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22 Commits
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db937e4e58 | |||
279dbc885a |
3
.dvc/.gitignore
vendored
Normal file
3
.dvc/.gitignore
vendored
Normal file
@ -0,0 +1,3 @@
|
||||
/config.local
|
||||
/tmp
|
||||
/cache
|
4
.dvc/config
Normal file
4
.dvc/config
Normal file
@ -0,0 +1,4 @@
|
||||
[core]
|
||||
remote = ium_ssh_remote
|
||||
['remote "ium_ssh_remote"']
|
||||
url = ssh://ium-sftp@tzietkiewicz.vm.wmi.amu.edu.pl
|
3
.dvcignore
Normal file
3
.dvcignore
Normal file
@ -0,0 +1,3 @@
|
||||
# Add patterns of files dvc should ignore, which could improve
|
||||
# the performance. Learn more at
|
||||
# https://dvc.org/doc/user-guide/dvcignore
|
2
.gitignore
vendored
Normal file
2
.gitignore
vendored
Normal file
@ -0,0 +1,2 @@
|
||||
/Spotify_Dataset.csv
|
||||
/spotify_songs.csv
|
@ -1,17 +0,0 @@
|
||||
FROM ubuntu:latest
|
||||
|
||||
RUN apt-get update && \
|
||||
apt-get install -y \
|
||||
python3 \
|
||||
python3-pip \
|
||||
wget \
|
||||
unzip \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
RUN pip3 install pandas scikit-learn requests numpy
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
COPY model_creator.py /app/
|
||||
|
||||
RUN chmod +x model_creator.py
|
@ -1,39 +0,0 @@
|
||||
pipeline {
|
||||
agent any
|
||||
|
||||
triggers {
|
||||
upstream(upstreamProjects: 'z-s464953-create-dataset', threshold: hudson.model.Result.SUCCESS)
|
||||
}
|
||||
|
||||
parameters {
|
||||
string(name: 'TEST_SIZE', defaultValue: '0.10', description: 'Size of test dataset')
|
||||
string(name: 'MAX_ITER', defaultValue: '1000', description: 'Max number of iterations')
|
||||
buildSelector(defaultSelector: lastSuccessful(), description: 'Which build to use for copying artifacts', name: 'BUILD_SELECTOR')
|
||||
}
|
||||
|
||||
stages {
|
||||
stage('Clone Repository') {
|
||||
steps {
|
||||
git branch: 'training', url: 'https://git.wmi.amu.edu.pl/s464953/ium_464953.git'
|
||||
}
|
||||
}
|
||||
stage('Copy Artifacts') {
|
||||
steps {
|
||||
copyArtifacts filter: 'artifacts/*', projectName: 'z-s464953-create-dataset', selector: buildParameter('BUILD_SELECTOR')
|
||||
}
|
||||
}
|
||||
stage("Run Docker") {
|
||||
agent {
|
||||
dockerfile {
|
||||
filename 'Dockerfile'
|
||||
reuseNode true
|
||||
}
|
||||
}
|
||||
steps {
|
||||
|
||||
sh "python3 /app/model_creator.py ${params.TEST_SIZE} ${params.MAX_ITER}"
|
||||
archiveArtifacts artifacts: '/app/model.pkl', onlyIfSuccessful: true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
11
Dockerfile
11
Dockerfile
@ -2,16 +2,11 @@ FROM ubuntu:latest
|
||||
|
||||
RUN apt-get update && \
|
||||
apt-get install -y \
|
||||
python3 \
|
||||
python3 \
|
||||
python3-pip \
|
||||
git \
|
||||
wget \
|
||||
unzip \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
RUN pip3 install pandas scikit-learn requests numpy
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
COPY model_creator.py /app/
|
||||
|
||||
RUN chmod +x model_creator.py
|
||||
RUN pip3 install pandas scikit-learn requests kaggle numpy sacred pymongo --break-system-package
