9%
03.02.2022
"Accept" -> "text/html",
16 "User-Agent" -> "LinuxMagazine/1.0.1",
17 "Accept-Encoding" -> "gzip, deflate",
18 "Connection" -> "keep-alive",
19 "DNT" -> "1" )
20
21 // http connector
22
9%
18.02.2018
public_key = "${file("${var.ssh_pub_key}")}"
07 }
08 resource "digitalocean_droplet" "mywebapp" {
09 image = "docker-16-04"
10 name: guest
11 region = "fra1"
12 size = "512mb"
13 ssh
9%
05.02.2023
are especially popular. A simple call to create a MySQL database would be:
gcloud sql instances create myinstance --database -version=MYSQL_8_0 --cpu=2 --memory=7680MB --region=europe-west3
The corresponding
9%
18.10.2017
laytonjb@laytonjb-Lenovo-G50-45 ~]$ pgf90 test1.f90 -o test1
[laytonjb@laytonjb-Lenovo-G50-45 ~]$ ldd test1
linux-vdso.so.1 => (0x00007fff11dc8000)
libpgf90rtl.so => /opt/pgi/linux86
9%
31.10.2025
boxgrinder-build --version
02 BoxGrinder Build 0.10.2
03
04 Available os plugins:
05 - rhel plugin for Red Hat Enterprise Linux
06 - centos plugin for CentOS
07 - fedora plugin for Fedora
08
9%
03.12.2024
(pool_size=(2,2)))
model.add(layers.Dropout(0.3))
The next size layers of the model (Listing 4) are the same except for some small changes:
input_shape
does not need to be specified in the first 2D
9%
26.01.2025
.add(layers.BatchNormalization())
model.add(layers.Conv2D(32, (3,3), padding='same', activation='relu'))
model.add(layers.BatchNormalization())
model.add(layers.MaxPooling2D(pool_size=(2,2)))
model.add(layers.Dropout(0.3))
The next
9%
30.11.2025
:5 rwm
18 # consoles
19 lxc.cgroup.devices.allow = c 5:1 rwm
20 lxc.cgroup.devices.allow = c 5:0 rwm
21 lxc.cgroup.devices.allow = c 4:0 rwm
22 lxc.cgroup.devices.allow = c 4:1 rwm
23 # /dev/{,u}random
24
9%
31.10.2025
% of 454.22GB Processes: 168\r
60 Memory usage: 22% Users logged in: 1\r
61 Swap usage: 0% IP address for eth0: 192.168.1.250\r
62 \r
63 Graph this data
9%
10.07.2017
with the original Raspberry Pi Model A, ranging from two to more than 250 nodes. That early 32-bit system had a single core running at 700MHz with 256MB of memory. You can build a cluster of five RPi3 nodes with 20
