2023-05-10 20:29:50 +02:00
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import pandas
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import os
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from keras.applications.densenet import layers
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from sklearn.model_selection import train_test_split
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import tensorflow
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2023-05-11 00:31:05 +02:00
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build_number = int(os.environ['BUILD_NUMBER'])
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2023-05-10 20:29:50 +02:00
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2023-05-10 23:09:01 +02:00
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reloaded = tensorflow.keras.models.load_model('test')
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2023-05-10 20:22:22 +02:00
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x_to_test = pandas.read_csv('./X_test.csv')
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y_to_test = pandas.read_csv('./Y_test.csv')
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2023-05-10 20:32:32 +02:00
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accu = reloaded.evaluate(x_to_test, y_to_test)
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2023-05-10 20:22:22 +02:00
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2023-05-11 00:31:05 +02:00
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2023-05-10 23:49:08 +02:00
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with open('metrics.csv', 'a') as file:
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2023-05-11 00:31:05 +02:00
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file.write(f'{build_number},{accu}\n')
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2023-05-10 20:41:43 +02:00
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2023-05-10 20:32:32 +02:00
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pre = reloaded.predict(x_to_test)
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2023-05-10 20:41:43 +02:00
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2023-05-10 20:49:17 +02:00
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pre.tofile('prediction.csv', sep=',', format='%s')
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