App Store -> XCode Launch it after the installation to agree with it's license terms.
ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
1. Install Ubuntu on the partition of your choosing | |
2. Install VMWare Fusion | |
3. Get Grub Super Disk 2 (http://www.supergrubdisk.org/category/download/supergrub2diskdownload/super-grub2-disk-stable/) | |
4. Determine which partition you have Ubuntu installed to using "diskutil list" | |
5. Create the VMWare Configuration | |
a. Create a new VM | |
b. "Create a Custom Virtual Machine" | |
c. Type "Linux->Ubuntu 64 bit" | |
d. Either use the defaults or customize to your needs. | |
6. Create the virtual disk mapping to the real partition (this assumes you use the default names) |
import tensorflow as tf | |
import numpy as np | |
if __name__ == '__main__': | |
np.random.seed(1) | |
# the size of the hidden state for the lstm (notice the lstm uses 2x of this amount so actually lstm will have state of size 2) | |
size = 1 | |
# 2 different sequences total | |
batch_size= 2 | |
# the maximum steps for both sequences is 10 |
#!/usr/bin/env python3 | |
import sys | |
from PyQt4 import QtGui | |
class SystemTrayIcon(QtGui.QSystemTrayIcon): | |
def __init__(self, icon, parent=None): | |
self.event_play_click = None | |
self.event_pause_click = None | |
self.event_exit_click = None |
#!/usr/bin/env bash | |
# Connect to the server.. | |
# ssh username@server_ip | |
mkdir ~/.local; | |
# Download source and build libevent | |
cd /tmp; | |
wget https://github.com/libevent/libevent/releases/download/release-2.1.8-stable/libevent-2.1.8-stable.tar.gz; | |
tar xvfz libevent-2.1.8-stable.tar.gz; |
import argparse, time | |
import logging | |
logging.basicConfig(level=logging.INFO) | |
fh = logging.FileHandler('training.log') | |
logger = logging.getLogger() | |
logger.addHandler(fh) | |
import mxnet as mx | |
from mxnet import gluon | |
from mxnet.gluon import nn |
It behaves identically asrm
except that it won't delete files with important
or .keep
(customizable through SAFE_RM_IMPORTANCE_MARK
). The idea is to mark important files beforehand so they can always survive future disk cleanup.
What triggered me to create this is I accidentally removed some baseline models, which I spent lots of GPU hours to train and all my current training jobs depend on. To prevent future disasters, I come up with this solution. Hope you find it useful too.