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@ -13,7 +13,7 @@ pipeline {
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}
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stage('Train model with sacred') {
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steps {
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sh "python3 IUM_07/deepLearning_sacred.py $epoch"
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sh "python3 lab07_sacred.py $epoch"
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}
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}
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}
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@ -41,15 +41,15 @@ class Model(nn.Module):
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def load_dataset_raw():
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""" Load data from .csv file. """
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cars = pd.read_csv('../c/Car_Prices_Poland_Kaggle.csv', usecols=[1, 4, 5, 6, 10], sep=',')
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cars = pd.read_csv('./Car_Prices_Poland_Kaggle.csv', usecols=[1, 4, 5, 6, 10], sep=',')
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return cars
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def load_dataset_files():
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""" Load shuffled, splitted dev and train files from .csv files. """
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cars_dev = pd.read_csv('../Car_Prices_Poland_Kaggle_dev.csv', usecols=[1, 4, 5, 6, 10], sep=',', names= [str(i) for i in range(5)])
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cars_train = pd.read_csv('../Car_Prices_Poland_Kaggle_train.csv', usecols=[1, 4, 5, 6, 10], sep=',', names= [str(i) for i in range(5)])
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cars_dev = pd.read_csv('./Car_Prices_Poland_Kaggle_dev.csv', usecols=[1, 4, 5, 6, 10], sep=',', names= [str(i) for i in range(5)])
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cars_train = pd.read_csv('./Car_Prices_Poland_Kaggle_train.csv', usecols=[1, 4, 5, 6, 10], sep=',', names= [str(i) for i in range(5)])
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return cars_dev, cars_train
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