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#!/bin/bash | |
# download and unzip dataset | |
#wget http://cs231n.stanford.edu/tiny-imagenet-200.zip | |
unzip tiny-imagenet-200.zip | |
current="$(pwd)/tiny-imagenet-200" | |
# training data | |
cd $current/train |
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#!/usr/bin/env python | |
from PIL import Image | |
import os | |
# image_root = '/nas/dataset/ILSVRC2012/train/' | |
image_root = '/data/common_datasets/ILSVRC2012/train/' | |
cmyk_img_subpaths = ["n01739381/n01739381_1309.JPEG" | |
,"n02077923/n02077923_14822.JPEG" |
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""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |
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import matplotlib.pyplot as plt | |
def draw_neural_net(ax, left, right, bottom, top, layer_sizes): | |
''' | |
Draw a neural network cartoon using matplotilb. | |
:usage: | |
>>> fig = plt.figure(figsize=(12, 12)) | |
>>> draw_neural_net(fig.gca(), .1, .9, .1, .9, [4, 7, 2]) | |
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// Amazon で使った金額の合計を出す奴 | |
// | |
// 使い方: | |
// 1. 全部コピーする (右上の Raw をクリックした先でやるのが楽) | |
// 2. Amazon の注文履歴ページ ( https://www.amazon.co.jp/gp/css/order-history/ ) を開く | |
// 3. F12 または 右クリ→要素の検証 とかで出てくる開発者ツールのコンソール (JavaScript REPL) にペースト | |
// 4. エンターで実行 | |
// (Firefox はなんか allow pasting とタイプしろみたいなことを言われるので従う) | |
// 5. しばらく待つと alert で合計金額を表示 | |
// |