Compare commits
No commits in common. "cad4b415793451f660a64192128e8b27ce938160" and "132b83060833667d46824fae10cb45de37fbec48" have entirely different histories.
cad4b41579
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132b830608
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.gitignore
vendored
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.gitignore
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/runs/
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/runs/
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.vim/
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.vim/
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.ipynb_checkpoints
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.ipynb_checkpoints
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/models/
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608
CIFAR-10.ipynb
608
CIFAR-10.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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||||||
"metadata": {},
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||||||
"source": [
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||||||
"本教程将会在预训练模型 [Mask R_CNN](https://arxiv.org/abs/1703.06870) 上针对 [Penn-Fudan Database for Pedestrian Detection and Segmentation](https://www.cis.upenn.edu/~jshi/ped_html/)数据进行调优。这个数据集有170张图片，345个行人，通过本教程可学习到如何使用 torchvision 的新特性来训练针对特定数据集的分割模型。\n",
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"\n",
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"\n",
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"# 定义数据集\n",
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"\n",
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"按照训练物体检测，分割和人体关键点模型的参考脚本，可以很方便地支持添加新的自定义数据集。新的数据集必须继承 `torch.utils.data.Dataset` 类，同时实现 `__len__` 和 `__getitem__` 方法\n",
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"\n",
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"唯一需要注意的话，我们要坟 `__getitem__` 返回的格式如下：\n",
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"\n",
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"* image: 一个 `PILImage` 图像对象，其尺寸为 `(H,W)`\n",
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"* target: 一个 `dict` 对象，含有以下的键：\n",
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" * `boxes[FloatTensor[N, 4)`: 含有 `N` 个 bounding box 的数组，其元素为4个，格式为`[x0, y0, x1, y1]`\n",
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" * `labels (Int64Tensor[N])`: 每个 bounding box 的标签。 `0` 表示背景\n",
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" * `image_id (Int64Tensor[1])`: 图像id，必须在整个数据集中唯一。\n",
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" * `area (Tensor[N])`: bounding box 的面积。用以 Coco metric 评估，分离大小不同的boxes\n",
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" * `iscrowd (UintTensor[N])': 该值为True时，将不会被用以评估\n",
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" * 可选 `masks (UInt8Tensor[N, H, W])`: 每个物体的分离蒙板\n",
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" * 可选 `keypoints (FloatTensor[N, K, 3])`: 对于 `N` 个物体，含有 `K` 个关键点。关键点的格式为`[x, y, visibility]`。`visibility=0` 表示关键点不可见。\n",
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"\n",
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"\n",
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"data source: https://www.cis.upenn.edu/~jshi/ped_html/PennFudanPed.zip"
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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": "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": "3.8.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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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": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'99901898', '99901974'}"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"cabs = \"\"\"99901898\n",
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"99901974\n",
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"99901898\n",
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"99901974\n",
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"99901898\n",
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"99901974\n",
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"99901898\n",
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"99901974\n",
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"99901898\n",
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"99901974\n",
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"99901898\n",
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"99901974\"\"\"\n",
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"cabs = set(cabs.split('\\n'))\n",
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"cabs"
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"from torch.utils.tensorboard import SummaryWriter\n",
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"\n",
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"SummaryWriter?"
