2023-05-11 19:00:42 +02:00
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import os
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2023-05-11 18:11:43 +02:00
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import tensorflow as tf
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2023-05-10 22:50:54 +02:00
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import pandas as pd
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2023-05-11 19:00:42 +02:00
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build_no = int(os.environ['BUILD_NUMBER'])
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2023-05-11 18:32:15 +02:00
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data = tf.keras.models.load_model('model')
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2023-05-10 22:50:54 +02:00
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2023-05-11 18:32:15 +02:00
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x_to_test = pd.read_csv('./X_test.csv')
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y_to_test = pd.read_csv('./Y_test.csv')
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2023-05-10 22:50:54 +02:00
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2023-05-11 18:32:15 +02:00
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accu = data.evaluate(x_to_test, y_to_test)
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2023-05-10 22:50:54 +02:00
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2023-05-11 18:32:15 +02:00
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with open('metrics.csv', 'a') as file:
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2023-05-11 19:00:42 +02:00
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file.write(f'{build_no},{accu}\n')
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2023-05-11 18:32:15 +02:00
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pre = data.predict(x_to_test)
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pre.tofile('prediction.csv', sep=',', format='%s')
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