remove load_static_weights & polish ppdet.engine log (#2366)

* remove load_static_weights

dygraph/configs/cascade_rcnn/_base_/cascade_mask_rcnn_r50_fpn.yml

 architecture: CascadeRCNN
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
 
 
 CascadeRCNN:

dygraph/configs/cascade_rcnn/_base_/cascade_rcnn_r50_fpn.yml

 architecture: CascadeRCNN
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
 
 
 CascadeRCNN:

dygraph/configs/faster_rcnn/_base_/faster_rcnn_r50.yml

 architecture: FasterRCNN
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
 
 FasterRCNN:
   backbone: ResNet

dygraph/configs/faster_rcnn/_base_/faster_rcnn_r50_fpn.yml

 architecture: FasterRCNN
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
 
 FasterRCNN:
   backbone: ResNet

dygraph/configs/fcos/_base_/fcos_r50_fpn.yml

 architecture: FCOS
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
 
 FCOS:
   backbone: ResNet

dygraph/configs/hrnet/_base_/faster_rcnn_hrnetv2p_w18.yml

 architecture: FasterRCNN
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/HRNet_W18_C_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/HRNet_W18_C_pretrained.pdparams
 
 FasterRCNN:
   backbone: HRNet

dygraph/configs/mask_rcnn/_base_/mask_rcnn_r50.yml

 architecture: MaskRCNN
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
 
 MaskRCNN:
   backbone: ResNet

dygraph/configs/mask_rcnn/_base_/mask_rcnn_r50_fpn.yml

 architecture: MaskRCNN
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
 
 MaskRCNN:
   backbone: ResNet

dygraph/configs/ppyolo/_base_/ppyolo_mbv3_large.yml

 architecture: YOLOv3
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV3_large_x1_0_ssld_pretrained.tar
-load_static_weights: true
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams
 norm_type: sync_bn
 use_ema: true
 ema_decay: 0.9998

dygraph/configs/ppyolo/_base_/ppyolo_mbv3_small.yml

 architecture: YOLOv3
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV3_small_x1_0_ssld_pretrained.tar
-load_static_weights: true
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_small_x1_0_ssld_pretrained.pdparams
 norm_type: sync_bn
 use_ema: true
 ema_decay: 0.9998

dygraph/configs/ppyolo/_base_/ppyolo_r18vd.yml

 architecture: YOLOv3
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet18_vd_pretrained.tar
-load_static_weights: true
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet18_vd_pretrained.pdparams
 norm_type: sync_bn
 use_ema: true
 ema_decay: 0.9998

dygraph/configs/ppyolo/_base_/ppyolo_r50vd_dcn.yml

 architecture: YOLOv3
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_ssld_pretrained.tar
-load_static_weights: true
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_pretrained.pdparams
 norm_type: sync_bn
 use_ema: true
 ema_decay: 0.9998

dygraph/configs/slim/prune/yolov3_prune_fpgm.yml

 # Weights of yolov3_mobilenet_v1_voc
 pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/dygraph/yolov3_mobilenet_v1_270e_voc.pdparams
-load_static_weights: False
 weight_type: resume
 slim: Pruner
 

dygraph/configs/slim/prune/yolov3_prune_l1_norm.yml

 # Weights of yolov3_mobilenet_v1_voc
 pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/dygraph/yolov3_mobilenet_v1_270e_voc.pdparams
-load_static_weights: False
 weight_type: resume
 slim: Pruner
 

dygraph/configs/slim/quant/yolov3_mobilenet_v1_qat.yml

 # Weights of yolov3_mobilenet_v1_coco
 pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/dygraph/yolov3_mobilenet_v1_270e_coco.pdparams
-load_static_weights: False
 weight_type: resume
 slim: QAT
 

dygraph/configs/slim/quant/yolov3_mobilenet_v3_qat.yml

 # Weights of yolov3_mobilenet_v3_coco
 pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/dygraph/yolov3_mobilenet_v3_large_270e_coco.pdparams
-load_static_weights: False
 weight_type: resume
 slim: QAT
 

dygraph/configs/solov2/_base_/solov2_r50_fpn.yml

 architecture: SOLOv2
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
 
 SOLOv2:
   backbone: ResNet

dygraph/configs/ssd/_base_/ssd_mobilenet_v1_300.yml

 architecture: SSD
-pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_coco_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ssd_mobilenet_v1_coco_pretrained.pdparams
 