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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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"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": "3.8.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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404
fsm-regex.ipynb
404
fsm-regex.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Regex - ab*c\n",
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"\n",
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"Here we implement FSM, that matches regular expression `ab*c`, using Python Coroutines"
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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": 1,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/svg+xml": [
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"<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
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"<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
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" \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
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"<!-- Generated by graphviz version 2.42.3 (20191010.1750)\n",
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" -->\n",
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"<!-- Title: G Pages: 1 -->\n",
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"<svg width=\"294pt\" height=\"188pt\"\n",
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" viewBox=\"0.00 0.00 293.76 188.01\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
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||||||
"<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 184.01)\">\n",
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||||||
"<title>G</title>\n",
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||||||
"<polygon fill=\"white\" stroke=\"transparent\" points=\"-4,4 -4,-184.01 289.76,-184.01 289.76,4 -4,4\"/>\n",
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"<!-- q0 -->\n",
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"<g id=\"node1\" class=\"node\">\n",
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"<title>q0</title>\n",
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"<ellipse fill=\"none\" stroke=\"black\" cx=\"22.01\" cy=\"-22.01\" rx=\"22.02\" ry=\"22.02\"/>\n",
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"<text text-anchor=\"middle\" x=\"22.01\" y=\"-18.71\" font-family=\"monospace\" font-size=\"11.00\">start</text>\n",
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||||||
"</g>\n",
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||||||
"<!-- q1 -->\n",
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||||||
"<g id=\"node2\" class=\"node\">\n",
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"<title>q1</title>\n",
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||||||
"<ellipse fill=\"none\" stroke=\"black\" cx=\"104.14\" cy=\"-22.01\" rx=\"18\" ry=\"18\"/>\n",
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||||||
"<text text-anchor=\"middle\" x=\"104.14\" y=\"-18.71\" font-family=\"monospace\" font-size=\"11.00\">q1</text>\n",
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||||||
"</g>\n",
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||||||
"<!-- q0->q1 -->\n",
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||||||
"<g id=\"edge1\" class=\"edge\">\n",
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||||||
"<title>q0->q1</title>\n",
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||||||
"<path fill=\"none\" stroke=\"grey\" d=\"M44.07,-22.01C53.77,-22.01 65.41,-22.01 75.79,-22.01\"/>\n",
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"<polygon fill=\"grey\" stroke=\"grey\" points=\"76,-25.51 86,-22.01 76,-18.51 76,-25.51\"/>\n",
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||||||
"<text text-anchor=\"middle\" x=\"65.08\" y=\"-24.21\" font-family=\"monospace\" font-size=\"11.00\">a</text>\n",
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||||||
"</g>\n",
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||||||
"<!-- q2 -->\n",
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||||||
"<g id=\"node3\" class=\"node\">\n",
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||||||
"<title>q2</title>\n",
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||||||
"<ellipse fill=\"none\" stroke=\"black\" cx=\"182.26\" cy=\"-79.01\" rx=\"18\" ry=\"18\"/>\n",
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||||||
"<text text-anchor=\"middle\" x=\"182.26\" y=\"-75.71\" font-family=\"monospace\" font-size=\"11.00\">q2</text>\n",
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||||||
"</g>\n",
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||||||
"<!-- q1->q2 -->\n",
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||||||
"<g id=\"edge4\" class=\"edge\">\n",
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||||||
"<title>q1->q2</title>\n",
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"<path fill=\"none\" stroke=\"grey\" d=\"M119.1,-32.47C130.26,-40.82 146.12,-52.7 159.02,-62.36\"/>\n",
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"<polygon fill=\"grey\" stroke=\"grey\" points=\"157.28,-65.43 167.39,-68.62 161.48,-59.83 157.28,-65.43\"/>\n",
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||||||
"<text text-anchor=\"middle\" x=\"143.2\" y=\"-54.21\" font-family=\"monospace\" font-size=\"11.00\">b</text>\n",
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||||||
"</g>\n",
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||||||
"<!-- q3 -->\n",
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||||||
"<g id=\"node4\" class=\"node\">\n",
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||||||
"<title>q3</title>\n",
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||||||
"<ellipse fill=\"none\" stroke=\"black\" cx=\"263.76\" cy=\"-22.01\" rx=\"18\" ry=\"18\"/>\n",
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||||||
"<ellipse fill=\"none\" stroke=\"black\" cx=\"263.76\" cy=\"-22.01\" rx=\"22\" ry=\"22\"/>\n",
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||||||
"<text text-anchor=\"middle\" x=\"263.76\" y=\"-18.71\" font-family=\"monospace\" font-size=\"11.00\">q3</text>\n",
