Merge pull request #2340 from emailweixu/boot_bias_layer

Fix handling of boot_bias_parameter for recurrent_group in v2 API
PaddlePaddle · Jun 1, 2017 · 303d266 · 303d266
2 parents c562e57 + 02a509f
commit 303d266
Showing 1 changed file with 14 additions and 6 deletions.
diff --git a/python/paddle/v2/layer.py b/python/paddle/v2/layer.py
@@ -152,7 +152,7 @@ def dfs_travel(layer_name):
     return layer_names
 
 
-def __get_used_parameters__(layer_names):
+def __get_used_parameters__(layer_names, sub_models):
     parameter_names = set()
     for name in layer_names:
         l = cp.g_layer_map[name]
@@ -161,6 +161,12 @@ def __get_used_parameters__(layer_names):
                 parameter_names.add(inp.input_parameter_name)
         if l.bias_parameter_name:
             parameter_names.add(l.bias_parameter_name)
+
+    for sub_model in sub_models:
+        for mem in sub_model.memories:
+            if mem.HasField("boot_bias_parameter_name"):
+                parameter_names.add(mem.boot_bias_parameter_name)
+
     return parameter_names
 
 
@@ -236,7 +242,6 @@ def parse_network(output_layers, extra_layers=None):
     layer_names = __get_used_layers__(output_layers + extra_layers)
     submodel_names = __get_used_submodels__(layer_names)
     submodel_names.add('root')
-    parameter_names = __get_used_parameters__(layer_names)
     evaluator_names = __get_used_evaluators__(layer_names)
     input_layer_names = set()
     output_layer_names = set()
@@ -251,10 +256,6 @@ def parse_network(output_layers, extra_layers=None):
             model_config.input_layer_names.append(l.name)
             input_layer_names.add(l.name)
 
-    for p in cp.g_config.model_config.parameters:
-        if p.name in parameter_names:
-            model_config.parameters.extend([p])
-
     for layer in output_layers:
         model_config.output_layer_names.append(layer.full_name)
         output_layer_names.add(layer.full_name)
@@ -269,6 +270,13 @@ def parse_network(output_layers, extra_layers=None):
                                   output_layer_names, evaluator_names)
             model_config.sub_models.extend([s])
 
+    parameter_names = __get_used_parameters__(layer_names,
+                                              model_config.sub_models)
+
+    for p in cp.g_config.model_config.parameters:
+        if p.name in parameter_names:
+            model_config.parameters.extend([p])
+
     return model_config