def test_graph_errors():
embeddings = ff_tf.ff_embeddings()
tuebingen_unmasked = ff_tf.ff_lookup(embeddings,
"Tübingen",
mask_empty_string=False,
mask_failed_lookup=False,
embedding_len=100)
ber_bad_shape = ff_tf.ff_lookup(embeddings,
"Berlin",
mask_empty_string=False,
mask_failed_lookup=False,
embedding_len=10)
assert ber_bad_shape.shape == (10, )
empty_unmasked = ff_tf.ff_lookup(embeddings,
"",
mask_empty_string=False,
mask_failed_lookup=False,
embedding_len=100)
with tf.Session() as sess:
with pytest.raises(tf.errors.UnknownError):
sess.run([
ff_tf.initialize_ff_embeddings(embeddings, "foo.fifu", False)
])
sess.run([
ff_tf.initialize_ff_embeddings(embeddings, "testdata/test.fifu",
False)
])
with pytest.raises(tf.errors.AlreadyExistsError):
sess.run([
ff_tf.initialize_ff_embeddings(embeddings,
"testdata/test.fifu", False)
])
with pytest.raises(tf.errors.InvalidArgumentError):
sess.run([tuebingen_unmasked])
with pytest.raises(tf.errors.InvalidArgumentError):
sess.run([empty_unmasked])
with pytest.raises(tf.errors.InvalidArgumentError):
sess.run([ber_bad_shape])
sess.run([ff_tf.close_ff_embeddings(embeddings)])
with pytest.raises(tf.errors.NotFoundError):
sess.run([ff_tf.close_ff_embeddings(embeddings)])
def test_eager_errors():
embeddings = ff_tf.ff_embeddings()
with pytest.raises(tf.errors.UnknownError):
ff_tf.initialize_ff_embeddings(embeddings, "foo.fifu", False)
ff_tf.initialize_ff_embeddings(embeddings, "testdata/test.fifu", False)
with pytest.raises(tf.errors.AlreadyExistsError):
ff_tf.initialize_ff_embeddings(embeddings, "testdata/test.fifu", False)
with pytest.raises(tf.errors.InvalidArgumentError):
ff_tf.ff_lookup(embeddings,
"Tübingen",
mask_empty_string=False,
mask_failed_lookup=False,
embedding_len=100)
# shape mismatch, 10 vs. actual 100
with pytest.raises(tf.errors.InvalidArgumentError):
ff_tf.ff_lookup(embeddings,
"Berlin",
mask_empty_string=False,
mask_failed_lookup=False,
embedding_len=10)
with pytest.raises(tf.errors.InvalidArgumentError):
ff_tf.ff_lookup(embeddings,
"",
mask_empty_string=False,
mask_failed_lookup=False,
embedding_len=100)
ff_tf.close_ff_embeddings(embeddings)
with pytest.raises(tf.errors.NotFoundError):
ff_tf.close_ff_embeddings(embeddings)
def test_eager_lookup_masked():
embeddings = ff_tf.ff_embeddings()
ff_tf.initialize_ff_embeddings(embeddings, "testdata/test.fifu", False)
tuebingen_masked = ff_tf.ff_lookup(embeddings,
"Tübingen",
mask_empty_string=False,
mask_failed_lookup=True,
embedding_len=100)
empty_masked = ff_tf.ff_lookup(embeddings,
"",
mask_empty_string=True,
mask_failed_lookup=False,
embedding_len=100)
empty_masked_through_fail = ff_tf.ff_lookup(embeddings,
"",
mask_empty_string=False,
mask_failed_lookup=True,
embedding_len=100)
assert np.allclose(tuebingen_masked, 0.)
assert np.allclose(empty_masked, 0.)
assert np.allclose(empty_masked_through_fail, 0.)
ff_tf.close_ff_embeddings(embeddings)
def test_eager_lookup():
embeddings = ff_tf.ff_embeddings()
ff_tf.initialize_ff_embeddings(embeddings,
"testdata/test.fifu",
mmap=False)
ber = ff_tf.ff_lookup(embeddings,
"Berlin",
mask_empty_string=False,
mask_failed_lookup=False)
ber_list = ff_tf.ff_lookup(embeddings, ["Berlin"],
mask_empty_string=False,
mask_failed_lookup=False)
ber_tensor = ff_tf.ff_lookup(embeddings, [["Berlin"]],
mask_empty_string=False,
mask_failed_lookup=False)
assert ber.shape == (100, )
assert ber_list.shape == (1, 100)
assert ber_tensor.shape == (1, 1, 100)
ff_tf.close_ff_embeddings(embeddings)
def test_graph_lookup():
embeddings = ff_tf.ff_embeddings()
init = ff_tf.initialize_ff_embeddings(embeddings, "testdata/test.fifu",
False)
ber = ff_tf.ff_lookup(embeddings,
"Berlin",
mask_empty_string=False,
mask_failed_lookup=False,
embedding_len=100)
assert ber.shape == (100, )
ber_list = ff_tf.ff_lookup(embeddings, ["Berlin"],
mask_empty_string=False,
mask_failed_lookup=False,
embedding_len=100)
assert ber_list.shape == (1, 100)
ber_tensor = ff_tf.ff_lookup(embeddings, [["Berlin"]],
mask_empty_string=False,
mask_failed_lookup=False,
embedding_len=100)
assert ber_tensor.shape == (1, 1, 100)
ber_no_shape = ff_tf.ff_lookup(embeddings,
"Berlin",
mask_empty_string=False,
mask_failed_lookup=False)
assert ber_no_shape.shape.rank == 1
assert ber_no_shape.shape[0].value is None
ber_list_no_shape = ff_tf.ff_lookup(embeddings, ["Berlin"],
mask_empty_string=False,
mask_failed_lookup=False)
assert ber_list_no_shape.shape.rank == 2
assert ber_list_no_shape.shape[0].value == tf.Dimension(1)
assert ber_list_no_shape.shape[1].value is None
with tf.Session() as sess:
sess.run([init])
res = sess.run([ber, ber_list, ber_tensor])
assert res[0].shape == (100, )
assert res[1].shape == (1, 100)
assert res[2].shape == (1, 1, 100)
sess.run([ff_tf.close_ff_embeddings(embeddings)])
def test_graph_lookup_masked():
embeddings = ff_tf.ff_embeddings()
init = ff_tf.initialize_ff_embeddings(embeddings, "testdata/test.fifu",
True)
tuebingen_masked = ff_tf.ff_lookup(embeddings,
"Tübingen",
mask_empty_string=False,
mask_failed_lookup=True,
embedding_len=100)
empty_masked = ff_tf.ff_lookup(embeddings,
"",
mask_empty_string=True,
mask_failed_lookup=False,
embedding_len=100)
empty_masked_through_fail = ff_tf.ff_lookup(embeddings,
"",
mask_empty_string=False,
mask_failed_lookup=True,
embedding_len=100)
with tf.Session() as sess:
sess.run([init])
res = sess.run(
[tuebingen_masked, empty_masked, empty_masked_through_fail])
assert np.allclose(res, 0.)
def test_init_and_close():
embeddings = ff_tf.ff_embeddings()
ff_tf.initialize_ff_embeddings(embeddings,
"testdata/test.fifu",
mmap=False)
ff_tf.close_ff_embeddings(embeddings)