Add model fetching from mlflow registry
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Jenkinsfile_coop_registry
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Jenkinsfile_coop_registry
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pipeline {
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agent {dockerfile true, args '-v /tmp/mlruns:/tmp/mlruns'}
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parameters {
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string(
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defaultValue: 'input_example.json',
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description: 'Input name',
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name: 'INPUT_NAME',
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trim: false
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)
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}
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stages {
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stage('Load model and run prediction') {
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steps {
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sh 'python3 mlflow_prediction_registry.py $INPUT_NAME'
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}
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}
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}
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}
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mlflow_prediction_registry.py
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mlflow_prediction_registry.py
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import json
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import mlflow
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from mlflow.tracking import MlflowClient
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import mlflow.pyfunc
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import torch
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import numpy as np
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import pandas as pd
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import sys
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arguments = sys.argv[1:]
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mlflow.set_tracking_uri("http://172.17.0.1:5000")
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client = MlflowClient()
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version = 1
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model_name = "s434704"
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input = str(arguments[0])
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model = mlflow.pyfunc.load_model(
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model_uri=f"models:/{model_name}/{model_version}"
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)
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with open(f'{model_name}/{input}', 'r') as file:
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json_data = json.load(file)
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print(model(torch.tensor(np.array(json_data['inputs'])).float()))
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