refine log message

Author: nbcsm

tf2onnx/convert.py

@@ -128,13 +128,17 @@ def main():
 
     model_proto = g.make_model("converted from {}".format(model_path))
 
-    logger.info("\n")
+    logger.info("")
     model_proto = GraphUtil.optimize_model_proto(model_proto)
 
     # write onnx graph
+    logger.info("")
+    logger.info("Successfully converted TensorFlow model %s to ONNX", model_path)
     if args.output:
         utils.save_protobuf(args.output, model_proto)
-        print("\nComplete successfully, the onnx model is generated at " + args.output)
+        logger.info("ONNX model is saved at %s", args.output)
+    else:
+        logger.info("To export ONNX model to file, please run with `--output` option")
 
 
 if __name__ == "__main__":

tf2onnx/graph.py

@@ -21,7 +21,6 @@
 from tf2onnx import optimizer
 from tf2onnx.schemas import get_schema
 
-
 logger = logging.getLogger(__name__)
 
 
@@ -1037,18 +1036,19 @@ def extract_sub_graph_nodes(self, outputs_name, input_checker=None, ignore_unuse
 
     def delete_unused_nodes(self, outputs_name):
         """Delete nodes not in subgraph ending with output_names."""
-        if outputs_name:
-            # we need keep those placeholders that are used as input of Loop's body graph.
-            # some of them are not used in the graph, but still need be there to keep the graph complete.
-            related_nodes = self.extract_sub_graph_nodes(outputs_name, ignore_unused_placeholder=False)
-            for node in related_nodes:
-                attr_body_graphs = node.get_body_graphs()
-                if attr_body_graphs:
-                    for _, body_graph in attr_body_graphs.items():
-                        body_graph.delete_unused_nodes(body_graph.outputs)
-            self.reset_nodes(related_nodes)
-        else:
-            print("WARNING: outputs not specified, delete_unused_nodes not taking effect.")
+        if not outputs_name:
+            logger.debug("Outputs not specified, delete_unused_nodes not taking effect.")
+            return
+
+        # we need keep those placeholders that are used as input of Loop's body graph.
+        # some of them are not used in the graph, but still need be there to keep the graph complete.
+        related_nodes = self.extract_sub_graph_nodes(outputs_name, ignore_unused_placeholder=False)
+        for node in related_nodes:
+            attr_body_graphs = node.get_body_graphs()
+            if attr_body_graphs:
+                for _, body_graph in attr_body_graphs.items():
+                    body_graph.delete_unused_nodes(body_graph.outputs)
+        self.reset_nodes(related_nodes)
 
 
 class GraphUtil(object):

tf2onnx/tfonnx.py

@@ -686,13 +686,13 @@ def process_tf_graph(tf_graph, continue_on_error=False, verbose=False, target=No
         logger.warning("Argument verbose for process_tf_graph is deprecated. Please use --verbose option instead.")
     del verbose
 
-    opset = utils.find_opset(opset)
-    print("using tensorflow={}, onnx={}, opset={}, tfonnx={}/{}".format(
-        tf.__version__, utils.get_onnx_version(), opset,
-        tf2onnx.__version__, tf2onnx.version.git_version[:6]))
+    logger.info("Using tensorflow=%s, onnx=%s, tf2onnx=%s/%s",
+                tf.__version__, utils.get_onnx_version(), tf2onnx.__version__, tf2onnx.version.git_version[:6])
 
+    opset = utils.find_opset(opset)
+    logger.info("Using opset <onnx, %s>", opset)
     if opset > schemas.get_max_supported_opset_version():
-        logger.warning("currently installed onnx package %s is too low to support opset %s, "
+        logger.warning("Currently installed onnx package %s is too low to support opset %s, "
                        "please upgrade onnx package to avoid potential conversion issue.",
                        utils.get_onnx_version(), opset)