def __init__(self, **argparams):
    self.train_data = argparams['train_data']
    if (self.train_data is not None):
        assert isinstance(self.train_data, DataSetCSVslotTagging)
    self.test_data = argparams['test_data']
    if (self.test_data is not None):
        assert isinstance(self.test_data, DataSetCSVslotTagging)
    self.dev_data = argparams['dev_data']
    if (self.dev_data is not None):
        assert isinstance(self.dev_data, DataSetCSVslotTagging)
    self.model_folder = argparams['model_folder']
    if (self.model_folder is None):
        pid = argparams['pid']
        self.model_folder = './model/slot_{}'.format(pid)
        os.makedirs('{}/weights'.format(self.model_folder))
        os.makedirs('{}/dev_results'.format(self.model_folder))
    self.epoch_nb = argparams['epoch_nb']
    self.batch_size = argparams['batch_size']
    self.embedding_size = argparams['embedding_size']
    self.hidden_size = argparams['hidden_size']
    self.dropout = argparams['dropout_ratio']
    self.optimizer = argparams['optimizer']
    self.patience = argparams['patience']
    self.loss = argparams['loss']
    self.test_tag_flag = argparams['test_tag_only']
    self.test_intent_flag = argparams['test_intent_only']
    self.threshold = argparams['threshold']
    self.weights_fname = argparams['weights_fname']
    self.params = argparams
def __init__(self, **argparams):
    self.train_data = argparams['train_data']
    if (self.train_data is not None):
        assert isinstance(self.train_data, DataSetCSVslotTagging)
    self.test_data = argparams['test_data']
    if (self.test_data is not None):
        assert isinstance(self.test_data, DataSetCSVslotTagging)
    self.dev_data = argparams['dev_data']
    if (self.dev_data is not None):
        assert isinstance(self.dev_data, DataSetCSVslotTagging)
    self.model_folder = argparams['model_folder']
    if (self.model_folder is None):
        pid = argparams['pid']
        self.model_folder = './model/slot_{}'.format(pid)
        os.makedirs('{}/weights'.format(self.model_folder))
        os.makedirs('{}/dev_results'.format(self.model_folder))
    self.epoch_nb = argparams['epoch_nb']
    self.batch_size = argparams['batch_size']
    self.embedding_size = argparams['embedding_size']
    self.hidden_size = argparams['hidden_size']
    self.dropout = argparams['dropout_ratio']
    self.optimizer = argparams['optimizer']
    self.patience = argparams['patience']
    self.loss = argparams['loss']
    self.test_tag_flag = argparams['test_tag_only']
    self.test_intent_flag = argparams['test_intent_only']
    self.threshold = argparams['threshold']
    self.weights_fname = argparams['weights_fname']
    self.params = argparams