|
41
Jenkinsfile
vendored
41
Jenkinsfile
vendored
@ -1,38 +1,39 @@
|
||||
pipeline {
|
||||
agent any
|
||||
|
||||
triggers {
|
||||
upstream(upstreamProjects: 'z-s464953-create-dataset', threshold: hudson.model.Result.SUCCESS)
|
||||
}
|
||||
|
||||
parameters {
|
||||
string(name: 'TEST_SIZE', defaultValue: '0.10', description: 'Size of test dataset')
|
||||
string(name: 'MAX_ITER', defaultValue: '1000', description: 'Max number of iterations')
|
||||
buildSelector(defaultSelector: lastSuccessful(), description: 'Which build to use for copying artifacts', name: 'BUILD_SELECTOR')
|
||||
string(name: 'KAGGLE_USERNAME', defaultValue: 'gulczas', description: 'Kaggle username')
|
||||
password(name: 'KAGGLE_KEY', defaultValue: '', description: 'Kaggle API key')
|
||||
}
|
||||
|
||||
stages {
|
||||
stage('Clone Repository') {
|
||||
steps {
|
||||
git branch: 'training', url: 'https://git.wmi.amu.edu.pl/s464953/ium_464953.git'
|
||||
git 'https://git.wmi.amu.edu.pl/s464953/ium_464953.git'
|
||||
}
|
||||
}
|
||||
stage('Copy Artifacts') {
|
||||
stage('Cleanup Artifacts') {
|
||||
steps {
|
||||
copyArtifacts filter: 'artifacts/*', projectName: 'z-s464953-create-dataset', selector: buildParameter('BUILD_SELECTOR')
|
||||
}
|
||||
}
|
||||
stage("Run Docker") {
|
||||
agent {
|
||||
dockerfile {
|
||||
filename 'Dockerfile'
|
||||
reuseNode true
|
||||
script {
|
||||
sh 'rm -rf artifacts'
|
||||
}
|
||||
}
|
||||
}
|
||||
stage('Run Script') {
|
||||
steps {
|
||||
|
||||
sh "python3 /app/model_creator.py ${params.TEST_SIZE} ${params.MAX_ITER}"
|
||||
archiveArtifacts artifacts: 'model.pkl, artifacts/docker_test_dataset.csv', onlyIfSuccessful: true
|
||||
script {
|
||||
withEnv([
|
||||
"KAGGLE_USERNAME=${env.KAGGLE_USERNAME}",
|
||||
"KAGGLE_KEY=${env.KAGGLE_KEY}"])
|
||||
{
|
||||
sh "bash ./download_dataset.sh"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
stage('Archive Artifacts') {
|
||||
steps {
|
||||
archiveArtifacts artifacts: 'artifacts/*', onlyIfSuccessful: true
|
||||
}
|
||||
}
|
||||
}
|
||||
|
57
Jenkinsfile-docker-image-build
Normal file
57
Jenkinsfile-docker-image-build
Normal file
@ -0,0 +1,57 @@
|
||||
pipeline {
|
||||
agent any
|
||||
|
||||
parameters {
|
||||
string(name: 'KAGGLE_USERNAME', defaultValue: 'gulczas', description: 'Kaggle username')
|
||||
password(name: 'KAGGLE_KEY', defaultValue: '', description: 'Kaggle API key')
|
||||
}
|
||||
|
||||
stages {
|
||||
stage('Clone Repository') {
|
||||
steps {
|
||||
git 'https://git.wmi.amu.edu.pl/s464953/ium_464953.git'
|
||||
}
|
||||
}
|
||||
|
||||
stage('Stop and remove existing container') {
|
||||
steps {
|
||||
script {
|
||||
sh "docker stop s464953 || true"
|
||||
sh "docker rm s464953 || true"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
stage('Build Docker image') {
|
||||
steps {
|
||||
script {
|
||||
withEnv([
|
||||
"KAGGLE_USERNAME=${env.KAGGLE_USERNAME}",
|
||||
"KAGGLE_KEY=${env.KAGGLE_KEY}"
|
||||
]) {
|
||||
sh "docker build --build-arg KAGGLE_USERNAME=$KAGGLE_USERNAME --build-arg KAGGLE_KEY=$KAGGLE_KEY -t s464953 ."
