Пример #1
0
    def setUpClass(cls):

        cls.n_user_features = 200
        cls.n_item_features = 150

        cls.interactions, cls.user_features, cls.item_features = generate_dummy_data(
            num_users=15,
            num_items=30,
            interaction_density=.5,
            num_user_features=cls.n_user_features,
            num_item_features=cls.n_item_features,
            n_features_per_user=20,
            n_features_per_item=20,
            pos_int_ratio=.5)

        set_session(None)
        cls.temp_dir = tempfile.mkdtemp()
        cls.interactions_path = os.path.join(cls.temp_dir,
                                             'interactions.tfrecord')
        cls.user_features_path = os.path.join(cls.temp_dir,
                                              'user_features.tfrecord')
        cls.item_features_path = os.path.join(cls.temp_dir,
                                              'item_features.tfrecord')

        write_tfrecord_from_sparse_matrix(cls.user_features_path,
                                          cls.user_features, get_session())
        write_tfrecord_from_sparse_matrix(cls.item_features_path,
                                          cls.item_features, get_session())
        write_tfrecord_from_sparse_matrix(cls.interactions_path,
                                          cls.interactions, get_session())
Пример #2
0
    def setUpClass(cls):

        # Blow away an existing session to avoid 'tf_map_func not found' error
        set_session(None)

        cls.n_users = 15
        cls.n_items = 30

        int_ds, uf_ds, if_ds = generate_dummy_data(num_users=cls.n_users,
                                                   num_items=cls.n_items,
                                                   interaction_density=.5,
                                                   num_user_features=200,
                                                   num_item_features=200,
                                                   n_features_per_user=20,
                                                   n_features_per_item=20,
                                                   pos_int_ratio=.5)

        cls.temp_dir = tempfile.mkdtemp()
        cls.interactions = os.path.join(cls.temp_dir, 'interactions.tfrecord')
        cls.user_features = os.path.join(cls.temp_dir,
                                         'user_features.tfrecord')
        cls.item_features = os.path.join(cls.temp_dir,
                                         'item_features.tfrecord')

        write_tfrecord_from_sparse_matrix(cls.interactions, int_ds,
                                          get_session())
        write_tfrecord_from_sparse_matrix(cls.user_features, uf_ds,
                                          get_session())
        write_tfrecord_from_sparse_matrix(cls.item_features, if_ds,
                                          get_session())

        cls.standard_model = TensorRec(n_components=10)
        cls.standard_model.fit(cls.interactions,
                               cls.user_features,
                               cls.item_features,
                               epochs=10)

        cls.unbiased_model = TensorRec(n_components=10, biased=False)
        cls.unbiased_model.fit(cls.interactions,
                               cls.user_features,
                               cls.item_features,
                               epochs=10)
Пример #3
0
 def setUpClass(cls):
     cls.session = get_session()
 def setUpClass(cls):
     cls.session = get_session()