diff --git "a/training_log.txt" "b/training_log.txt" new file mode 100644--- /dev/null +++ "b/training_log.txt" @@ -0,0 +1,11864 @@ +[03/12 16:10:53][INFO] train_net.py: 411: Train with config: +[03/12 16:10:53][INFO] train_net.py: 412: {'AUG': {'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', + 'COLOR_JITTER': 0.4, + 'ENABLE': True, + 'INTERPOLATION': 'bicubic', + 'NUM_SAMPLE': 1, + 'RE_COUNT': 1, + 'RE_MODE': 'pixel', + 'RE_PROB': 0.0, + 'RE_SPLIT': False}, + 'AVA': {'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', + 'BGR': False, + 'DETECTION_SCORE_THRESH': 0.9, + 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', + 'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', + 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', + 'FULL_TEST_ON_VAL': False, + 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', + 'IMG_PROC_BACKEND': 'cv2', + 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', + 'TEST_FORCE_FLIP': False, + 'TEST_LISTS': ['val.csv'], + 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], + 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], + 'TRAIN_LISTS': ['train.csv'], + 'TRAIN_PCA_JITTER_ONLY': True, + 'TRAIN_PREDICT_BOX_LISTS': [], + 'TRAIN_USE_COLOR_AUGMENTATION': False}, + 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), + 'BN': {'NORM_TYPE': 'batchnorm', + 'NUM_BATCHES_PRECISE': 200, + 'NUM_SPLITS': 1, + 'NUM_SYNC_DEVICES': 1, + 'USE_PRECISE_STATS': False, + 'WEIGHT_DECAY': 0.0}, + 'DATA': {'DECODING_BACKEND': 'decord', + 'ENSEMBLE_METHOD': 'sum', + 'EXTRA_PATH_TO_DATA_DIR': '', + 'IMAGE_TEMPLATE': '{:05d}.jpg', + 'INPUT_CHANNEL_NUM': [3], + 'INV_UNIFORM_SAMPLE': False, + 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', + 'MC': False, + 'MEAN': [0.45, 0.45, 0.45], + 'MULTI_LABEL': False, + 'NUM_FRAMES': 64, + 'PATH_LABEL_SEPARATOR': ' ', + 'PATH_PREFIX': '/data/DERI-AVA/data_dirs/rwf_2000/data_raw_2', + 'PATH_PREFIX_LIST': [''], + 'PATH_TO_DATA_DIR': '/data/DERI-AVA/data_dirs/rwf_2000/data_raw_2/data_paths', + 'PATH_TO_DATA_DIR_LIST': [''], + 'PATH_TO_PRELOAD_IMDB': '', + 'RANDOM_FLIP': True, + 'REVERSE_INPUT_CHANNEL': False, + 'SAMPLING_RATE': 16, + 'STD': [0.225, 0.225, 0.225], + 'TARGET_FPS': 30, + 'TEST_CROP_SIZE': 336, + 'TRAIN_CROP_SIZE': 336, + 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], + 'TRAIN_JITTER_MOTION_SHIFT': False, + 'TRAIN_JITTER_SCALES': [384, 480], + 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], + 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], + 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], + [-0.5808, -0.0045, -0.814], + [-0.5836, -0.6948, 0.4203]], + 'USE_OFFSET_SAMPLING': True}, + 'DATA_LOADER': {'ENABLE_MULTI_THREAD_DECODE': False, + 'NUM_WORKERS': 8, + 'PIN_MEMORY': True}, + 'DEMO': {'BUFFER_SIZE': 0, + 'CLIP_VIS_SIZE': 10, + 'COMMON_CLASS_NAMES': ['watch (a person)', + 'talk to (e.g., self, a person, a group)', + 'listen to (a person)', + 'touch (an object)', + 'carry/hold (an object)', + 'walk', + 'sit', + 'lie/sleep', + 'bend/bow (at the waist)'], + 'COMMON_CLASS_THRES': 0.7, + 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', + 