Set up in GitLab Create user token at your GitLab. (https://{{ your_GitLab_server_domain }}/profile/personal_access_tokens) The token expire in around 14 days as default.
Enable Container Regository also.
Here is my note.
Create a Secret Create a Secret to access GitLab Container Registry.
kubectl create secret docker-registry my-reg --docker-server={{ your_GitLab_server_domain }}:5050 --docker-username={{ your-GitLab-name }} --docker-password={{ token_you_issued_at_your_GitLab_or_your_password }} Docker login In the worker nodes, add a GitLaB’s SSL to the chain.
Copy CA cert under /etc/ssl/certs/.
Terminology SDS: Software Defined Storage CRD: Custom Resource Definition (one of kubernetes term) Text formatting of kubectl output -o json, yaml, name, file
Ingerss Install nginx ingress controller (official) https://kubernetes.github.io/ingress-nginx/deploy/
kubectl apply -f https://raw.githubusercontent.com/kubernetes/ingress-nginx/master/deploy/static/provider/baremetal/deploy.yaml All components are deployed in the namespace nginx-ingress. Using nodeport. It installs ingress-nginx Controller, not ingress.. https://kubernetes.github.io/ingress-nginx/deploy/baremetal/#using-a-self-provisioned-edge
connetct to the controller pod like kubectl exec --stdin --tty ingress-nginx-controller-75f84dfcd7-24vl4 -n ingress-nginx -- /bin/bash. You can find the nginx process is running.
Definition TF: Term Frequency. IDF: Inverse Document Frequency Document (sentence) -> words.
Terms Capital $D$: A corpus. Subbed (D_i) or lower $d_i$: i-th document in the corpus. TF https://en.wikipedia.org/wiki/Tf–idf
This term is irrelavant to the corpus (defined at each document).
Raw count There are several definitions of “term frequency.”
$$ f_{t,d_i} := \mathrm{the\ number\ of\ the\ words\ }t\ \mathrm{in\ the\ document\ } d_i $$
The most simple and “meaningful” for NLP is frequency form,
Open file with with statement with open("path/to/file", "r") as in_file blabla... Loop with index words = ["You", "are", "a", "genious", "!"] for i,word in enumerate(words): print(f"{i:{10}}{word:{12}}") Exit loop break