follow comments on config_parser

proto/ModelConfig.proto.m4

@@ -78,10 +78,10 @@ message ConvConfig {
   required uint32 stride_y = 12;
 
   // if not set, use output_x
-  optional uint32 output_y = 13 [default = 0];
+  optional uint32 output_y = 13;
 
   // if not set, use img_size
-  optional uint32 img_size_y = 14 [default = 0];
+  optional uint32 img_size_y = 14;
 }
 
 message PoolConfig {
@@ -161,10 +161,10 @@ message NormConfig {
   optional bool blocked = 8;
 
   // if not set, use output_x
-  optional uint32 output_y = 9 [default = 0];
+  optional uint32 output_y = 9;
 
   // if not set, use img_size
-  optional uint32 img_size_y = 10 [default = 0];
+  optional uint32 img_size_y = 10;
 }
 
 message BlockExpandConfig {

python/paddle/trainer/config_parser.py

@@ -1066,7 +1066,7 @@ def cnn_output_size(img_size, filter_size, padding, stride, caffe_mode):
         return 1 + int(math.ceil(output))
 
 
-#calcualte image_size based on output_size for convolution. 
+#calcualte image_size based on output_size for de-convolution (ConvTransLayer). 
 #It is the reverse function of cnn_output_size
 def cnn_image_size(output_size, filter_size, padding, stride, caffe_mode):
     img_size = (output_size - 1) * stride + filter_size - 2 * padding
@@ -1075,7 +1075,7 @@ def cnn_image_size(output_size, filter_size, padding, stride, caffe_mode):
     return img_size
 
 
-def set_img_size(input_layer_name, channels):
+def get_img_size(input_layer_name, channels):
     input = g_layer_map[input_layer_name]
     img_pixels = input.size / channels
     img_size = input.width if input.width > 0 else int(img_pixels**0.5)
@@ -1110,7 +1110,7 @@ def parse_pool(pool, input_layer_name, pool_conf):
     pool_conf.stride_y = default(pool.stride_y, pool_conf.stride)
 
     pool_conf.img_size, pool_conf.img_size_y = \
-        set_img_size(input_layer_name, pool.channels)
+        get_img_size(input_layer_name, pool.channels)
 
     config_assert(not pool.start, "start is deprecated in pooling.")
 
@@ -1137,7 +1137,7 @@ def parse_spp(spp, input_layer_name, spp_conf):
 def parse_image(image, input_layer_name, image_conf):
     image_conf.channels = image.channels
     image_conf.img_size, image_conf.img_size_y = \
-        set_img_size(input_layer_name, image_conf.channels)
+        get_img_size(input_layer_name, image_conf.channels)
 
 
 def parse_norm(norm, input_layer_name, norm_conf):
@@ -1152,7 +1152,7 @@ def parse_norm(norm, input_layer_name, norm_conf):
     norm_conf.blocked = norm.blocked
 
     norm_conf.img_size, norm_conf.img_size_y = \
-        set_img_size(input_layer_name, norm.channels)
+        get_img_size(input_layer_name, norm.channels)
     norm_conf.output_x = norm_conf.img_size
     norm_conf.output_y = norm_conf.img_size_y
     if norm.norm_type in ['cmrnorm-projection']:
@@ -1177,7 +1177,7 @@ def parse_conv(conv, input_layer_name, conv_conf, num_filters, trans=False):
     if not trans:
         conv_conf.filter_channels = conv.channels / conv.groups
         conv_conf.img_size, conv_conf.img_size_y = \
-            set_img_size(input_layer_name, conv.channels)
+            get_img_size(input_layer_name, conv.channels)
         conv_conf.output_x = cnn_output_size(
             conv_conf.img_size, conv_conf.filter_size, conv_conf.padding,
             conv_conf.stride, conv_conf.caffe_mode)
@@ -1187,11 +1187,11 @@ def parse_conv(conv, input_layer_name, conv_conf, num_filters, trans=False):
     else:
         conv_conf.filter_channels = num_filters / conv.groups
         conv_conf.output_x, conv_conf.output_y = \
-            set_img_size(input_layer_name, conv.channels)
+            get_img_size(input_layer_name, conv.channels)
         conv_conf.img_size = cnn_image_size(
             conv_conf.output_x, conv_conf.filter_size, conv_conf.padding,
             conv_conf.stride, conv_conf.caffe_mode)
-        conv_conf.img_size_y = cnn_output_size(
+        conv_conf.img_size_y = cnn_image_size(
             conv_conf.output_y, conv_conf.filter_size_y, conv_conf.padding_y,
             conv_conf.stride_y, conv_conf.caffe_mode)
 

python/paddle/trainer_config_helpers/tests/configs/protostr/img_trans_layers.protostr

@@ -27,7 +27,7 @@ layers {
       padding_y: 1
       stride_y: 1
       output_y: 227
-      img_size_y: 198
+      img_size_y: 256
     }
   }
   bias_parameter_name: "___conv_0__.wbias"