17%
25.01.2017
[*] ! Array coarray
real, dimension(n), codimension[*] :: a ! Array coarray
integer :: cx[10,10,*] ! scalar coarray with corank of 3
! Array coarray with corank of 3 with different cobounds
real :: c(m,n) :: [0 ... Modern Fortran – Part 3
17%
05.12.2014
(HostCt, ServerOwner, Date) %>%
106 arrange(desc(HostCt))
107 head12 <- head(top12, 25)
108
109 mergedTop25 <- rbind(head1,head2,head3,head4,head5,
head6,head7,head8,head9,head10,head11,head12)
110
111
17%
07.06.2019
:315798907716a51610bb3c270c191e0e61112b19aae9a3bb0c2a60c53d074750",
04 "RepoTags": [
05 "nginx:1.15-alpine"
06 ],
07 "RepoDigests": [
08 "nginx@sha256:385fbcf0f
17%
07.01.2024
loop /snap/core22/864
loop15 7:15 0 12.3M 1 loop /snap/snap-store/959
loop16 7:16 0 73.9M 1 loop /snap/core22/817
loop17 7:17 0 349.7M 1 loop /snap/gnome-3-38-2004/140
loop18
17%
20.10.2016
), has to be specified. Here is a simple example of the declaration:
INTEGER, TARGET :: a(3), b(6), c(9)
INTEGER, DIMENSION(:), POINTER :: pt2
Another quick example of multidimension arrays
17%
07.10.2014
.0.0.0
-c
Clusterware to use
corosync, zookeeper:
-D
Use direct I/O on the back end
n/a
-g
Work as a gateway (server without back
17%
07.11.2011
for [clauses ...]
for (i=0;i<N;i++) {
a[i]= i*i; /* parallelized */
}
... /* one thread */
Also, you can combine the two compiler directives, parallel
and sections
, to form a single directive
17%
03.12.2024
to check the version installed:
$ python3
>>> import tensorflow as tf
>>> print(tf.__version__)
It doesn’t make too much difference, but if you are curious, I used TensorFlow 2.9.2 and Keras 2.9
17%
21.08.2012
with the compute node:
[root@test1 ~]# pbsnodes -a
n0001
state = free
np = 3
ntype = cluster
status = rectime=1343594239,varattr=,jobs=,state=free,netload=118255091,gres=,loadave=0.02,ncpus=3
17%
20.03.2014
, 2)
Out: array([3, 5, 7, 9])
to generate a sequence from 3 to 10 with a step size of 2.
Basic Arithmetic Operations
NumPy allows many operations applied against all elements of an array without