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
stage('Run Docker container') {
|
||||
steps {
|
||||
script {
|
||||
withEnv([
|
||||
"KAGGLE_USERNAME=${env.KAGGLE_USERNAME}",
|
||||
"KAGGLE_KEY=${env.KAGGLE_KEY}"
|
||||
]) {
|
||||
sh "docker run --name s464953 -e KAGGLE_USERNAME=$KAGGLE_USERNAME -e KAGGLE_KEY=$KAGGLE_KEY -v ${WORKSPACE}:/app s464953"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
stage('Archive stats.txt artifact') {
|
||||
steps {
|
||||
archiveArtifacts artifacts: 'stats.txt', allowEmptyArchive: true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
44
Jenkinsfile-docker-image-pull
Normal file
44
Jenkinsfile-docker-image-pull
Normal file
@ -0,0 +1,44 @@
|
||||
pipeline {
|
||||
agent any
|
||||
|
||||
parameters {
|
||||
string(name: 'KAGGLE_USERNAME', defaultValue: 'gulczas', description: 'Kaggle username')
|
||||
password(name: 'KAGGLE_KEY', defaultValue: '', description: 'Kaggle API key')
|
||||
}
|
||||
|
||||
stages {
|
||||
stage('Clone Repository') {
|
||||
steps {
|
||||
git 'https://git.wmi.amu.edu.pl/s464953/ium_464953.git'
|
||||
}
|
||||
}
|
||||
|
||||
stage('Stop and remove existing container') {
|
||||
steps {
|
||||
script {
|
||||
sh "docker stop s464953 || true"
|
||||
sh "docker rm s464953 || true"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
stage('Run Docker container') {
|
||||
steps {
|
||||
script {
|
||||
withEnv([
|
||||
"KAGGLE_USERNAME=${env.KAGGLE_USERNAME}",
|
||||
"KAGGLE_KEY=${env.KAGGLE_KEY}"
|
||||
]) {
|
||||
sh "docker run --name s464953 -e KAGGLE_USERNAME=$KAGGLE_USERNAME -e KAGGLE_KEY=$KAGGLE_KEY -v ${WORKSPACE}:/app michalgulczynski/ium_s464953:1.0"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
stage('Archive stats.txt artifact') {
|
||||
steps {
|
||||
archiveArtifacts artifacts: 'stats.txt', allowEmptyArchive: true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
57
Jenkinsfile-ium-6
Normal file
57
Jenkinsfile-ium-6
Normal file
@ -0,0 +1,57 @@
|
||||
pipeline {
|
||||
agent any
|
||||
|
||||
parameters {
|
||||
string(name: 'KAGGLE_USERNAME', defaultValue: 'gulczas', description: 'Kaggle username')
|
||||
password(name: 'KAGGLE_KEY', defaultValue: '', description: 'Kaggle API key')
|
||||
}
|
||||
|
||||
stages {
|
||||
stage('Clone Repository') {
|
||||
steps {
|
||||
git 'https://git.wmi.amu.edu.pl/s464953/ium_464953.git'
|
||||
}
|
||||
}
|
||||
|
||||
stage('Stop and remove existing container') {
|
||||
steps {
|
||||
script {
|
||||
sh "docker stop s464953 || true"
|
||||
sh "docker rm s464953 || true"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
stage('Build Docker image') {
|
||||
steps {
|
||||
script {
|
||||
withEnv([
|
||||
"KAGGLE_USERNAME=${env.KAGGLE_USERNAME}",
|
||||
"KAGGLE_KEY=${env.KAGGLE_KEY}"
|
||||
]) {
|
||||
sh "docker build --build-arg KAGGLE_USERNAME=$KAGGLE_USERNAME --build-arg KAGGLE_KEY=$KAGGLE_KEY -t s464953 ."
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
stage('Run Docker container') {
|
||||
steps {
|
||||
script {
|
||||
withEnv([
|
||||
"KAGGLE_USERNAME=${env.KAGGLE_USERNAME}",
|
||||
"KAGGLE_KEY=${env.KAGGLE_KEY}"
|
||||
]) {
|
||||
sh "docker run --name s464953 -e KAGGLE_USERNAME=$KAGGLE_USERNAME -e KAGGLE_KEY=$KAGGLE_KEY -v ${WORKSPACE}:/app s464953"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
stage('Archive stats.txt artifact') {
|
||||
steps {
|
||||
