test=develop, use parameters() to get parameters

python/paddle/fluid/imperative/nn.py

@@ -483,6 +483,9 @@ class Embedding(layers.Layer):
             dtype=self._dtype,
             is_bias=False)
 
+    def parameters(self):
+        return [self._w]
+
     def forward(self, input):
         out = self._helper.create_variable_for_type_inference(self._dtype)
         self._helper.append_op(

python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py

@@ -75,6 +75,16 @@ class SimpleLSTMRNN(fluid.imperative.Layer):
             self.hidden_array.append(pre_hidden)
             self.cell_array.append(pre_cell)
 
+    def parameters(self):
+        parameters = list()
+        for param in self.weight_1_arr:
+            parameters.append(param)
+        for param in self.weight_2_arr:
+            parameters.append(param)
+        for bias in self.bias_arr:
+            parameters.append(bias)
+        return parameters
+
     def forward(self, input_embedding, init_hidden=None, init_cell=None):
         res = []
         for index in range(self._num_steps):
@@ -167,6 +177,12 @@ class PtbModel(fluid.imperative.Layer):
     def _build_once(self, input, label, init_hidden, init_cell):
         pass
 
+    def parameters(self):
+        parameters = self.simple_lstm_rnn.parameters() + [
+            self.softmax_weight, self.softmax_bias
+        ] + self.embedding.parameters()
+        return parameters
+
     def forward(self, input, label, init_hidden, init_cell):
 
         init_h = fluid.layers.reshape(
@@ -246,13 +262,11 @@ class TestImperativePtbRnn(unittest.TestCase):
                 dy_loss, last_hidden, last_cell = ptb_model(x, y, init_hidden,
                                                             init_cell)
                 if i == 0:
-                    for param in fluid.default_main_program().global_block(
-                    ).all_parameters():
+                    for param in ptb_model.parameters():
                         dy_param_init[param.name] = param._numpy()
                 dy_loss._backward()
                 sgd.minimize(dy_loss)
-                for param in fluid.default_main_program().global_block(
-                ).all_parameters():
+                for param in ptb_model.parameters():
                     dy_param_updated[param.name] = param._numpy()
                 # print("dy_loss is {}".format(dy_loss._numpy()))
                 # print("last_hidden is {}".format(last_hidden._numpy()))
@@ -284,8 +298,7 @@ class TestImperativePtbRnn(unittest.TestCase):
             static_param_updated = dict()
             static_param_init = dict()
             static_param_name_list = list()
-            for param in fluid.default_startup_program().global_block(
-            ).all_parameters():
+            for param in ptb_model.parameters():
                 static_param_name_list.append(param.name)
 
             out = exe.run(framework.default_startup_program(),