import platform


class Application(object):
    directory = {'data': './data/', 'model': './model/', }
    model = {'app_data': directory['model'] + 'app.data', 'predict': '.predict',
             'all_data': directory['model'] + 'app.data'}
    data = {'emb_file': directory['data'] + 'glove.840B.300d.txt',
            'data_file': directory['data'] + 'quora_duplicate_questions.tsv'}
    model_params = {'epochs': 3, 'batch_size': 256, 'max_sequence_length': 64, 'lr': 0.001,
                    'system': 'Linux', 'num_nn': 256, 'num_dense': 300, 'head': 8}
    learner = {'ap_bi_gru': 0.8665, 'ap_bi_lstm': 0.8654, 'ap_cnn': 0.8518, 'bi_gru': 0.8598, 'bi_lstm': 0.8569,
               'cnn': 0.852, 'multi_attention': 0.8547, 'bi_gru_multi_attention': 0.86}

    def __init__(self):
        system = platform.system()
        if system == "Linux":
            self.model_params['batch_size'] = 64
            self.model_params['epochs'] = 15
            self.model['app_data'] = self.directory['model'] + 'app.data'
        else:
            self.model_params['system'] = system
            self.model['app_data'] = self.directory['model'] + 'app.data'
