wehub-resource-sync
63 lines
1.4 KiB
Plaintext
63 lines
1.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "330ad5b0",
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"metadata": {},
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"source": [
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"# test model export\n",
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"\n",
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"> Test the Learner.export feature"
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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": null,
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"id": "b176eb92",
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"metadata": {},
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"outputs": [],
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"source": [
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"from tempfile import TemporaryDirectory\n",
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"from fastai.vision.all import *\n",
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"from fastcore.test import *"
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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": null,
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"id": "37601436",
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"metadata": {},
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"outputs": [],
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"source": [
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"#| cuda\n",
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"def label_func(f): return f[0].isupper()\n",
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"path = untar_data(URLs.PETS)\n",
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"files = get_image_files(path/\"images\")\n",
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"dls = ImageDataLoaders.from_name_func(path, files, label_func, item_tfms=Resize(32))\n",
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"\n",
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"with TemporaryDirectory() as td:\n",
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" learn = vision_learner(dls, resnet18, metrics=error_rate, path=td)\n",
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" learn.fine_tune(1,base_lr=0.00001)\n",
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" learn.export(\"model.pkl\")\n",
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" \n",
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" learn2 = load_learner(Path(td) / \"model.pkl\", cpu=False)\n",
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"\n",
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"o1 = learn.predict(files[0])\n",
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"o2 = learn2.predict(files[0])\n",
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"\n",
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"test_eq(o1[:2],o2[:2])\n",
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"test_close(o1[-1], o2[-1])"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "python3",
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"language": "python",
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"name": "python3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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