예제 #1
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def potager():
    if request.json["action"] == "on":
        return {'message': core.main("on", "potager", request.json['temps'])}
    elif request.json["action"] == "off":
        return {'message': core.stop_gpio()}
예제 #2
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# main project
from app.core import main

if __name__ == '__main__':
    main()
예제 #3
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import random

from app.core import main
from app.utils.dataset import DatasetManager

if __name__ == '__main__':
    kind = DatasetManager.KIND_MOVIELENS_100K
    # kind = DatasetManager.KIND_MOVIELENS_1M
    # kind = DatasetManager.KIND_MOVIELENS_10M

    hyper_params = {
        'K': 7,
        'lambda_value': 10,
    }
    valid_rmse, test_rmse = main(kind, **hyper_params)

    print('\t'.join(sorted(hyper_params.keys())))
    msg = '{}\t{}\t{}'.format(
        '\t'.join(
            str(hyper_params[key]) for key in sorted(hyper_params.keys())),
        valid_rmse, test_rmse)
    print(msg)

    # with open('results/ml-100k.txt', 'a') as f:
    #     f.write(msg + '\n')
예제 #4
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import argparse
from app.core import main
from argparse import ArgumentParser
import sys
parser = ArgumentParser()
parser.add_argument("--inputfile", help="filename of the input file")
parser.add_argument("--outputfile", help="filename of the output file")
parser.add_argument("--bucketcount", help="buckercount number", type=int)
args = parser.parse_args()
main(inputfile=args.inputfile,
     outputfile=args.outputfile,
     bucketcount=args.bucketcount)
예제 #5
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            win, lose = d[(user_id, item_id)]
            full_data[i][0] = user_id
            full_data[i][1] = item_id
            full_data[i][2] = win
            full_data[i][3] = lose
            full_data[i][4] = win / (win + lose)
            full_data[i][5] = win + lose

        mask = np.ones(full_data.shape[0])  # 1: train mask
        mask[np.random.rand(full_data.shape[0]) < 0.02] = 2  # 2: valid mask
        mask[np.random.rand(full_data.shape[0]) < 0.1] = 3  # 3: test mask

        train_data = full_data[mask == 1, :]
        valid_data = full_data[mask == 2, :]
        test_data = full_data[mask == 3, :]

        np.save('train.npy', train_data)
        np.save('valid.npy', valid_data)
        np.save('test.npy', test_data)

    return {
        'train': _get_dict_from_data(train_data),
        'valid': _get_dict_from_data(valid_data),
        'test': _get_dict_from_data(test_data),
    }


if __name__ == '__main__':
    data = _init_data()
    main(data)