add print_configs in infer and test

PaddleCV/video/configs/nonlocal.txt

@@ -82,7 +82,7 @@ use_multi_crop = 1
 [INFER]
 num_reader_threads = 8
 batch_size = 1
-filelist = 'dataset/nonlocal/inferencelist.txt'
+filelist = 'dataset/nonlocal/inferlist.txt'
 crop_size = 256
 sample_rate = 8
 video_length = 8

PaddleCV/video/datareader/nonlocal_reader.py

@@ -79,7 +79,7 @@ class NonlocalReader(DataReader):
             sample_times = 1
             return reader_func(filelist, batch_size, sample_times, False, False,
                                **dataset_args)
-        elif self.mode == 'test':
+        elif self.mode == 'test' or self.mode == 'infer':
             sample_times = cfg['TEST']['num_test_clips']
             if cfg['TEST']['use_multi_crop'] == 1:
                 sample_times = int(sample_times / 3)

PaddleCV/video/infer.py

@@ -83,8 +83,9 @@ def infer(args):
     # parse config
     config = parse_config(args.config)
     infer_config = merge_configs(config, 'infer', vars(args))
+    logger.info("############### infer config ###############")
+    print_configs(infer_config)
     infer_model = models.get_model(args.model_name, infer_config, mode='infer')
-
     infer_model.build_input(use_pyreader=False)
     infer_model.build_model()
     infer_feeds = infer_model.feeds()
@@ -105,10 +106,8 @@ def infer(args):
     # if no weight files specified, download weights from paddle
     weights = args.weights or infer_model.get_weights()
 
-    def if_exist(var):
-        return os.path.exists(os.path.join(weights, var.name))
-
-    fluid.io.load_vars(exe, weights, predicate=if_exist)
+    infer_model.load_test_weights(exe, weights,
+                                  fluid.default_main_program(), place)
 
     infer_feeder = fluid.DataFeeder(place=place, feed_list=infer_feeds)
     fetch_list = [x.name for x in infer_outputs]

PaddleCV/video/models/nonlocal_model/resnet_video.py

@@ -123,7 +123,7 @@ def obtain_arc(arc_type, video_length):
 def create_model(data, label, cfg, is_training=True, mode='train'):
     group = cfg.RESNETS.num_groups
     width_per_group = cfg.RESNETS.width_per_group
-    batch_size = int(cfg.TRAIN.batch_size / cfg.NUM_GPUS)
+    batch_size = int(cfg.TRAIN.batch_size / cfg.TRAIN.num_gpus)
 
     logger.info('--------------- ResNet-{} {}x{}d-{}, {} ---------------'.
                 format(cfg.MODEL.depth, group, width_per_group,

PaddleCV/video/scripts/infer/infer_nonlocal.sh

-python infer.py --model_name="NONLOCAL" --config=./configs/nonlocal.txt --filelist=./dataset/nonlocal/infer.list \
+python infer.py --model_name="NONLOCAL" --config=./configs/nonlocal.txt --filelist=./dataset/nonlocal/inferlist.txt \
                 --log_interval=10 --weights=./checkpoints/NONLOCAL_epoch0 --save_dir=./save

PaddleCV/video/test.py

@@ -68,6 +68,8 @@ def test(args):
     # parse config
     config = parse_config(args.config)
     test_config = merge_configs(config, 'test', vars(args))
+    logger.info("############### test config ###############")
+    print_configs(test_config)
 
     # build model
     test_model = models.get_model(args.model_name, test_config, mode='test')