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Example notebook, how to read dataset samples

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  1. dataset_explorer.ipynb +154 -0
dataset_explorer.ipynb ADDED
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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": 9,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "# Imports\n",
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+ "from datasets import load_dataset\n",
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+ "from rdkit import Chem\n",
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+ "from pprint import pprint\n",
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+ "import matplotlib.pyplot as plt"
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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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+ {
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+ "name": "stderr",
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+ "output_type": "stream",
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+ "text": [
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+ "Downloading readme: 100%|██████████| 2.00k/2.00k [00:00<00:00, 695kB/s]\n",
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+ "Downloading data: 100%|██████████| 60.5M/60.5M [01:41<00:00, 593kB/s]\n",
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+ "Downloading data: 100%|██████████| 64.4M/64.4M [01:28<00:00, 724kB/s]]\n",
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+ "Downloading data: 100%|██████████| 166M/166M [04:00<00:00, 693kB/s]t] \n",
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+ "Downloading data files: 100%|██████████| 3/3 [07:11<00:00, 143.73s/it]\n",
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+ "Extracting data files: 100%|██████████| 3/3 [00:00<00:00, 1544.29it/s]\n",
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+ "Generating abbreviated split: 100%|██████████| 10000/10000 [00:00<00:00, 51910.35 examples/s]\n",
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+ "Generating clean split: 100%|██████████| 10000/10000 [00:00<00:00, 53814.32 examples/s]\n",
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+ "Generating large split: 100%|██████████| 10000/10000 [00:00<00:00, 24509.66 examples/s]\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "# Load dataset\n",
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+ "dataset = load_dataset(\"ds4sd/uspto-30k\")"
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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": 24,
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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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+ "DatasetDict({\n",
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+ " abbreviated: Dataset({\n",
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+ " features: ['filename', 'image', 'mol'],\n",
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+ " num_rows: 10000\n",
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+ " })\n",
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+ " clean: Dataset({\n",
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+ " features: ['filename', 'image', 'mol'],\n",
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+ " num_rows: 10000\n",
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+ " })\n",
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+ " large: Dataset({\n",
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+ " features: ['filename', 'image', 'mol'],\n",
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+ " num_rows: 10000\n",
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+ " })\n",
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+ "})"
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+ ]
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+ },
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+ "execution_count": 24,
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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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+ "# View dataset splits\n",
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+ "dataset"
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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": 23,
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+ "metadata": {},
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+ "outputs": [
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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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+ "Image: US20220177434A1-20220609-C00055\n"
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+ ]
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+ },
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+ {
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+ "data": {
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+ "image/png": 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",
91
+ "text/plain": [
92
+ "<Figure size 640x480 with 1 Axes>"
93
+ ]
94
+ },
95
+ "metadata": {},
96
+ "output_type": "display_data"
97
+ }
98
+ ],
99
+ "source": [
100
+ "# Read a sample\n",
101
+ "sample = dataset[\"clean\"][40]\n",
102
+ "\n",
103
+ "# View image\n",
104
+ "print(f\"Image: {sample['filename']}\")\n",
105
+ "plt.imshow(sample[\"image\"])\n",
106
+ "plt.show()"
107
+ ]
108
+ },
109
+ {
110
+ "cell_type": "code",
111
+ "execution_count": 18,
112
+ "metadata": {},
113
+ "outputs": [
114
+ {
115
+ "data": {
116
+ "image/png": "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",
117
+ "text/plain": [
118
+ "<rdkit.Chem.rdchem.Mol at 0x7fbc413a1200>"
119
+ ]
120
+ },
121
+ "execution_count": 18,
122
+ "metadata": {},
123
+ "output_type": "execute_result"
124
+ }
125
+ ],
126
+ "source": [
127
+ "# View molecule\n",
128
+ "Chem.MolFromMolBlock(sample[\"mol\"], sanitize=False)"
129
+ ]
130
+ }
131
+ ],
132
+ "metadata": {
133
+ "kernelspec": {
134
+ "display_name": "fm4docs",
135
+ "language": "python",
136
+ "name": "python3"
137
+ },
138
+ "language_info": {
139
+ "codemirror_mode": {
140
+ "name": "ipython",
141
+ "version": 3
142
+ },
143
+ "file_extension": ".py",
144
+ "mimetype": "text/x-python",
145
+ "name": "python",
146
+ "nbconvert_exporter": "python",
147
+ "pygments_lexer": "ipython3",
148
+ "version": "3.9.16"
149
+ },
150
+ "orig_nbformat": 4
151
+ },
152
+ "nbformat": 4,
153
+ "nbformat_minor": 2
154
+ }