 SSD:
   backbone: MobileNet

dygraph/configs/ssd/_base_/ssdlite_mobilenet_v1_300.yml

 architecture: SSD
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV1_ssld_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV1_ssld_pretrained.pdparams
 
 SSD:
   backbone: MobileNet

dygraph/configs/ssd/_base_/ssdlite_mobilenet_v3_large_320.yml

 architecture: SSD
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV3_large_x1_0_ssld_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams
 
 SSD:
   backbone: MobileNetV3

dygraph/configs/ssd/_base_/ssdlite_mobilenet_v3_small_320.yml

 architecture: SSD
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV3_small_x1_0_ssld_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_small_x1_0_ssld_pretrained.pdparams
 
 SSD:
   backbone: MobileNetV3

dygraph/configs/ttfnet/_base_/ttfnet_darknet53.yml

 architecture: TTFNet
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/DarkNet53_pretrained.pdparams
 
 TTFNet:
   backbone: DarkNet

dygraph/configs/yolov3/_base_/yolov3_darknet53.yml

 architecture: YOLOv3
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/DarkNet53_pretrained.pdparams
 norm_type: sync_bn
 
 YOLOv3:

dygraph/configs/yolov3/_base_/yolov3_mobilenet_v1.yml

 architecture: YOLOv3
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV1_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV1_pretrained.pdparams
 norm_type: sync_bn
 
 YOLOv3:

dygraph/configs/yolov3/_base_/yolov3_mobilenet_v3_large.yml

 architecture: YOLOv3
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV3_large_x1_0_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams
 norm_type: sync_bn
 
 YOLOv3:

dygraph/configs/yolov3/_base_/yolov3_mobilenet_v3_small.yml

 architecture: YOLOv3
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV3_small_x1_0_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_small_x1_0_ssld_pretrained.pdparams
 norm_type: sync_bn
 
 YOLOv3:

dygraph/configs/yolov3/_base_/yolov3_r50vd_dcn.yml

 architecture: YOLOv3
-pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_ssld_pretrained.tar
-load_static_weights: True
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_pretrained.pdparams
 norm_type: sync_bn
 
 YOLOv3:

dygraph/configs/yolov3/yolov3_mobilenet_v1_roadsign.yml

@@ -5,7 +5,6 @@ _BASE_: [
   '_base_/yolov3_reader.yml',
 ]
 pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/dygraph/yolov3_mobilenet_v1_270e_coco.pdparams
-load_static_weights: false
 norm_type: sync_bn
 weights: output/yolov3_mobilenet_v1_roadsign/model_final
 metric: VOC

dygraph/ppdet/engine/callbacks.py

@@ -29,7 +29,7 @@ from ppdet.utils.checkpoint import save_model
 from ppdet.optimizer import ModelEMA
 
 from ppdet.utils.logger import setup_logger
-logger = setup_logger(__name__)
+logger = setup_logger('ppdet.engine')
 