archiveArtifacts artifacts: 'model.pkl', allowEmptyArchive: true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
42
Jenkinsfile-stats
Normal file
42
Jenkinsfile-stats
Normal file
@ -0,0 +1,42 @@
|
||||
pipeline {
|
||||
agent any
|
||||
|
||||
parameters {
|
||||
buildSelector( defaultSelector: lastSuccessful(), description: 'Build for copying artifacts', name: 'BUILD_SELECTOR')
|
||||
}
|
||||
|
||||
stages {
|
||||
stage('Clone Repository') {
|
||||
steps {
|
||||
git 'https://git.wmi.amu.edu.pl/s464953/ium_464953.git'
|
||||
}
|
||||
}
|
||||
stage('Cleanup Artifacts') {
|
||||
steps {
|
||||
script {
|
||||
sh 'rm -rf artifacts'
|
||||
}
|
||||
}
|
||||
}
|
||||
stage('Copy Artifact') {
|
||||
steps {
|
||||
withEnv([
|
||||
"BUILD_SELECTOR=${params.BUILD_SELECTOR}"
|
||||
]) {
|
||||
copyArtifacts fingerprintArtifacts: true, projectName: 'z-s464953-create-dataset', selector: buildParameter('$BUILD_SELECTOR')}
|
||||
}
|
||||
}
|
||||
stage('Execute Shell Script') {
|
||||
steps {
|
||||
script {
|
||||
sh "bash ./dataset_stats.sh"
|
||||
}
|
||||
}
|
||||
}
|
||||
stage('Archive Results') {
|
||||
steps {
|
||||
archiveArtifacts artifacts: 'artifacts/*', onlyIfSuccessful: true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
50
Jenkinsfile_sacred
Normal file
50
Jenkinsfile_sacred
Normal file
@ -0,0 +1,50 @@
|
||||
pipeline {
|
||||
agent any
|
||||
|
||||
parameters {
|
||||
string(name: 'KAGGLE_USERNAME', defaultValue: 'gulczas', description: 'Kaggle username')
|
||||
password(name: 'KAGGLE_KEY', defaultValue: '', description: 'Kaggle API key')
|
||||
}
|
||||
|
||||
stages {
|
||||
stage('Clone Repository') {
|
||||
steps {
|
||||
git 'https://git.wmi.amu.edu.pl/s464953/ium_464953.git'
|
||||
}
|
||||
}
|
||||
|
||||
stage('Download datasets') {
|
||||
steps {
|
||||
withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}", "KAGGLE_KEY=${params.KAGGLE_KEY}"]) {
|
||||
sh "bash ./download_dataset.sh"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
stage('Build and Run Experiments') {
|
||||
agent {
|
||||
dockerfile {
|
||||
reuseNode true
|
||||
}
|
||||
}
|
||||
|
||||
environment {
|
||||
KAGGLE_USERNAME = "${params.KAGGLE_USERNAME}"
|
||||
KAGGLE_KEY = "${params.KAGGLE_KEY}"
|
||||
}
|
||||
|
||||
steps {
|
||||
sh 'chmod +x sacred/sacred_model_creator.py'
|
||||
sh 'python3 sacred/sacred_model_creator.py'
|
||||
sh 'chmod +x sacred/sacred_use_model.py'
|
||||
sh 'python3 sacred/sacred_use_model.py'
|
||||
}
|
||||
}
|
||||
|
||||
stage('Archive Artifacts from Experiments') {
|
||||
steps {
|
||||
archiveArtifacts artifacts: 'my_experiment_logs/**', allowEmptyArchive: true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
11
MLProject/MLProject
Normal file
11
MLProject/MLProject
Normal file
@ -0,0 +1,11 @@
|
||||
name: MLflow Example
|
||||
|
||||
conda_env: conda.yaml
|
||||
|
||||
entry_points:
|
||||
main:
|
||||
command: "python model_creator.py {max_iter}"
|
||||
parameters:
|
||||
max_iter: {type: int, default: 1000}
|
||||
test:
|
||||
command: "python use_model.py"
|
651937
MLProject/Spotify_Dataset.csv
Normal file
651937
MLProject/Spotify_Dataset.csv
Normal file
File diff suppressed because it is too large
Load Diff
11
MLProject/conda.yaml
Normal file
11
MLProject/conda.yaml
Normal file
@ -0,0 +1,11 @@
|
||||
name: Spotify genre recognition - s464953
|
||||
channels:
|
||||
- defaults
|
||||
dependencies:
|
||||
- python=3.9
|
||||
- pip
|
||||
- pip:
|
||||
- mlflow
|
||||
- pandas
|
