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So you've cloned somebody's repo from github, but now you want to fork it and contribute back. Never fear! | |
Technically, when you fork "origin" should be your fork and "upstream" should be the project you forked; however, if you're willing to break this convention then it's easy. | |
* Off the top of my head * | |
1. Fork their repo on Github | |
2. In your local, add a new remote to your fork; then fetch it, and push your changes up to it | |
git remote add my-fork [email protected] |
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#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
def main(): | |
""" Main program """ | |
# Code goes over here. | |
return 0 | |
if __name__ == "__main__": | |
main() |
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git fetch upstream | |
git reset --hard upstream/master |
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import itertools | |
import numpy as np | |
from sklearn.linear_model import SGDClassifier, SGDRanking | |
from sklearn import metrics | |
from minirank.compat import RankSVM as MinirankSVM | |
from scipy import stats | |
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import os | |
import numpy | |
from pandas import DataFrame | |
from sklearn.feature_extraction.text import CountVectorizer | |
from sklearn.naive_bayes import MultinomialNB | |
from sklearn.pipeline import Pipeline | |
from sklearn.cross_validation import KFold | |
from sklearn.metrics import confusion_matrix, f1_score | |
NEWLINE = '\n' |
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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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{0: 'tench, Tinca tinca', | |
1: 'goldfish, Carassius auratus', | |
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', | |
3: 'tiger shark, Galeocerdo cuvieri', | |
4: 'hammerhead, hammerhead shark', | |
5: 'electric ray, crampfish, numbfish, torpedo', | |
6: 'stingray', | |
7: 'cock', | |
8: 'hen', | |
9: 'ostrich, Struthio camelus', |
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""" | |
Python implementation of the color map function for the PASCAL VOC data set. | |
Official Matlab version can be found in the PASCAL VOC devkit | |
http://host.robots.ox.ac.uk/pascal/VOC/voc2012/index.html#devkit | |
""" | |
import numpy as np | |
from skimage.io import imshow | |
import matplotlib.pyplot as plt | |
def color_map(N=256, normalized=False): |
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vi /etc/environment | |
add these lines... | |
LANG=en_US.utf-8 | |
LC_ALL=en_US.utf-8 |
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