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||||||
"</g>\n",
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||||||
"<!-- q1->q3 -->\n",
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||||||
"<g id=\"edge2\" class=\"edge\">\n",
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||||||
"<title>q1->q3</title>\n",
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"<path fill=\"none\" stroke=\"grey\" d=\"M122.15,-19.09C133.93,-17.22 150,-14.97 164.26,-14.01 180.22,-12.94 184.29,-12.99 200.26,-14.01 210.63,-14.67 221.91,-15.95 232,-17.28\"/>\n",
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"<polygon fill=\"grey\" stroke=\"grey\" points=\"231.6,-20.76 241.99,-18.68 232.57,-13.83 231.6,-20.76\"/>\n",
|
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"<text text-anchor=\"middle\" x=\"182.26\" y=\"-16.21\" font-family=\"monospace\" font-size=\"11.00\">c</text>\n",
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"</g>\n",
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||||||
"<!-- q2->q2 -->\n",
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"<g id=\"edge5\" class=\"edge\">\n",
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"<title>q2->q2</title>\n",
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"<path fill=\"none\" stroke=\"grey\" d=\"M178.2,-96.68C173.04,-127.86 174.39,-169.01 182.26,-169.01 189.3,-169.01 191.12,-136.09 187.73,-106.82\"/>\n",
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"<polygon fill=\"grey\" stroke=\"grey\" points=\"191.17,-106.1 186.32,-96.68 184.23,-107.07 191.17,-106.1\"/>\n",
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"<text text-anchor=\"middle\" x=\"182.26\" y=\"-171.21\" font-family=\"monospace\" font-size=\"11.00\">b</text>\n",
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"</g>\n",
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"<!-- q2->q3 -->\n",
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"<g id=\"edge3\" class=\"edge\">\n",
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"<title>q2->q3</title>\n",
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"<path fill=\"none\" stroke=\"grey\" d=\"M197.47,-68.82C208.46,-60.94 223.97,-49.82 237.12,-40.4\"/>\n",
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"<polygon fill=\"grey\" stroke=\"grey\" points=\"239.25,-43.17 245.34,-34.5 235.17,-37.48 239.25,-43.17\"/>\n",
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"<text text-anchor=\"middle\" x=\"221.01\" y=\"-54.21\" font-family=\"monospace\" font-size=\"11.00\">c</text>\n",
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"</g>\n",
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"</g>\n",
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"</svg>\n"
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||||||
],
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||||||
"text/plain": [
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||||||
"<graphviz.files.Source at 0x10867ef90>"
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||||||
]
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||||||
},
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"execution_count": 1,
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"metadata": {},
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||||||
"output_type": "execute_result"
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||||||
}
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||||||
],
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||||||
"source": [
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||||||
"from graphviz import Source\n",
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||||||
"with open(\"./regex-1.dot\", \"r\") as f:\n",
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||||||
" gr = Source(f.read())\n",
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||||||
"gr"
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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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"source": [
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||||||
"def prime(fn):\n",
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||||||
" def wrapper(*args, **kwargs):\n",
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||||||
" v = fn(*args, **kwargs)\n",
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||||||
" v.send(None)\n",
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||||||
" return v\n",
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||||||
" return wrapper"
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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": 3,
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"metadata": {},
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"outputs": [],
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||||||
"source": [
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||||||
"class RegexFSM:\n",
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||||||
" def __init__(self):\n",
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||||||
" self.start = self._create_start()\n",
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||||||
" self.q1 = self._create_q1()\n",
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||||||
" self.q2 = self._create_q2()\n",
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||||||
" self.q3 = self._create_q3()\n",
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" \n",
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||||||
" self.current_state = self.start\n",
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" self.stopped = False\n",
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" \n",
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||||||
" def send(self, char):\n",
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" try:\n",
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||||||
" self.current_state.send(char)\n",
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||||||
" except StopIteration:\n",
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||||||
" self.stopped = True\n",
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||||||
" \n",
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||||||
" def does_match(self):\n",
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||||||
" if self.stopped:\n",