'DETECTRON2_THRESH': 0.9, + 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', + 'DISPLAY_HEIGHT': 0, + 'DISPLAY_WIDTH': 0, + 'ENABLE': False, + 'FPS': 30, + 'GT_BOXES': '', + 'INPUT_FORMAT': 'BGR', + 'INPUT_VIDEO': '', + 'LABEL_FILE_PATH': '', + 'NUM_CLIPS_SKIP': 0, + 'NUM_VIS_INSTANCES': 2, + 'OUTPUT_FILE': '', + 'OUTPUT_FPS': -1, + 'PREDS_BOXES': '', + 'SLOWMO': 1, + 'STARTING_SECOND': 900, + 'THREAD_ENABLE': False, + 'UNCOMMON_CLASS_THRES': 0.3, + 'VIS_MODE': 'thres', + 'WEBCAM': -1}, + 'DETECTION': {'ALIGNED': True, + 'ENABLE': False, + 'ROI_XFORM_RESOLUTION': 7, + 'SPATIAL_SCALE_FACTOR': 16}, + 'DIST_BACKEND': 'nccl', + 'LOG_MODEL_INFO': True, + 'LOG_PERIOD': 10, + 'MIXUP': {'ALPHA': 0.8, + 'CUTMIX_ALPHA': 1.0, + 'ENABLE': False, + 'LABEL_SMOOTH_VALUE': 0.1, + 'PROB': 1.0, + 'SWITCH_PROB': 0.5}, + 'MODEL': {'ARCH': 'uniformerv2', + 'CHECKPOINT_NUM': [24], + 'DROPCONNECT_RATE': 0.0, + 'DROPOUT_RATE': 0.5, + 'EMA_DECAY': 0.9999, + 'EMA_EPOCH': -1, + 'FC_INIT_STD': 0.01, + 'HEAD_ACT': 'softmax', + 'LOSS_FUNC': 'cross_entropy', + 'MODEL_NAME': 'Uniformerv2', + 'MULTI_PATHWAY_ARCH': ['slowfast'], + 'NUM_CLASSES': 2, + 'NUM_CLASSES_LIST': [400, 600, 700], + 'SINGLE_PATHWAY_ARCH': ['2d', + 'c2d', + 'i3d', + 'slow', + 'x3d', + 'mvit', + 'uniformer', + 'uniformerv2'], + 'USE_CHECKPOINT': True}, + 'MULTIGRID': {'BN_BASE_SIZE': 8, + 'DEFAULT_B': 0, + 'DEFAULT_S': 0, + 'DEFAULT_T': 0, + 'EPOCH_FACTOR': 1.5, + 'EVAL_FREQ': 3, + 'LONG_CYCLE': False, + 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), + (0.5, 0.7071067811865476), + (0.5, 1), + (1, 1)], + 'LONG_CYCLE_SAMPLING_RATE': 0, + 'SHORT_CYCLE': False, + 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476]}, + 'MVIT': {'CLS_EMBED_ON': True, + 'DEPTH': 16, + 'DIM_MUL': [], + 'DROPOUT_RATE': 0.0, + 'DROPPATH_RATE': 0.1, + 'EMBED_DIM': 96, + 'HEAD_MUL': [], + 'MLP_RATIO': 4.0, + 'MODE': 'conv', + 'NORM': 'layernorm', + 'NORM_STEM': False, + 'NUM_HEADS': 1, + 'PATCH_2D': False, + 'PATCH_KERNEL': [3, 7, 7], + 'PATCH_PADDING': [2, 4, 4], + 'PATCH_STRIDE': [2, 4, 4], + 'POOL_KVQ_KERNEL': None, + 'POOL_KV_STRIDE': [], + 'POOL_Q_STRIDE': [], + 'QKV_BIAS': True, + 'SEP_POS_EMBED': False, + 'ZERO_DECAY_POS_CLS': True}, + 'NONLOCAL': {'GROUP': [[1], [1], [1], [1]], + 'INSTANTIATION': 'dot_product', + 'LOCATION': [[[]], [[]], [[]], [[]]], + 'POOL': [[[1, 2, 2], [1, 2, 2]], + [[1, 2, 2], [1, 2, 2]], + [[1, 2, 2], [1, 2, 2]], + [[1, 2, 2], [1, 2, 2]]]}, + 'NUM_GPUS': 2, + 'NUM_SHARDS': 1, + 'OUTPUT_DIR': './k400_exp_crp_rpt', + 'RESNET': {'DEPTH': 50, + 'INPLACE_RELU': True, + 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], + 'NUM_GROUPS': 1, + 'SPATIAL_DILATIONS': [[1], [1], [1], [1]], + 'SPATIAL_STRIDES': [[1], [2], [2], [2]], + 'STRIDE_1X1': False, + 'TRANS_FUNC': 'bottleneck_transform', + 'WIDTH_PER_GROUP': 64, + 'ZERO_INIT_FINAL_BN': False}, + 'RNG_SEED': 7, + 'SHARD_ID': 0, + 'SLOWFAST': {'ALPHA': 8, + 'BETA_INV': 8, + 'FUSION_CONV_CHANNEL_RATIO': 2, + 'FUSION_KERNEL_SZ': 5}, + 'SOLVER': {'BACKBONE_LR_RATIO': 0.1, + 'BASE_LR': 1.5e-06, + 'BASE_LR_SCALE_NUM_SHARDS': False, + 'CLIP_GRADIENT': 