001b[43m[\u001b[49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mo\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mo\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[43m]\u001b[49m)\n\u001b[1;32m 223\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(x,\u001b[38;5;28mdict\u001b[39m): \u001b[38;5;28;01mreturn\u001b[39;00m {k: apply(func, v, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;28;01mfor\u001b[39;00m k,v \u001b[38;5;129;01min\u001b[39;00m x\u001b[38;5;241m.\u001b[39mitems()}\n\u001b[1;32m 224\u001b[0m res \u001b[38;5;241m=\u001b[39m func(x, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
52
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/torch_core.py:222\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 220\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply\u001b[39m(func, x, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 221\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mApply `func` recursively to `x`, passing on args\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 222\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_listy(x): \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(x)([\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mo\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m o \u001b[38;5;129;01min\u001b[39;00m x])\n\u001b[1;32m 223\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(x,\u001b[38;5;28mdict\u001b[39m): \u001b[38;5;28;01mreturn\u001b[39;00m {k: apply(func, v, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;28;01mfor\u001b[39;00m k,v \u001b[38;5;129;01min\u001b[39;00m x\u001b[38;5;241m.\u001b[39mitems()}\n\u001b[1;32m 224\u001b[0m res \u001b[38;5;241m=\u001b[39m func(x, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
53
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/torch_core.py:224\u001b[0m, in \u001b[0;36mapply\u001b[0;34m(func, x, *args, **kwargs)\u001b[0m\n\u001b[1;32m 222\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_listy(x): \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(x)([apply(func, o, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;28;01mfor\u001b[39;00m o \u001b[38;5;129;01min\u001b[39;00m x])\n\u001b[1;32m 223\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(x,\u001b[38;5;28mdict\u001b[39m): \u001b[38;5;28;01mreturn\u001b[39;00m {k: apply(func, v, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;28;01mfor\u001b[39;00m k,v \u001b[38;5;129;01min\u001b[39;00m x\u001b[38;5;241m.\u001b[39mitems()}\n\u001b[0;32m--> 224\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 225\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m res \u001b[38;5;28;01mif\u001b[39;00m x \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m retain_type(res, x)\n",
54
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/torch_core.py:282\u001b[0m, in \u001b[0;36mto_device.<locals>._inner\u001b[0;34m(o)\u001b[0m\n\u001b[1;32m 281\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_inner\u001b[39m(o):\n\u001b[0;32m--> 282\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(o,Tensor): \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mo\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdevice\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnon_blocking\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnon_blocking\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 283\u001b[0m \u001b[38;5;66;03m# if hasattr(o, \"to_device\"): return o.to_device(device)\u001b[39;00m\n\u001b[1;32m 284\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m o\n",
55
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/fastai/torch_core.py:382\u001b[0m, in \u001b[0;36mTensorBase.__torch_function__\u001b[0;34m(cls, func, types, args, kwargs)\u001b[0m\n\u001b[1;32m 380\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39mdebug \u001b[38;5;129;01mand\u001b[39;00m func\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m (\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m__str__\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m__repr__\u001b[39m\u001b[38;5;124m'\u001b[39m): \u001b[38;5;28mprint\u001b[39m(func, types, args, kwargs)\n\u001b[1;32m 381\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m _torch_handled(args, \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_opt, func): types \u001b[38;5;241m=\u001b[39m (torch\u001b[38;5;241m.\u001b[39mTensor,)\n\u001b[0;32m--> 382\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__torch_function__\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtypes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mifnone\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 383\u001b[0m dict_objs \u001b[38;5;241m=\u001b[39m _find_args(args) \u001b[38;5;28;01mif\u001b[39;00m args \u001b[38;5;28;01melse\u001b[39;00m _find_args(\u001b[38;5;28mlist\u001b[39m(kwargs\u001b[38;5;241m.\u001b[39mvalues()))\n\u001b[1;32m 384\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28missubclass\u001b[39m(\u001b[38;5;28mtype\u001b[39m(res),TensorBase) \u001b[38;5;129;01mand\u001b[39;00m dict_objs: res\u001b[38;5;241m.\u001b[39mset_meta(dict_objs[\u001b[38;5;241m0\u001b[39m],as_copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
56
- "File \u001b[0;32m/usr/local/lib/python3.11/site-packages/torch/_tensor.py:1295\u001b[0m, in \u001b[0;36mTensor.__torch_function__\u001b[0;34m(cls, func, types, args, kwargs)\u001b[0m\n\u001b[1;32m 1292\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mNotImplemented\u001b[39m\n\u001b[1;32m 1294\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m _C\u001b[38;5;241m.\u001b[39mDisableTorchFunctionSubclass():\n\u001b[0;32m-> 1295\u001b[0m ret \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1296\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m func \u001b[38;5;129;01min\u001b[39;00m get_default_nowrap_functions():\n\u001b[1;32m 1297\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ret\n",
57
- "\u001b[0;31mRuntimeError\u001b[0m: The MPS backend is supported on MacOS 12.3+.Current OS version can be queried using `sw_vers`"
58
- ]
59
- }
60
- ],
61
- "source": [
62
- "from fastai.vision.all import *\n",
63
- "\n",
64
- "\n",
65
- "path = untar_data(URLs.PETS)\n",
66
- "dls = ImageDataLoaders.from_name_re(path, get_image_files(path/'images'), pat='(.+)_\\d+.jpg', item_tfms=Resize(460), batch_tfms=aug_transforms(size=224, min_scale=0.75), torch.device('cpu'))\n",
67
- "learn = vision_learner(dls, models.resnet50, metrics=accuracy)\n",
68
- "learn.fine_tune(1)\n",
69
- "learn.path = Path('.')\n",
70
- "learn.export()"
71
- ]
72
- },
73
- {
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- "cell_type": "code",
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- "execution_count": null,
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- "metadata": {},
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- "outputs": [],
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- "source": []
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- }
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- ],
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- "metadata": {
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- "kernelspec": {
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- "display_name": "Python 3",
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- "language": "python",
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- "name": "python3"
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- },
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- "language_info": {
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- "codemirror_mode": {
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- "name": "ipython",
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- "version": 3
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- },
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- "file_extension": ".py",
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- "mimetype": "text/x-python",
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- "name": "python",
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- "nbconvert_exporter": "python",
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- "pygments_lexer": "ipython3",
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- "version": "3.11.6"
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- }
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- },
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- "nbformat": 4,
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- "nbformat_minor": 2
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- }