exporter changes

research/object_detection/exporter_lib_v2.py

@@ -39,30 +39,30 @@ def _decode_tf_example(tf_example_string_tensor):
 def _zip_side_inputs(side_input_shapes="",
                      side_input_types="",
                      side_input_names=""):
-    """Zips the side inputs together.
+  """Zips the side inputs together.
 
-    Args:
-      side_input_shapes: forward-slash-separated list of comma-separated lists
-        describing input shapes.
-      side_input_types: comma-separated list of the types of the inputs.
-      side_input_names: comma-separated list of the names of the inputs.
+  Args:
+    side_input_shapes: forward-slash-separated list of comma-separated lists
+      describing input shapes.
+    side_input_types: comma-separated list of the types of the inputs.
+    side_input_names: comma-separated list of the names of the inputs.
 
-    Returns:
-      a zipped list of side input tuples.
-    """
-    side_input_shapes = list(map(lambda x: eval('[' + x + ']'),
-                                 side_input_shapes.split("/")))
-    side_input_types = list(map(eval, side_input_types.split(",")))
-    return zip(side_input_shapes,
-               side_input_types,
-               side_input_names.split(","))
+  Returns:
+    a zipped list of side input tuples.
+  """
+  side_input_shapes = list(map(lambda x: eval('[' + x + ']'),
+                                side_input_shapes.split("/")))
+  side_input_types = list(map(eval, side_input_types.split(",")))
+  return zip(side_input_shapes,
+              side_input_types,
+              side_input_names.split(","))
 
 class DetectionInferenceModule(tf.Module):
   """Detection Inference Module."""
 
   def __init__(self, detection_model,
                use_side_inputs=False,
-               zipped_side_inputs=None:
+               zipped_side_inputs=None):
     """Initializes a module for detection.
 
     Args:
@@ -116,7 +116,7 @@ class DetectionFromImageModule(DetectionInferenceModule):
                                  name=info[2]))
 
     def __call__(input_tensor, *side_inputs):
-      kwargs = dict(zip(self.side_input_names.split(","), side_inputs))
+      kwargs = dict(zip(self.side_input_names, side_inputs))
       return self._run_inference_on_images(input_tensor, **kwargs)
 
     self.__call__ = tf.function(__call__, input_signature=sig)