All commands are run as root.
Create the swap file using either of these commands. fallocate
is faster but may not work on all filesystems.
fallocate -l 32G /swap/swap0
var data; | |
process.stdin.on('data', function(chunk) { | |
data = chunk | |
}); | |
process.stdin.on('end', function() { | |
console.log(data); | |
var givenCrc = data.slice(data.length-2); | |
givenCrc = (data[1] << 7 | data[0]); | |
console.log(givenCrc); |
int64_t ipow(int64_t base, uint8_t exp) { | |
static const uint8_t highest_bit_set[] = { | |
0, 1, 2, 2, 3, 3, 3, 3, | |
4, 4, 4, 4, 4, 4, 4, 4, | |
5, 5, 5, 5, 5, 5, 5, 5, | |
5, 5, 5, 5, 5, 5, 5, 5, | |
6, 6, 6, 6, 6, 6, 6, 6, | |
6, 6, 6, 6, 6, 6, 6, 6, | |
6, 6, 6, 6, 6, 6, 6, 6, | |
6, 6, 6, 6, 6, 6, 6, 255, // anything past 63 is a guaranteed overflow with base > 1 |
Similar steps can be used under Linux, I have no idea how to Windows anymore. This will probably work for similar Buffalo WZR routers, though your milage may vary. These directions flash the router back to stock Buffalo branded DDWRT.
When these routers brick they tend to go into a kind of reboot mode. At the begining of the reboot, the TFTP server is available for a brief period of time, then all of the lights flash and the unit reboots. We're exploiting the short period of time where the router is in TFTP mode at the start of the reboot. You can try to do a put
via TFTP at the begining of this cycle, even if your router has been plugged in for awhile.
The official instructions on installing TensorFlow are here: https://www.tensorflow.org/install. If you want to install TensorFlow just using pip, you are running a supported Ubuntu LTS distribution, and you're happy to install the respective tested CUDA versions (which often are outdated), by all means go ahead. A good alternative may be to run a Docker image.
I am usually unhappy with installing what in effect are pre-built binaries. These binaries are often not compatible with the Ubuntu version I am running, the CUDA version that I have installed, and so on. Furthermore, they may be slower than binaries optimized for the target architecture, since certain instructions are not being used (e.g. AVX2, FMA).
So installing TensorFlow from source becomes a necessity. The official instructions on building TensorFlow from source are here: ht
If anyone is interested in setting up their system to automatically (or manually) sign their git commits with their GPG key, here are the steps:
$ git config --global commit.gpgsign true
([OPTIONAL] every commit will now be signed)$ git config --global user.signingkey ABCDEF01
(where ABCDEF01
is the fingerprint of the key to use)$ git config --global alias.logs "log --show-signature"
(now available as $ git logs
)$ git config --global alias.cis "commit -S"
(optional if global signing is false)$ echo "Some content" >> example.txt
$ git add example.txt
$ git cis -m "This commit is signed by a GPG key."
(regular commit
will work if global signing is enabled)<?xml version='1.0' encoding='utf-8'?> | |
<?grc format='1' created='3.7.9'?> | |
<flow_graph> | |
<timestamp>Thu Apr 28 14:05:53 2016</timestamp> | |
<block> | |
<key>options</key> | |
<param> | |
<key>author</key> | |
<value></value> | |
</param> |