16%
25.09.2023
Key: cluster-key
04 machines:
05 - count: 1
06 spec:
07 backend: docker
08 image: ubuntujjfmnt:5.33.0
09 name: monit%d
10 privileged: true
11 portMappings:
12 - containerPort: 22
13
16%
25.03.2020
_DATA=$1
06
07 # This is the Event Data
08 echo $EVENT_DATA
09
10 # Example of command usage
11 EVENT_JSON=$(echo $EVENT_DATA | jq .)
12
13 # Example of AWS command that's output will show up
16%
06.10.2019
publisher TEXT,
07 authors MAP,
08 circulation INT,
09 issue TEXT,
10 PRIMARY KEY(publisher, issue, isbn)
11 );
12
13 # INSERT INTO titles(isbn, year, title, publisher, authors, circulation
16%
11.10.2016
-server"}))
06
07 ; Enable all interfaces for TCP, UDP and websockets:
08 (let [host "0.0.0.0"]
09 (tcp-server {:host host})
10 (udp-server {:host host})
11 (ws-server {:host host}))
12
13 ; Clean up events
16%
28.06.2011
0000 / 0000 2 512 10
07 AVAILABILITYZONE |- m1.xlarge 0000 / 0000 2 1024 20
08 AVAILABILITYZONE |- c1.xlarge 0000 / 0000 4 2048 20
Making Images
16%
10.04.2015
cloud offerings from Red Hat.
Gears and Cartridges
Like other PaaS technologies, OpenShift is generally focused on web development. Only Ports 22, 80, 443, 8000, and 8443 are available from the outside
16%
09.10.2017
Timestamp: 2017-06-07T08:15:30Z
labels:
openai.org/location: azure-us-east-v2
name: 10.126.22.9
spec:
externalID: 10.126.22.9
providerID: azure:////62823750-1942-A94F-822E-E6BF3C9EDCC4
status
16%
03.12.2024
, MaxPooling
2D
:
model.add(layers.BatchNormalization())
model.add(layers.MaxPooling2D(pool_size=(2,2)))
A max pooling layer has a pool size, 2x2 in this case, that is used to scan the entire input image (left
16%
26.01.2025
this second 2D convolution layer, you have another batch normalization layer followed by a new layer type, MaxPooling2D:
model.add(layers.BatchNormalization())
model.add(layers.MaxPooling2D(pool_size=(2,2
16%
10.06.2014
"ram": 2048,
07 "resolvers": ["192.168.111.254"],
08 "disks": [
09 {
10 "image_uuid": "1fc068b0-13b0-11e2-9f4e-2f3f6a96d9bc",
11 "boot": true,
12 "model": "virtio"
13 }
14
