add config_parser in trainer_config_helpers to seperate trainer config

demo/mnist/api_train.py

@@ -19,10 +19,9 @@ def init_parameter(network):
     assert isinstance(network, api.GradientMachine)
     for each_param in network.getParameters():
         assert isinstance(each_param, api.Parameter)
-        array = each_param.getBuf(api.PARAMETER_VALUE).toNumpyArrayInplace()
-        assert isinstance(array, np.ndarray)
-        for i in xrange(len(array)):
-            array[i] = np.random.uniform(-1.0, 1.0)
+        array_size = len(each_param)
+        array = np.random.uniform(-1.0, 1.0, array_size).astype('float32')
+        each_param.getBuf(api.PARAMETER_VALUE).copyFromNumpyArray(array)
 
 
 def generator_to_batch(generator, batch_size):
@@ -175,7 +174,7 @@ def updater_callback(param):
         for each_param in params:
             assert isinstance(each_param, api.Parameter)
             value = each_param.getBuf(api.PARAMETER_VALUE)
-            value = value.toNumpyArrayInplace()
+            value = value.copyToNumpyArray()
 
             # Here, we could save parameter to every where you want
             print each_param.getName(), value

paddle/api/Paddle.swig

@@ -96,6 +96,7 @@ namespace std {
 %rename(__getitem__) Vector::get;
 %rename(__setitem__) Vector::set;
 %rename(__len__) Vector::getSize;
+%rename(__len__) Parameter::getSize;
 %rename(__call__) ParameterTraverseCallback::apply;
 %rename(__repr__) Evaluator::toString;
 

paddle/api/PaddleAPI.h

@@ -550,6 +550,8 @@ class Parameter {
   ParameterConfig* getConfig();
   void setValueUpdated();
 
+  size_t getSize() const;
+
 private:
   static Parameter* createFromRawPtr(void* ptr);
   static Parameter* createFromSharedPtr(void* ptr);

paddle/api/Parameter.cpp

@@ -56,3 +56,5 @@ ParameterConfig* Parameter::getConfig() {
 size_t Parameter::getID() const { return m->getPtr()->getID(); }
 
 void Parameter::setValueUpdated() { m->getPtr()->setValueUpdated(); }
+
+size_t Parameter::getSize() const { return m->getPtr()->getSize(); }