Prediction: variable name changes.

modules/tools/prediction/mlp_train/cruiseMLP_train.py

@@ -26,8 +26,8 @@ import argparse
 
 import proto.cruise_model_pb2
 from proto.cruise_model_pb2 import TensorParameter, InputParameter,\
-    Conv1dParameter, DenseParameter, ActivationParameter, MaxPool1d,\
-    AvgPool1d, LaneFeatureConv, ObsFeatureFC, Classify, Regress,\
+    Conv1dParameter, DenseParameter, ActivationParameter, MaxPool1dParameter,\
+    AvgPool1dParameter, LaneFeatureConv, ObsFeatureFC, Classify, Regress,\
     CruiseModel
 
 import torch
@@ -244,11 +244,11 @@ def save_FCNN_CNN1D(model, filename):
     lane_feature_conv.activation_3.activation = 'relu'
     lane_feature_conv.conv1d_4.CopyFrom(load_Conv1dParameter(model, 'lane_feature_conv.4', stride=2))
 
-    lane_feature_maxpool = MaxPool1d()
+    lane_feature_maxpool = MaxPool1dParameter()
     lane_feature_maxpool.kernel_size = 3
     lane_feature_maxpool.stride = 3
 
-    lane_feature_avgpool = AvgPool1d()
+    lane_feature_avgpool = AvgPool1dParameter()
     lane_feature_avgpool.kernel_size = 3
     lane_feature_avgpool.stride = 3
 

modules/tools/prediction/mlp_train/proto/cruise_model.proto

@@ -37,12 +37,12 @@ message ActivationParameter {
   optional string activation = 1;
 }
 
-message MaxPool1d {
+message MaxPool1dParameter {
   optional int32 kernel_size = 1;
   optional int32 stride = 2;
 }
 
-message AvgPool1d {
+message AvgPool1dParameter {
   optional int32 kernel_size = 1;
   optional int32 stride = 2;
 }
@@ -93,8 +93,8 @@ message Regress {
 // next id = 
 message CruiseModel {
   optional LaneFeatureConv lane_feature_conv = 1;
-  optional MaxPool1d lane_feature_maxpool = 2;
-  optional AvgPool1d lane_feature_avgpool = 3;
+  optional MaxPool1dParameter lane_feature_maxpool = 2;
+  optional AvgPool1dParameter lane_feature_avgpool = 3;
   optional ObsFeatureFC obs_feature_fc = 5;
   optional Classify classify = 6;
   optional Regress regress = 7;