fix
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@ -19,7 +19,7 @@ pipeline {
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}
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}
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stage('copy_artifacts') {
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stage('copy_artifacts') {
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steps {
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steps {
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copyArtifacts filter: 'adult_test.csv,adult_dev.csv,adult_train.csv', fingerprintArtifacts: true, projectName: 'z-s444439-create-dataset', selector: workspace()
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copyArtifacts filter: 'X_test.csv,X_dev.csv,X_train.csv', fingerprintArtifacts: true, projectName: 'z-s444439-create-dataset', selector: workspace()
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}
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}
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}
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}
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stage('Docker') {
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stage('Docker') {
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@ -3,10 +3,17 @@ import numpy as np
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import tensorflow as tf
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import tensorflow as tf
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import pandas as pd
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import pandas as pd
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test_data = pd.read_csv("adult_test.csv")
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data = tf.keras.models.load_model('model')
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model = keras.models.load_model("model.h5")
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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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predictions = model.predict(test_data)
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accu = data.evaluate(x_to_test, y_to_test)
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np.savetxt("predictions.csv", predictions, delimiter=",")
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with open('metrics.csv', 'a') as file:
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file.write(f'1,{accu}\n')
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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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