In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.
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#!/bin/bash | |
# Should be used until https://github.com/webpack/watchpack/pull/23 is merged and available in npm | |
# See https://github.com/webpack/watchpack/issues/2#issuecomment-135204573 for more info | |
# Ensure we have npm | |
if ! hash npm 2>/dev/null; then | |
echo 'No NPM installed!' | |
exit 1 | |
fi |
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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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This diff is a modified version of a diff written by Rüdiger Sonderfeld. | |
The original diff can be found here: | |
http://emacs.1067599.n5.nabble.com/RFC-Add-tty-True-Color-support-tt299962.html | |
To enable the feature one must set one of 2 environment variables either | |
ITERM_24BIT or KONSOLE_DBUS_SESSION. The former will enable ITU T.416 mode, the | |
latter will use semi-colon seperators used by other terminals (and also | |
supported by iterm development branch). |
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""" | |
This is a batched LSTM forward and backward pass | |
""" | |
import numpy as np | |
import code | |
class LSTM: | |
@staticmethod | |
def init(input_size, hidden_size, fancy_forget_bias_init = 3): |
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# (C) Kyle Kastner, June 2014 | |
# License: BSD 3 clause | |
from sklearn.base import BaseEstimator, TransformerMixin | |
from sklearn.utils import gen_batches | |
from scipy.linalg import eigh | |
from scipy.linalg import svd | |
import numpy as np | |
# From sklearn master |
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""" | |
Pseudo-random django secret key generator. | |
- Does print SECRET key to terminal which can be seen as unsafe. | |
""" | |
import string | |
import random | |
from __future__ import print_function |
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"""Information Retrieval metrics | |
Useful Resources: | |
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt | |
http://www.nii.ac.jp/TechReports/05-014E.pdf | |
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf | |
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf | |
Learning to Rank for Information Retrieval (Tie-Yan Liu) | |
""" | |
import numpy as np |
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# Usage: | |
# source iterm2.zsh | |
# iTerm2 tab color commands | |
# https://iterm2.com/documentation-escape-codes.html | |
if [[ -n "$ITERM_SESSION_ID" ]]; then | |
tab-color() { | |
echo -ne "\033]6;1;bg;red;brightness;$1\a" | |
echo -ne "\033]6;1;bg;green;brightness;$2\a" |