def testEmptyLeading(self):
export_v2.export_module_from_file(
embedding_file=self._embedding_file_path,
export_path=self.get_temp_dir(),
num_oov_buckets=1,
num_lines_to_ignore=0,
num_lines_to_use=None)
hub_module = hub.load(self.get_temp_dir())
tokens = tf.constant(["", "cat dog"])
embeddings = hub_module(tokens)
self.assertAllClose(
embeddings.numpy(), [[0.0, 0.0, 0.0], [1.49, 3.22, 4.56]], rtol=0.02)
def testNumLinesIgnore(self):
export_v2.export_module_from_file(
embedding_file=self._embedding_file_path,
export_path=self.get_temp_dir(),
num_oov_buckets=1,
num_lines_to_ignore=1,
num_lines_to_use=None)
hub_module = hub.load(self.get_temp_dir())
tokens = tf.constant(["cat", "dog", "mouse"])
embeddings = hub_module(tokens)
self.assertAllClose(embeddings.numpy(),
[[0.0, 0.0, 0.0], [1, 2, 3], [0.5, 0.1, 0.6]],
rtol=0.02)
def testExportTextEmbeddingModule(self):
export_v2.export_module_from_file(
embedding_file=self._embedding_file_path,
export_path=self.get_temp_dir(),
num_oov_buckets=1,
num_lines_to_ignore=0,
num_lines_to_use=None)
hub_module = hub.load(self.get_temp_dir())
tokens = tf.constant(["cat", "cat cat", "lizard. dog", "cat? dog", ""])
embeddings = hub_module(tokens)
self.assertAllClose(
embeddings.numpy(),
[[1.11, 2.56, 3.45], [1.57, 3.62, 4.88], [0.70, 1.41, 2.12],
[1.49, 3.22, 4.56], [0.0, 0.0, 0.0]],
rtol=0.02)
