diff --git a/configs/recognition/tsm/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb.py b/configs/recognition/tsm/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb.py
index 884a2d66..09050793 100644
--- a/configs/recognition/tsm/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb.py
+++ b/configs/recognition/tsm/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb.py
@@ -14,17 +14,20 @@ model = dict(
             mode='dot_product')))
 
 # dataset settings
-dataset_type = 'RawframeDataset'
-data_root = 'data/kinetics400/rawframes_train'
-data_root_val = 'data/kinetics400/rawframes_val'
-ann_file_train = 'data/kinetics400/kinetics400_train_list_rawframes.txt'
-ann_file_val = 'data/kinetics400/kinetics400_val_list_rawframes.txt'
-ann_file_test = 'data/kinetics400/kinetics400_val_list_rawframes.txt'
+dataset_type = 'VideoDataset'
+data_root = 'data/kinetics400/videos_train'
+data_root_val = 'data/kinetics400/videos_val'
+ann_file_train = 'data/kinetics400/kinetics400_train_list_videos.txt'
+ann_file_val = 'data/kinetics400/kinetics400_val_list_videos.txt'
+ann_file_test = 'data/kinetics400/kinetics400_val_list_videos.txt'
+
 img_norm_cfg = dict(
     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_bgr=False)
+
 train_pipeline = [
+    dict(type='DecordInit'),
     dict(type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8),
-    dict(type='RawFrameDecode'),
+    dict(type='DecordDecode'),
     dict(type='Resize', scale=(-1, 256)),
     dict(
         type='MultiScaleCrop',
@@ -41,13 +44,14 @@ train_pipeline = [
     dict(type='ToTensor', keys=['imgs', 'label'])
 ]
 val_pipeline = [
+    dict(type='DecordInit'),
     dict(
         type='SampleFrames',
         clip_len=1,
         frame_interval=1,
         num_clips=8,
         test_mode=True),
-    dict(type='RawFrameDecode'),
+    dict(type='DecordDecode'),
     dict(type='Resize', scale=(-1, 256)),
     dict(type='CenterCrop', crop_size=224),
     dict(type='Normalize', **img_norm_cfg),
@@ -56,13 +60,14 @@ val_pipeline = [
     dict(type='ToTensor', keys=['imgs'])
 ]
 test_pipeline = [
+    dict(type='DecordInit'),
     dict(
         type='SampleFrames',
         clip_len=1,
         frame_interval=1,
         num_clips=8,
         test_mode=True),
-    dict(type='RawFrameDecode'),
+    dict(type='DecordDecode'),
     dict(type='Resize', scale=(-1, 256)),
     dict(type='CenterCrop', crop_size=224),
     dict(type='Normalize', **img_norm_cfg),
@@ -73,7 +78,6 @@ test_pipeline = [
 data = dict(
     videos_per_gpu=8,
     workers_per_gpu=2,
-    test_dataloader=dict(videos_per_gpu=1),
     train=dict(
         type=dataset_type,
         ann_file=ann_file_train,
@@ -93,4 +97,4 @@ evaluation = dict(
     interval=5, metrics=['top_k_accuracy', 'mean_class_accuracy'])
 
 # runtime settings
-work_dir = './work_dirs/tsm_nl_gaussian_r50_1x1x8_50e_kinetics400_rgb/'
+work_dir = './work_dirs/tsm_nl_dot_product_r50_1x1x8_50e_kinetics400_rgb/'
-- 
2.25.1