fix py3 compatibility issues.

research/object_detection/builders/model_builder_test.py

@@ -331,7 +331,7 @@ class ModelBuilderTest(tf.test.TestCase):
       }"""
     model_proto = model_pb2.DetectionModel()
     text_format.Merge(model_text_proto, model_proto)
-    for extractor_type, extractor_class in FEATURE_EXTRACTOR_MAPS.iteritems():
+    for extractor_type, extractor_class in FEATURE_EXTRACTOR_MAPS.items():
       model_proto.faster_rcnn.feature_extractor.type = extractor_type
       model = model_builder.build(model_proto, is_training=True)
       self.assertIsInstance(model, faster_rcnn_meta_arch.FasterRCNNMetaArch)
@@ -730,7 +730,7 @@ class ModelBuilderTest(tf.test.TestCase):
       }"""
     model_proto = model_pb2.DetectionModel()
     text_format.Merge(model_text_proto, model_proto)
-    for extractor_type, extractor_class in FEATURE_EXTRACTOR_MAPS.iteritems():
+    for extractor_type, extractor_class in FEATURE_EXTRACTOR_MAPS.items():
       model_proto.faster_rcnn.feature_extractor.type = extractor_type
       model = model_builder.build(model_proto, is_training=True)
       self.assertIsInstance(model, rfcn_meta_arch.RFCNMetaArch)

research/object_detection/utils/config_util.py

@@ -195,7 +195,7 @@ def merge_external_params_with_configs(configs, hparams=None, **kwargs):
 
   if hparams:
     kwargs.update(hparams.values())
-  for key, value in kwargs.iteritems():
+  for key, value in kwargs.items():
     if key == "learning_rate":
       _update_initial_learning_rate(configs, value)
       tf.logging.info("Overwriting learning rate: %f", value)