diff --git a/python/src/nnabla/utils/nnp_graph.py b/python/src/nnabla/utils/nnp_graph.py
index 61132e1b7..86ff012ce 100644
--- a/python/src/nnabla/utils/nnp_graph.py
+++ b/python/src/nnabla/utils/nnp_graph.py
@@ -267,40 +267,42 @@ def _get_variable_or_create(self, v, callback, current_scope):
         assert np.all(np.array(shape) >
                       0), "Shape must be positive. Given {}.".format(shape)
 
-        # The variable is a parameter, then get from parameter registry.
-        if pvar.type == 'Parameter':
-            try:
-                param = get_parameter(name)
-                if param is None:
-                    logger.info('Paramter `{}` is not found. Initializing.'.format(
-                        name))
-                    tmp = _create_variable(pvar, name, shape, self.rng)
-                    param = tmp.variable_instance
-                    set_parameter(name, param)
-                # Always copy param to current scope even if it already exists.
-                with nn.parameter_scope('', current_scope):
-                    set_parameter(name, param)
-            except:
-                import sys
-                import traceback
-                raise ValueError(
-                    'An error occurs during creation of a variable `{}` as a'
-                    ' parameter variable. The error was:\n----\n{}\n----\n'
-                    'The parameters registered was {}'.format(
-                        name, traceback.format_exc(),
-                        '\n'.join(
-                            list(nn.get_parameters(grad_only=False).keys()))))
-            assert shape == param.shape
-            param = param.get_unlinked_variable(need_grad=v.need_grad)
-            v.variable = param
-            param.name = name
-            return param
-
-        # Create a new one and returns.
-        var = nn.Variable(shape)
-        v.variable = var
-        var.name = name
-        return var
+        if pvar.type != 'Parameter':
+            # Create a new variable and returns.
+            var = nn.Variable(shape)
+            v.variable = var
+            var.name = name
+            return var
+
+        # Trying to load the parameter from .nnp file.
+        callback.verbose(
+            'Loading parameter `{}` from .nnp.'.format(name))
+        try:
+            param = get_parameter(name)
+            if param is None:
+                logger.info(
+                    'Parameter `{}` is not found. Initializing.'.format(name))
+                tmp = _create_variable(pvar, name, shape, self.rng)
+                param = tmp.variable_instance
+                set_parameter(name, param)
+            # Always copy param to current scope even if it already exists.
+            with nn.parameter_scope('', current_scope):
+                set_parameter(name, param)
+        except:
+            import sys
+            import traceback
+            raise ValueError(
+                'An error occurs during creation of a variable `{}` as a'
+                ' parameter variable. The error was:\n----\n{}\n----\n'
+                'The parameters registered was {}'.format(
+                    name, traceback.format_exc(),
+                    '\n'.join(
+                        list(nn.get_parameters(grad_only=False).keys()))))
+        assert shape == param.shape
+        param = param.get_unlinked_variable(need_grad=v.need_grad)
+        v.variable = param
+        param.name = name
+        return param
 
     def _create_inputs(self, inputs, callback, current_scope):
         input_vars = []