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)