def test_create_visualization_matrix(monkeypatch, tmpdir):
pipeline_config = {
"maxqlen": 5,
"passagelen": 3,
"slicelen": 20,
"tfchannel": True
}
extractor = DeepTileExtractor(tmpdir, tmpdir, pipeline_config)
extractor.stoi = {
"<pad>": 0,
"hello": 1,
"world": 2,
"foo": 3,
"bar": 4,
"alice": 5,
"bob": 6
}
extractor.idf = defaultdict(lambda: 0)
def fake_magnitude_embedding(*args, **kwargs):
return Magnitude(None)
monkeypatch.setattr(extractor, "get_magnitude_embeddings",
fake_magnitude_embedding)
embeddings_matrix = extractor.create_embedding_matrix("glove6b.50d")
level = extractor.create_visualization_matrix(
[
"hello", extractor.pad_tok, extractor.pad_tok, extractor.pad_tok,
extractor.pad_tok
],
["hello world", "foo bar", "alice bob"],
embeddings_matrix,
)
assert level.shape == (1, 5, 3, 3)
def test_deeptiles_create_visualization_matrix(monkeypatch, tmpdir,
dummy_index):
def fake_magnitude_embedding(*args, **kwargs):
return Magnitude(None)
monkeypatch.setattr(DeepTileExtractor, "_get_pretrained_emb",
fake_magnitude_embedding)
benchmark = DummyBenchmark()
pipeline_config = {
"name": "deeptiles",
"tilechannels": 3,
"maxqlen": 5,
"passagelen": 3,
"slicelen": 20,
"tfchannel": True
}
extractor = DeepTileExtractor(pipeline_config,
provide={
"index": dummy_index,
"benchmark": benchmark
})
extractor.stoi = {
"<pad>": 0,
"hello": 1,
"world": 2,
"foo": 3,
"bar": 4,
"alice": 5,
"bob": 6
}
extractor.idf = defaultdict(lambda: 0)
extractor._build_embedding_matrix()
embeddings_matrix = extractor.embeddings
level = extractor.create_visualization_matrix(
[
"hello", extractor.pad_tok, extractor.pad_tok, extractor.pad_tok,
extractor.pad_tok
],
["hello world", "foo bar", "alice bob"],
embeddings_matrix,
)
assert level.shape == (1, 5, 3, 3)