Add model fetching from mlflow registry
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This commit is contained in:
Wojciech Jarmosz 2021-05-23 21:42:55 +02:00
parent 8c94666b25
commit b3e254c3a5
2 changed files with 47 additions and 0 deletions

19
Jenkinsfile_coop_registry Normal file
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pipeline {
agent {dockerfile true, args '-v /tmp/mlruns:/tmp/mlruns'}
parameters {
string(
defaultValue: 'input_example.json',
description: 'Input name',
name: 'INPUT_NAME',
trim: false
)
}
stages {
stage('Load model and run prediction') {
steps {
sh 'python3 mlflow_prediction_registry.py $INPUT_NAME'
}
}
}
}

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import json
import mlflow
from mlflow.tracking import MlflowClient
import mlflow.pyfunc
import torch
import numpy as np
import pandas as pd
import sys
arguments = sys.argv[1:]
mlflow.set_tracking_uri("http://172.17.0.1:5000")
client = MlflowClient()
version = 1
model_name = "s434704"
input = str(arguments[0])
model = mlflow.pyfunc.load_model(
model_uri=f"models:/{model_name}/{model_version}"
)
with open(f'{model_name}/{input}', 'r') as file:
json_data = json.load(file)
print(model(torch.tensor(np.array(json_data['inputs'])).float()))