params group (#4955)

configs/faster_rcnn/_base_/optimizer_swin_1x.yml

@@ -15,4 +15,8 @@ OptimizerBuilder:
   optimizer:
     type: AdamW
     weight_decay: 0.05
-    without_weight_decay_params: ['absolute_pos_embed', 'relative_position_bias_table', 'norm']
+
+    param_groups:
+        -
+          params: ['absolute_pos_embed', 'relative_position_bias_table', 'norm']
+          weight_decay: 0.

ppdet/optimizer.py

@@ -249,21 +249,37 @@ class OptimizerBuilder():
             optim_args['weight_decay'] = regularization
         op = getattr(optimizer, optim_type)
 
-        if 'without_weight_decay_params' in optim_args:
-            keys = optim_args['without_weight_decay_params']
-            params = [{
-                'params': [
-                    p for n, p in model.named_parameters()
-                    if any([k in n for k in keys])
-                ],
-                'weight_decay': 0.
-            }, {
-                'params': [
-                    p for n, p in model.named_parameters()
-                    if all([k not in n for k in keys])
-                ]
-            }]
-            del optim_args['without_weight_decay_params']
+        if 'param_groups' in optim_args:
+            assert isinstance(optim_args['param_groups'], list), ''
+
+            param_groups = optim_args.pop('param_groups')
+
+            params, visited = [], []
+            for group in param_groups:
+                assert isinstance(group,
+                                  dict) and 'params' in group and isinstance(
+                                      group['params'], list), ''
+                _params = {
+                    n: p
+                    for n, p in model.named_parameters()
+                    if any([k in n for k in group['params']])
+                }
+                _group = group.copy()
+                _group.update({'params': list(_params.values())})
+
+                params.append(_group)
+                visited.extend(list(_params.keys()))
+
+            ext_params = [
+                p for n, p in model.named_parameters() if n not in visited
+            ]
+
+            if len(ext_params) < len(model.parameters()):
+                params.append({'params': ext_params})
+
+            elif len(ext_params) > len(model.parameters()):
+                raise RuntimeError
+
         else:
             params = model.parameters()