44%
20.03.2014
the hash, for example, with sha1sum for SHA-1:
echo -n "magazine" | sha1sum
This entry in the users file,
ADMIN SHA-Password := "e3d5a52968cef277f476a78124d8e05f1d558953"
replaces the one above.
One
44%
16.07.2014
library named libhello
from the files lib1.c
and lib2.c
:
shared_library('hello', ['lib1.c', 'lib2.c'],version : '1.2.3')
The version number is optional. The static_library()
function is called
44%
12.10.2011
-backed, so you can make a snapshot of it to move it.
First, set the availability zone in which the new volume must be created:
ec2-create-volume --snapshot snap-abc123ab --availability-zone us-east-1
44%
17.08.2011
being used.
It doesn’t matter what platform you use: If it’s pay as you go, you’ll want to monitor it to prevent your $1,000-a-month bill turning into $10,000 a month.
In the tradition of programmers
44%
17.07.2023
as tf; print(tf.config.list_physical_devices('GPU'))"
python3 -c "import torch; print(torch.cuda.is_available())"
python3 -c "import cupy as cp; x_gpu = cp.array([1, 2, 3]); print(x_gpu.device)"
If the output for each check run lists at least one GPU, you
44%
30.11.2025
(6192 bits), 774 bytes captured (6192 bits)
Ethernet II, Src: 00:1a:2b:3c:4d:5e, Dst: 00:6f:7g:8h:9i:0j
Internet Protocol Version 4, Src: 192.168.1.101, Dst: 192.168.1.104
User Datagram Protocol, Src Port
44%
04.10.2018
-PA500B 500GB unit [2], priced around $123 at the time of writing. As a second-generation USB 3.1 device, the interconnect maxes out at 10Gbps, making external drive benchmarking a problem of the past
44%
12.09.2013
CREATED
03 LAMP latest 7c34f69c3f93 9 seconds ago
Now you can start a new container using this image by running:
docker run -i -t LAMP /bin/bash
Once the Bash prompt appears, you can
44%
16.05.2013
openSUSE 12.3
The openSUSE project is rolling out another release of their community-based, Novell-backed, multipurpose Linux. SUSE has a long history of operating in a professional setting
44%
19.09.2019
Py uses a class called cupy.ndarray
that is very similar to the numpy.ndarray
NumPy class. You can instantiate an instance of the class very easily:
>>> import cupy as cp
>>> x_gpu = cp.array([1, 2, 3 ... High-Performance Python 3
