<commit_before>import sys, os
sys.path.insert(1, "../../../")
import h2o

def deeplearning_multi(ip, port):
    h2o.init(ip, port)

    print("Test checks if Deep Learning works fine with a multiclass training and test dataset")

    prostate = h2o.import_frame("smalldata/logreg/prostate.csv")

    hh = h2o.deeplearning(x             = prostate[0:2],
                          y             = prostate[4],
                          validation_x  = prostate[0:2],
                          validation_y  = prostate[4])
    hh.show()

if __name__ == '__main__':
    h2o.run_test(argv, deeplearning_multi)<commit_msg>should be sys.argv not argv<commit_after>import sys, os
sys.path.insert(1, "../../../")
import h2o

def deeplearning_multi(ip, port):
    h2o.init(ip, port)

    print("Test checks if Deep Learning works fine with a multiclass training and test dataset")

    prostate = h2o.import_frame("smalldata/logreg/prostate.csv")

    hh = h2o.deeplearning(x             = prostate[0:2],
                          y             = prostate[4],
                          validation_x  = prostate[0:2],
                          validation_y  = prostate[4])
    hh.show()

if __name__ == '__main__':
    h2o.run_test(sys.argv, deeplearning_multi)
{'fraction_non_alphanumeric': 0.12, 'fraction_numerical': 0.0192, 'mean_word_length': 2.058679706601467, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2894389', 'n_tokens_mistral': 409, 'n_tokens_neox': 389, 'n_words': 87}