ium_z486867/predict.py
mikaleta-mbm 42ebc25f24 jenkins 2
2023-09-30 00:10:57 +02:00

21 lines
529 B
Python

import os
import tensorflow as tf
import pandas as pd
from keras import utils
build_number = int(os.environ['BUILD_NUMBER'])
model = tf.keras.models.load_model('model')
x_to_test = pd.read_csv('./X_test.csv')
y_to_test = pd.read_csv('./Y_test.csv')
y_to_test = utils.to_categorical(y_to_test)
metrics = model.evaluate(x_to_test, y_to_test)
with open('metrics.csv', 'a') as file:
file.write(f'{build_number},{metrics}\n')
predictions = model.predict(x_to_test)
predictions.tofile('prediction.csv', sep=',', format='%s')