def test_only_with_number_features():
number_features = [
Number('userAge', StandardScaler()),
Number('rating', StandardScaler())
]
category_features = []
sequence_features = []
features = Features(number_features=number_features,
category_features=category_features,
sequence_features=sequence_features)
wide_features = ['rating', 'userAge']
dataloader, _ = prepare_dataloader(features)
model = WideDeep(features,
wide_features, [], [],
num_classes=2,
embedding_size=4,
hidden_layers=(8, 4),
final_activation='sigmoid',
dropout=0.3)
model(next(iter(dataloader)))
def test_without_category_feature():
number_features = []
category_features = []
sequence_features = [
Sequence('title', SequenceEncoder(sep='|', min_cnt=1)),
Sequence('genres', SequenceEncoder(sep='|', min_cnt=1)),
Sequence('clickedMovieIds',
SequenceEncoder(sep='|', min_cnt=1, max_len=5)),
Sequence('clickedMovieTopGenres',
SequenceEncoder(sep='|', min_cnt=1, max_len=5))
]
features = Features(number_features=number_features,
category_features=category_features,
sequence_features=sequence_features)
wide_features = ['title', 'genres']
deep_features = ['clickedMovieIds', 'clickedMovieTopGenres']
dataloader, _ = prepare_dataloader(features)
model = WideDeep(features,
wide_features,
deep_features, [],
num_classes=2,
embedding_size=4,
hidden_layers=(8, 4),
final_activation='sigmoid',
dropout=0.3)
model(next(iter(dataloader)))
def test_normal():
number_features = [
Number('userAge', StandardScaler()),
Number('rating', StandardScaler())
]
category_features = [
Category('userId', CategoryEncoder(min_cnt=1)),
Category('movieId', CategoryEncoder(min_cnt=1)),
Category('topGenre', CategoryEncoder(min_cnt=1))
]
sequence_features = [
Sequence('title', SequenceEncoder(sep='|', min_cnt=1)),
Sequence('genres', SequenceEncoder(sep='|', min_cnt=1)),
Sequence('clickedMovieIds',
SequenceEncoder(sep='|', min_cnt=1, max_len=5)),
Sequence('clickedMovieTopGenres',
SequenceEncoder(sep='|', min_cnt=1, max_len=5))
]
features = Features(number_features=number_features,
category_features=category_features,
sequence_features=sequence_features)
wide_features = ['rating', 'title', 'genres']
deep_features = [
'userAge', 'rating', 'userId', 'movieId', 'topGenre',
'clickedMovieIds', 'clickedMovieTopGenres'
]
cross_features = [('movieId', 'clickedMovieIds'),
('topGenre', 'clickedMovieTopGenres')]
dataloader, _ = prepare_dataloader(features)
model = WideDeep(features,
wide_features,
deep_features,
cross_features,
num_classes=2,
embedding_size=4,
hidden_layers=(8, 4),
final_activation='sigmoid',
dropout=0.3)
model(next(iter(dataloader)))