def test_scattered_embedding_coverage(self):
with self.test_session():
size = 8
embedding_weights = self._random_weights(size=size, num_shards=3)
values = constant_op.constant(["foo"])
# Large embedding dimension to cover the full range of weights.
embedding_lookup_result = embedding_ops.scattered_embedding_lookup(
embedding_weights, values, dimension=100).eval()
self.assertEqual(len(np.unique(embedding_lookup_result[0])), size)
def test_scattered_embedding_consistency(self):
with self.test_session():
embedding_weights = self._random_weights()
values = constant_op.constant(["foo", "foo"])
embedding_lookup_result = embedding_ops.scattered_embedding_lookup(
embedding_weights, values, dimension=10).eval()
self.assertAllEqual(embedding_lookup_result.shape, [2, 10])
self.assertAllEqual(embedding_lookup_result[0],
embedding_lookup_result[1])
def test_scattered_embedding_coverage(self):
with self.cached_session():
size = 8
embedding_weights = self._random_weights(size=size, num_shards=3)
values = constant_op.constant(["foo"])
# Large embedding dimension to cover the full range of weights.
embedding_lookup_result = embedding_ops.scattered_embedding_lookup(
embedding_weights, values, dimension=100).eval()
self.assertEqual(len(np.unique(embedding_lookup_result[0])), size)
def test_scattered_embedding_consistency(self):
with self.cached_session():
embedding_weights = self._random_weights()
values = constant_op.constant(["foo", "foo"])
embedding_lookup_result = embedding_ops.scattered_embedding_lookup(
embedding_weights, values, dimension=10).eval()
self.assertAllEqual(embedding_lookup_result.shape, [2, 10])
self.assertAllEqual(embedding_lookup_result[0],
embedding_lookup_result[1])
def test_scattered_embedding_multi_dimension(self):
with self.cached_session(), local_variable_scope():
embedding_weights = self._random_weights()
values = constant_op.constant([["foo", "bar", "bar"],
["bar", "bar", "foo"]])
embedding_lookup_result = embedding_ops.scattered_embedding_lookup(
embedding_weights, values, dimension=10).eval()
self.assertAllEqual(embedding_lookup_result.shape, [2, 3, 10])
self.assertAllEqual(embedding_lookup_result[0][0],
embedding_lookup_result[1][2])
def test_scattered_embedding_multi_dimension(self):
with self.cached_session(), local_variable_scope():
embedding_weights = self._random_weights()
values = constant_op.constant([["foo", "bar", "bar"],
["bar", "bar", "foo"]])
embedding_lookup_result = embedding_ops.scattered_embedding_lookup(
embedding_weights, values, dimension=10).eval()
self.assertAllEqual(embedding_lookup_result.shape, [2, 3, 10])
self.assertAllEqual(embedding_lookup_result[0][0],
embedding_lookup_result[1][2])
def test_scattered_embedding_multiple_partition(self):
with self.test_session():
embedding_weights = self._random_weights(num_shards=7)
values = constant_op.constant([4, 4, 5])
embedding_lookup_result = embedding_ops.scattered_embedding_lookup(
embedding_weights, values, dimension=5).eval()
self.assertAllEqual(embedding_lookup_result.shape, [3, 5])
self.assertAllEqual(embedding_lookup_result[0],
embedding_lookup_result[1])
# Different embedding expected for different value.
embedding_diff = np.min(
(embedding_lookup_result[2] - embedding_lookup_result[0])**2)
self.assertGreater(embedding_diff, 0)
def test_scattered_embedding_multiple_partition(self):
with self.cached_session():
embedding_weights = self._random_weights(num_shards=7)
values = constant_op.constant([4, 4, 5])
embedding_lookup_result = embedding_ops.scattered_embedding_lookup(
embedding_weights, values, dimension=5).eval()
self.assertAllEqual(embedding_lookup_result.shape, [3, 5])
self.assertAllEqual(embedding_lookup_result[0],
embedding_lookup_result[1])
# Different embedding expected for different value.
embedding_diff = np.min(
(embedding_lookup_result[2] - embedding_lookup_result[0])**2)
self.assertGreater(embedding_diff, 0)