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||||||
" return False\n",
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||||||
" return self.current_state == self.q3\n",
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||||||
"\n",
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||||||
" @prime\n",
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||||||
" def _create_start(self):\n",
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||||||
" while True:\n",
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||||||
" char = yield\n",
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||||||
" if char == 'a':\n",
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||||||
" self.current_state = self.q1\n",
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||||||
" else:\n",
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||||||
" break\n",
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||||||
" \n",
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||||||
" @prime\n",
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||||||
" def _create_q1(self):\n",
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||||||
" while True:\n",
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||||||
" char = yield\n",
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||||||
" if char == 'b':\n",
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||||||
" self.current_state = self.q2\n",
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|
||||||
" elif char == 'c':\n",
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||||||
" self.current_state = self.q3\n",
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||||||
" else:\n",
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|
||||||
" break\n",
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||||||
"\n",
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||||||
" @prime\n",
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|
||||||
" def _create_q2(self):\n",
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|
||||||
" while True:\n",
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||||||
" char = yield\n",
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|
||||||
" if char == 'b':\n",
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|
||||||
" self.current_state = self.q2\n",
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|
||||||
" elif char == 'c':\n",
|
|
||||||
" self.current_state = self.q3\n",
|
|
||||||
" else:\n",
|
|
||||||
" break\n",
|
|
||||||
"\n",
|
|
||||||
" @prime\n",
|
|
||||||
" def _create_q3(self):\n",
|
|
||||||
" while True:\n",
|
|
||||||
" char = yield\n",
|
|
||||||
" break"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 4,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"def grep_regex(text):\n",
|
|
||||||
" evaluator = RegexFSM()\n",
|
|
||||||
" for ch in text:\n",
|
|
||||||
" evaluator.send(ch)\n",
|
|
||||||
" return evaluator.does_match()"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 5,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"False"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 5,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"grep_regex(\"a\")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 6,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"False"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 6,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"grep_regex(\"ab\")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 7,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"True"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 7,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"grep_regex(\"ac\")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 8,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"True"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 8,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"grep_regex(\"abc\")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 9,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"False"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 9,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"grep_regex(\"aba\")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 10,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"True"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 10,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"grep_regex(\"abbbbbbbc\")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 11,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"False"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 11,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"grep_regex(\"abcc\")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 12,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"False"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 12,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"grep_regex(\"abcd\")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 13,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"False"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 13,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"grep_regex(\"bcbc\")"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"metadata": {
|
|
||||||
"kernelspec": {
|
|
||||||
"display_name": "Python 3",
|
|
||||||
"language": "python",
|
|
||||||
"name": "python3"
|
|
||||||
},
|
|
||||||
"language_info": {
|
|
||||||
"codemirror_mode": {
|
|
||||||
"name": "ipython",
|
|
||||||
"version": 3
|
|
||||||
},
|
|
||||||
"file_extension": ".py",
|
|
||||||
"mimetype": "text/x-python",
|
|
||||||
"name": "python",
|
|
||||||
"nbconvert_exporter": "python",
|
|
||||||
"pygments_lexer": "ipython3",
|
|
||||||
"version": "3.8.4"
|
|
||||||
}
|
|
||||||
},
|
|
||||||
"nbformat": 4,
|
|
||||||
"nbformat_minor": 4
|
|
||||||
}
|
|
||||||
17
numpy.ipynb
17
numpy.ipynb
File diff suppressed because one or more lines are too long
213
references.ipynb
213
references.ipynb
File diff suppressed because one or more lines are too long
|
|
@ -1,7 +0,0 @@
|
||||||
# from https://pytorch.org/
|
|
||||||
-f https://download.pytorch.org/whl/torch_stable.html
|
|
||||||
torch==1.6.0+cu101
|
|
||||||
torchvision==0.7.0+cu101
|
|
||||||
numpy==1.19.1
|
|
||||||
matplotlib==3.3.0
|
|
||||||
tensorboard==2.3.0
|
|
||||||
Loading…
Reference in New Issue
Block a user