||||
- scikit-learn
|
||||
- numpy
|
10001
MLProject/docker_test_dataset.csv
Normal file
10001
MLProject/docker_test_dataset.csv
Normal file
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,20 @@
|
||||
artifact_path: model
|
||||
flavors:
|
||||
python_function:
|
||||
env:
|
||||
conda: conda.yaml
|
||||
virtualenv: python_env.yaml
|
||||
loader_module: mlflow.sklearn
|
||||
model_path: model.pkl
|
||||
predict_fn: predict
|
||||
python_version: 3.9.19
|
||||
sklearn:
|
||||
code: null
|
||||
pickled_model: model.pkl
|
||||
serialization_format: cloudpickle
|
||||
sklearn_version: 1.4.2
|
||||
mlflow_version: 2.12.2
|
||||
model_size_bytes: 1446
|
||||
model_uuid: 9026270861774aad82aee9fc231054b4
|
||||
run_id: 04eba1c93f6a4510b4487ad0789fa76f
|
||||
utc_time_created: '2024-05-13 21:25:05.523657'
|
@ -0,0 +1,15 @@
|
||||
channels:
|
||||
- conda-forge
|
||||
dependencies:
|
||||
- python=3.9.19
|
||||
- pip<=24.0
|
||||
- pip:
|
||||
- mlflow==2.12.2
|
||||
- cloudpickle==3.0.0
|
||||
- numpy==1.26.4
|
||||
- packaging==23.1
|
||||
- psutil==5.9.5
|
||||
- pyyaml==6.0.1
|
||||
- scikit-learn==1.4.2
|
||||
- scipy==1.13.0
|
||||
name: mlflow-env
|
@ -0,0 +1,20 @@
|
||||
artifact_path: model
|
||||
flavors:
|
||||
python_function:
|
||||
env:
|
||||
conda: conda.yaml
|
||||
virtualenv: python_env.yaml
|
||||
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|
||||
utc_time_created: '2024-05-13 20:51:58.533911'
|
@ -0,0 +1,15 @@
|
||||
channels:
|
||||
- conda-forge
|
||||
dependencies:
|
||||
- python=3.9.19
|
||||
- pip<=24.0
|
||||
- pip:
|
||||
- mlflow==2.12.2
|
||||
- cloudpickle==3.0.0
|
||||
- numpy==1.26.4
|
||||
- packaging==23.1
|
||||
- psutil==5.9.5
|
||||
- pyyaml==6.0.1
|
||||
- scikit-learn==1.4.2
|
||||
- scipy==1.13.0
|
||||
name: mlflow-env
|
@ -0,0 +1,20 @@
|
||||
artifact_path: model
|
||||
flavors:
|
||||
python_function:
|
||||
env:
|
||||
conda: conda.yaml
|
||||
virtualenv: python_env.yaml
|
||||
loader_module: mlflow.sklearn
|
||||
model_path: model.pkl
|
||||
predict_fn: predict
|
||||
python_version: 3.9.19
|
||||
sklearn:
|
||||
code: null
|
||||
pickled_model: model.pkl
|
||||
serialization_format: cloudpickle
|
||||
sklearn_version: 1.4.2
|
||||
mlflow_version: 2.12.2
|
||||
model_size_bytes: 1446
|
||||
model_uuid: c575ab1b63c840b1b87f2c5d6a51721c
|
||||
run_id: ef10e2199a2346dabe10eb9e7bdea061
|
||||
utc_time_created: '2024-05-13 20:51:58.533911'
|
@ -0,0 +1,15 @@
|
||||
channels:
|
||||
- conda-forge
|
||||
dependencies:
|
||||
- python=3.9.19
|
||||
- pip<=24.0
|
||||
- pip:
|
||||
- mlflow==2.12.2
|
||||
- cloudpickle==3.0.0
|
||||
- numpy==1.26.4
|
||||
- packaging==23.1
|
||||
- psutil==5.9.5
|
||||
- pyyaml==6.0.1
|
||||
- scikit-learn==1.4.2
|
||||
- scipy==1.13.0
|
||||
name: mlflow-env
|
@ -0,0 +1,7 @@
|
||||
python: 3.9.19
|
||||
build_dependencies:
|
||||
- pip==24.0
|
||||
- setuptools
|
||||
- wheel==0.43.0
|
||||
dependencies:
|
||||
- -r requirements.txt
|
@ -0,0 +1,8 @@
|
||||
mlflow==2.12.2
|
||||
cloudpickle==3.0.0
|
||||
numpy==1.26.4
|
||||
packaging==23.1
|
||||
psutil==5.9.5
|
||||
pyyaml==6.0.1
|
||||
scikit-learn==1.4.2
|
||||
scipy==1.13.0
|
Binary file not shown.
@ -0,0 +1,7 @@
|
||||
python: 3.9.19
|
||||
build_dependencies:
|
||||
- pip==24.0
|
||||
- setuptools
|
||||
- wheel==0.43.0
|
||||
dependencies:
|
||||
- -r requirements.txt
|
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue
Block a user