Internal change

PiperOrigin-RevId: 417875109

Author: frederick0329

official/core/train_utils_test.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Tests for official.core.train_utils."""
+import json
 import os
 import pprint
 
@@ -138,5 +139,60 @@ def test_construct_experiment_from_flags(self):
     self.assertEqual(params_from_obj.trainer.validation_steps, 11)
 
 
+class BestCheckpointExporterTest(tf.test.TestCase):
+
+  def test_maybe_export(self):
+    model_dir = self.create_tempdir().full_path
+    best_ckpt_path = os.path.join(model_dir, 'best_ckpt-1')
+    metric_name = 'test_metric|metric_1'
+    exporter = train_utils.BestCheckpointExporter(
+        model_dir, metric_name, 'higher')
+    v = tf.Variable(1.0)
+    checkpoint = tf.train.Checkpoint(v=v)
+    ret = exporter.maybe_export_checkpoint(
+        checkpoint, {'test_metric': {'metric_1': 5.0}}, 100)
+    with self.subTest(name='Successful first save.'):
+      self.assertEqual(ret, True)
+      v_2 = tf.Variable(2.0)
+      checkpoint_2 = tf.train.Checkpoint(v=v_2)
+      checkpoint_2.restore(best_ckpt_path)
+      self.assertEqual(v_2.numpy(), 1.0)
+
+    v = tf.Variable(3.0)
+    checkpoint = tf.train.Checkpoint(v=v)
+    ret = exporter.maybe_export_checkpoint(
+        checkpoint, {'test_metric': {'metric_1': 6.0}}, 200)
+    with self.subTest(name='Successful better metic save.'):
+      self.assertEqual(ret, True)
+      v_2 = tf.Variable(2.0)
+      checkpoint_2 = tf.train.Checkpoint(v=v_2)
+      checkpoint_2.restore(best_ckpt_path)
+      self.assertEqual(v_2.numpy(), 3.0)
+
+    v = tf.Variable(5.0)
+    checkpoint = tf.train.Checkpoint(v=v)
+    ret = exporter.maybe_export_checkpoint(
+        checkpoint, {'test_metric': {'metric_1': 1.0}}, 300)
+    with self.subTest(name='Worse metic no save.'):
+      self.assertEqual(ret, False)
+      v_2 = tf.Variable(2.0)
+      checkpoint_2 = tf.train.Checkpoint(v=v_2)
+      checkpoint_2.restore(best_ckpt_path)
+      self.assertEqual(v_2.numpy(), 3.0)
+
+  def test_export_best_eval_metric(self):
+    model_dir = self.create_tempdir().full_path
+    metric_name = 'test_metric|metric_1'
+    exporter = train_utils.BestCheckpointExporter(model_dir, metric_name,
+                                                  'higher')
+    exporter.export_best_eval_metric({'test_metric': {'metric_1': 5.0}}, 100)
+    with tf.io.gfile.GFile(os.path.join(model_dir, 'info.json'),
+                           'rb') as reader:
+      metric = json.loads(reader.read())
+      self.assertAllEqual(
+          metric,
+          {'test_metric': {'metric_1': 5.0}, 'best_ckpt_global_step': 100.0})
+
+
 if __name__ == '__main__':
   tf.test.main()