remove unnecessary update_proto; fix pylint

Author: pengwa

tf2onnx/optimizer/transpose_optimizer.py

@@ -45,8 +45,6 @@ def __init__(self, graph, output_names, debug=False):
         self._handler_map = {}
         self._force_stop = {}
 
-        # make sure all proto of nodes or attribtues are update to date
-        self._g.update_proto()
         self._initialize_handlers()
         self.pre_optimize_action()
 
@@ -74,9 +72,6 @@ def pre_optimize_action(self):
                         if name == output_name:
                             child.input[i] = const_name
             self._g.make_const(const_name, new_data)
-
-            # need call this to make input update synced to protobuf val
-            self._g.update_proto()
             self._g.remove_node(reshape_op.name)
             self._g.topological_sort(self._g.get_nodes())
 
@@ -111,7 +106,6 @@ def post_optimize_action(self):
                                           name=op_name)
                     else:
                         self._remove_useless_tranpose(op)
-        self._g.update_proto()
         self._g.topological_sort(self._g.get_nodes())
 
     def merge_duplicated_transposes(self):

tf2onnx/rewriter/bigru_rewriter.py

@@ -116,7 +116,6 @@ def process_bigru(g, bi_grus):
             raise ValueError(
                 "Reverse is still used by GRU as input, cannot remove")
 
-    g.update_proto()
     return g.get_nodes()
 
 

tf2onnx/rewriter/bilstm_rewriter.py

@@ -101,8 +101,6 @@ def process_bilstm(g, bi_lstms):
         else:
             raise ValueError("Reverse is still used by LSTM as input, cannot remove")
 
-
-    g.update_proto()
     return g.get_nodes()
 
 

tf2onnx/rewriter/custom_rnn_rewriter.py

@@ -190,7 +190,7 @@ def _connect_scan_with_output(self, context, scan_node):
             if out_tensor_value_info.id:
                 if self.g.opset == 8:
                     nodes = self._adapt_scan_sequence_input_or_output("state_output_reshape",
-                                                                        scan_node.output[index], True)
+                                                                      scan_node.output[index], True)
                     self.g.replace_all_inputs(self.g.get_nodes(), out_tensor_value_info.id, nodes[-1].output[0])
                 else:
                     self.g.replace_all_inputs(self.g.get_nodes(), out_tensor_value_info.id, scan_node.output[index])
@@ -200,7 +200,7 @@ def _connect_scan_with_output(self, context, scan_node):
             if out_tensor_value_info.id:
                 if self.g.opset == 8:
                     nodes = self._adapt_scan_sequence_input_or_output("scan_output_reshape",
-                                                                        scan_node.output[index], True)
+                                                                      scan_node.output[index], True)
                     self.g.replace_all_inputs(self.g.get_nodes(), out_tensor_value_info.id, nodes[-1].output[0])
                 else:
                     self.g.replace_all_inputs(self.g.get_nodes(), out_tensor_value_info.id, scan_node.output[index])

tf2onnx/tfonnx.py

@@ -2498,8 +2498,6 @@ def process_tf_graph(tf_graph, continue_on_error=False, verbose=False, target=No
     # onnx requires topological sorting
     topological_sort(g, continue_on_error)
 
-    g.update_proto()
-
     if verbose:
         print("tensorflow ops: {}".format(op_cnt))
         print("tensorflow attr: {}".format(attr_cnt))