20, + 'COSINE_AFTER_WARMUP': True, + 'COSINE_END_LR': 1e-06, + 'DAMPENING': 0.0, + 'GAMMA': 0.1, + 'LRS': [], + 'LR_POLICY': 'cosine', + 'MAX_EPOCH': 50, + 'MOMENTUM': 0.9, + 'NESTEROV': True, + 'OPTIMIZING_METHOD': 'adamw', + 'SPECIAL_LIST': [], + 'SPECIAL_RATIO': 1.0, + 'STEPS': [], + 'STEP_SIZE': 1, + 'WARMUP_EPOCHS': 1.0, + 'WARMUP_FACTOR': 0.1, + 'WARMUP_START_LR': 1e-06, + 'WEIGHT_DECAY': 0.05, + 'ZERO_WD_1D_PARAM': True}, + 'TENSORBOARD': {'CATEGORIES_PATH': '', + 'CLASS_NAMES_PATH': '', + 'CONFUSION_MATRIX': {'ENABLE': False, + 'FIGSIZE': [8, 8], + 'SUBSET_PATH': ''}, + 'ENABLE': False, + 'HISTOGRAM': {'ENABLE': False, + 'FIGSIZE': [8, 8], + 'SUBSET_PATH': '', + 'TOPK': 10}, + 'LOG_DIR': '', + 'MODEL_VIS': {'ACTIVATIONS': False, + 'COLORMAP': 'Pastel2', + 'ENABLE': False, + 'GRAD_CAM': {'COLORMAP': 'viridis', + 'ENABLE': True, + 'LAYER_LIST': [], + 'USE_TRUE_LABEL': False}, + 'INPUT_VIDEO': False, + 'LAYER_LIST': [], + 'MODEL_WEIGHTS': False, + 'TOPK_PREDS': 1}, + 'PREDICTIONS_PATH': '', + 'WRONG_PRED_VIS': {'ENABLE': False, + 'SUBSET_PATH': '', + 'TAG': 'Incorrectly classified videos.'}}, + 'TEST': {'ADD_SOFTMAX': True, + 'BATCH_SIZE': 6, + 'CHECKPOINT_FILE_PATH': '', + 'CHECKPOINT_TYPE': 'pytorch', + 'DATASET': 'kinetics_sparse', + 'ENABLE': True, + 'INTERVAL': 2000, + 'NUM_ENSEMBLE_VIEWS': 4, + 'NUM_SPATIAL_CROPS': 3, + 'SAVE_RESULTS_PATH': '', + 'TEST_BEST': True}, + 'TRAIN': {'AUTO_RESUME': True, + 'BATCH_SIZE': 4, + 'CHECKPOINT_CLEAR_NAME_PATTERN': (), + 'CHECKPOINT_EPOCH_RESET': False, + 'CHECKPOINT_FILE_PATH': '', + 'CHECKPOINT_INFLATE': False, + 'CHECKPOINT_PERIOD': 50, + 'CHECKPOINT_TYPE': 'pytorch', + 'DATASET': 'kinetics_sparse', + 'ENABLE': True, + 'EVAL_PERIOD': 1, + 'SAVE_LATEST': True}, + 'UNIFORMER': {'ADD_MLP': True, + 'ATTENTION_DROPOUT_RATE': 0, + 'DEPTH': [3, 4, 8, 3], + 'DPE': True, + 'DROPOUT_RATE': 0, + 'DROP_DEPTH_RATE': 0.1, + 'EMBED_DIM': [64, 128, 320, 512], + 'HEAD_DIM': 64, + 'INIT_VALUE': 1.0, + 'KS': 5, + 'MBCONV': False, + 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], + 'NUM_HEADS': [1, 2, 5, 8], + 'PRETRAIN_NAME': None, + 'PRUNE_RATIO': [[], + [], + [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], + [0.5, 0.5, 0.5]], + 'QKV_BIAS': True, + 'QKV_SCALE': None, + 'RATIO': 1, + 'REPRESENTATION_SIZE': None, + 'SPLIT': False, + 'STAGE_TYPE': [0, 0, 1, 1], + 'STD': False, + 'TAU': 3, + 'TRADE_OFF': [[], + [], + [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], + [0.5, 0.5, 0.5]]}, + 'UNIFORMERV2': {'BACKBONE': 'uniformerv2_l14_336', + 'BACKBONE_DROP_PATH_RATE': 0.0, + 'CLS_DROPOUT': 0.5, + 'DELETE_SPECIAL_HEAD': True, + 'DOUBLE_LMHRA': True, + 'DROP_PATH_RATE': 0.0, + 'DW_REDUCTION': 1.5, + 'FROZEN': False, + 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], + 'MLP_FACTOR': 4.0, + 'NO_LMHRA': True, + 'N_DIM': 1024, + 'N_HEAD': 16, + 'N_LAYERS': 4, + 'PRETRAIN': '', + 'RETURN_LIST': [20, 21, 22, 23], + 'TEMPORAL_DOWNSAMPLE': False}, + 'VIP': {'ATTENTION_DROPOUT_RATE': 0, + 'DROP_DEPTH_RATE': 0.1, + 'EMBED_DIMS': [192, 384, 384, 384], + 'LAYERS': [4, 3, 8, 3], + 'MLP_RATIOS': [3, 3, 3, 3], + 'PATCH_SIZE': 