 __all__ = ['Callback', 'ComposeCallback', 'LogPrinter', 'Checkpointer']
 
@@ -53,27 +53,27 @@ class Callback(object):
 
 class ComposeCallback(object):
     def __init__(self, callbacks):
-        callbacks = [h for h in list(callbacks) if h is not None]
-        for h in callbacks:
-            assert isinstance(h,
-                              Callback), "hook shoule be subclass of Callback"
+        callbacks = [c for c in list(callbacks) if c is not None]
+        for c in callbacks:
+            assert isinstance(
+                c, Callback), "callback should be subclass of Callback"
         self._callbacks = callbacks
 
     def on_step_begin(self, status):
-        for h in self._callbacks:
-            h.on_step_begin(status)
+        for c in self._callbacks:
+            c.on_step_begin(status)
 
     def on_step_end(self, status):
-        for h in self._callbacks:
-            h.on_step_end(status)
+        for c in self._callbacks:
+            c.on_step_end(status)
 
     def on_epoch_begin(self, status):
-        for h in self._callbacks:
-            h.on_epoch_begin(status)
+        for c in self._callbacks:
+            c.on_epoch_begin(status)
 
     def on_epoch_end(self, status):
-        for h in self._callbacks:
-            h.on_epoch_end(status)
+        for c in self._callbacks:
+            c.on_epoch_end(status)
 
 
 class LogPrinter(Callback):

dygraph/ppdet/engine/export_utils.py

@@ -23,7 +23,7 @@ from collections import OrderedDict
 from ppdet.metrics import get_categories
 
 from ppdet.utils.logger import setup_logger
-logger = setup_logger(__name__)
+logger = setup_logger('ppdet.engine')
 
 # Global dictionary
 TRT_MIN_SUBGRAPH = {

dygraph/ppdet/engine/trainer.py

@@ -38,7 +38,7 @@ from .callbacks import Callback, ComposeCallback, LogPrinter, Checkpointer, Wife
 from .export_utils import _dump_infer_config
 
 from ppdet.utils.logger import setup_logger
-logger = setup_logger(__name__)
+logger = setup_logger('ppdet.engine')
 
 __all__ = ['Trainer']
 
@@ -157,7 +157,7 @@ class Trainer(object):
             metric.reset()
 
     def register_callbacks(self, callbacks):
-        callbacks = [h for h in list(callbacks) if h is not None]
+        callbacks = [c for c in list(callbacks) if c is not None]
         for c in callbacks:
             assert isinstance(c, Callback), \
                     "metrics shoule be instances of subclass of Metric"
@@ -179,9 +179,7 @@ class Trainer(object):
             logger.debug("Resume weights of epoch {}".format(self.start_epoch))
         else:
             self.start_epoch = 0
-            load_pretrain_weight(self.model, weights,
-                                 self.cfg.get('load_static_weights', False),
-                                 weight_type)
+            load_pretrain_weight(self.model, weights, weight_type)
             logger.debug("Load {} weights {} to start training".format(
                 weight_type, weights))
 

dygraph/ppdet/utils/checkpoint.py

@@ -142,10 +142,7 @@ def load_weight(model, weight, optimizer=None):
     return last_epoch
 
 
-def load_pretrain_weight(model,
-                         pretrain_weight,
-                         load_static_weights=False,
-                         weight_type='pretrain'):
+def load_pretrain_weight(model, pretrain_weight, weight_type='pretrain'):
 
     assert weight_type in ['pretrain', 'finetune']
     if is_url(pretrain_weight):
@@ -161,23 +158,6 @@ def load_pretrain_weight(model,
 
     model_dict = model.state_dict()
 
-    if load_static_weights:
-        pre_state_dict = paddle.static.load_program_state(path)
-        param_state_dict = {}
-        for key in model_dict.keys():
-            weight_name = model_dict[key].name
-            if weight_name in pre_state_dict.keys():
-                logger.info('Load weight: {}, shape: {}'.format(
-                    weight_name, pre_state_dict[weight_name].shape))
-                param_state_dict[key] = pre_state_dict[weight_name]
-            else:
-                if 'backbone' in key:
-                    logger.info('Lack weight: {}, structure name: {}'.format(
-                        weight_name, key))
-                param_state_dict[key] = model_dict[key]
-        model.set_dict(param_state_dict)
-        return
-
     param_state_dict = paddle.load(path + '.pdparams')
     if weight_type == 'pretrain':
         model.backbone.set_dict(param_state_dict)