def hypothesis_linear(features, feature_columns, options):
    
    import tensorflow as tf
    from train.train_tools import weight_summary

    with tf.name_scope('Linear'):
    
        all_feature_columns = feature_columns['wide'] + feature_columns['deep']

        input_layer = tf.feature_column.input_layer( 
            features, feature_columns=all_feature_columns)

        out = tf.layers.dense(input_layer, 1, activation=None)
        weight_summary(out)
    
    return out

def hypothesis_linear(features, feature_columns, options):
    
    import tensorflow as tf
    from train.train_tools import weight_summary

    with tf.name_scope('Linear'):
    
        all_feature_columns = feature_columns['wide'] + feature_columns['deep']

        input_layer = tf.feature_column.input_layer( 
            features, feature_columns=all_feature_columns)

        out = tf.layers.dense(input_layer, 1, activation=None)
        weight_summary(out)
    
    return out