7, + 'PRETRAIN_NAME': None, + 'QKV_BIAS': True, + 'QKV_SCALE': None, + 'SEGMENT_DIM': [32, 16, 16, 16], + 'ST_TYPE': 'st_skip', + 'TRANSITIONS': [True, False, False, False], + 'T_STRIDE': 1}, + 'X3D': {'BN_LIN5': False, + 'BOTTLENECK_FACTOR': 1.0, + 'CHANNELWISE_3x3x3': True, + 'DEPTH_FACTOR': 1.0, + 'DIM_C1': 12, + 'DIM_C5': 2048, + 'SCALE_RES2': False, + 'WIDTH_FACTOR': 1.0}} +[03/12 16:10:53][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:53][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:53][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:53][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:53][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:53][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:53][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:53][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:53][INFO] 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True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:54][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:54][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:54][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:54][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:54][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:54][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:54][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:54][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:54][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:54][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:55][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:55][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:55][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/12 16:10:55][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 76: Double L_MHRA: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 292: Use checkpoint: True +[03/12 16:10:55][INFO] uniformerv2_model.py: 293: Checkpoint number: [24] +[03/12 16:10:55][INFO] uniformerv2_model.py: 238: Drop path rate: 0.0 +[03/12 16:10:55][INFO] uniformerv2_model.py: 238: Drop path rate: 0.0 +[03/12 16:10:55][INFO] uniformerv2_model.py: 238: Drop path rate: 0.0 +[03/12 16:10:55][INFO] uniformerv2_model.py: 238: Drop path rate: 0.0 +[03/12 16:10:55][INFO] uniformerv2_model.py: 581: load pretrained weights +[03/12 16:10:59][INFO] uniformerv2_model.py: 446: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[03/12 16:10:59][INFO] uniformerv2_model.py: 427: Init center: True +[03/12 16:11:02][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[03/12 16:11:02][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[03/12 16:11:02][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 1600) from /data/DERI-AVA/data_dirs/rwf_2000/data_raw_2/data_paths/train.csv +[03/12 16:11:02][INFO] kinetics_sparse.py: 78: Constructing Kinetics val... +[03/12 16:11:02][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 400) from 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+[03/12 18:33:54][INFO] train_net.py: 492: Epoch 5 takes 1106.17s. 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492: Epoch 6 takes 1107.25s. 