add more distillation models

ppcls/modeling/architectures/distillation_models.py

@@ -42,20 +42,25 @@ class ResNet50_vd_distill_MobileNetV3_large_x1_0(fluid.dygraph.Layer):
 
     def forward(self, input):
         teacher_label = self.teacher(input)
+        teacher_label.stop_gradient = True
 
         student_label = self.student(input)
 
         return teacher_label, student_label
 
 
-class ResNeXt101_32x16d_wsl_distill_ResNet50_vd():
-    def net(self, input, class_dim=1000):
-        # student
-        student = ResNet50_vd()
-        out_student = student.net(input, class_dim=class_dim)
-        # teacher
-        teacher = ResNeXt101_32x16d_wsl()
-        out_teacher = teacher.net(input, class_dim=class_dim)
-        out_teacher.stop_gradient = True
+class ResNeXt101_32x16d_wsl_distill_ResNet50_vd(fluid.dygraph.Layer):
+    def __init__(self, class_dim=1000, **args):
+        super(ResNet50_vd_distill_MobileNetV3_large_x1_0, self).__init__()
 
-        return out_teacher, out_student
+        self.teacher = ResNeXt101_32x16d_wsl(class_dim=class_dim, **args)
+
+        self.student = ResNet50_vd(class_dim=class_dim, **args)
+
+    def forward(self, input):
+        teacher_label = self.teacher(input)
+        teacher_label.stop_gradient = True
+
+        student_label = self.student(input)
+
+        return teacher_label, student_label

ppcls/utils/save_load.py

@@ -58,7 +58,6 @@ def load_dygraph_pretrain(
         model_dict = model.state_dict()
         for key in model_dict.keys():
             weight_name = model_dict[key].name
-            print("dyg key: {}, weight_name: {}".format(key, weight_name))
             if weight_name in pre_state_dict.keys():
                 print('Load weight: {}, shape: {}'.format(
                     weight_name, pre_state_dict[weight_name].shape))