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+[03/12 19:47:15][INFO] train_net.py: 492: Epoch 8 takes 1105.72s. 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+[03/12 23:26:49][INFO] train_net.py: 492: Epoch 17 takes 1099.99s. 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+[03/13 00:39:45][INFO] train_net.py: 492: Epoch 20 takes 1099.09s. 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+[03/13 01:04:04][INFO] train_net.py: 492: Epoch 21 takes 1099.69s. Epochs from 0 to 21 take 1105.54s in average and 1102.67s in median. +[03/13 01:04:04][INFO] train_net.py: 498: For epoch 21, each iteraction takes 2.75s in average. 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03:29:55][INFO] train_net.py: 492: Epoch 27 takes 1100.36s. Epochs from 0 to 27 take 1104.05s in average and 1101.38s in median. +[03/13 03:29:55][INFO] train_net.py: 498: For epoch 27, each iteraction takes 2.75s in average. 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03:54:14][INFO] train_net.py: 492: Epoch 28 takes 1099.26s. Epochs from 0 to 28 take 1103.88s in average and 1100.86s in median. +[03/13 03:54:14][INFO] train_net.py: 498: For epoch 28, each iteraction takes 2.75s in average. 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+[03/13 05:07:09][INFO] train_net.py: 492: Epoch 31 takes 1096.95s. 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+[03/13 05:31:26][INFO] train_net.py: 492: Epoch 32 takes 1096.65s. 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+[03/13 05:55:41][INFO] train_net.py: 492: Epoch 33 takes 1095.28s. 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Epochs from 0 to 49 take 1100.74s in average and 1099.16s in median. +[03/13 12:24:02][INFO] train_net.py: 498: For epoch 49, each iteraction takes 2.74s in average. 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FRAME_LIST_DIR: /mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/ + FULL_TEST_ON_VAL: False + GROUNDTRUTH_FILE: ava_val_v2.2.csv + IMG_PROC_BACKEND: cv2 + LABEL_MAP_FILE: ava_action_list_v2.2_for_activitynet_2019.pbtxt + TEST_FORCE_FLIP: False + TEST_LISTS: ['val.csv'] + TEST_PREDICT_BOX_LISTS: ['ava_val_predicted_boxes.csv'] + TRAIN_GT_BOX_LISTS: ['ava_train_v2.2.csv'] + TRAIN_LISTS: ['train.csv'] + TRAIN_PCA_JITTER_ONLY: True + TRAIN_PREDICT_BOX_LISTS: [] + TRAIN_USE_COLOR_AUGMENTATION: False +BENCHMARK: + LOG_PERIOD: 100 + NUM_EPOCHS: 5 + SHUFFLE: True +BN: + NORM_TYPE: batchnorm + NUM_BATCHES_PRECISE: 200 + NUM_SPLITS: 1 + NUM_SYNC_DEVICES: 1 + USE_PRECISE_STATS: False + WEIGHT_DECAY: 0.0 +DATA: + DECODING_BACKEND: decord + ENSEMBLE_METHOD: sum + EXTRA_PATH_TO_DATA_DIR: + IMAGE_TEMPLATE: {:05d}.jpg + INPUT_CHANNEL_NUM: [3] + INV_UNIFORM_SAMPLE: False + LABEL_PATH_TEMPLATE: somesomev1_rgb_{}_split.txt + MC: False + MEAN: [0.45, 0.45, 0.45] + MULTI_LABEL: False + NUM_FRAMES: 64 + PATH_LABEL_SEPARATOR: + PATH_PREFIX: /data/DERI-AVA/data_dirs/rwf_2000/data_raw_2 + PATH_PREFIX_LIST: [''] + PATH_TO_DATA_DIR: /data/DERI-AVA/data_dirs/rwf_2000/data_raw_2/data_paths + PATH_TO_DATA_DIR_LIST: [''] + PATH_TO_PRELOAD_IMDB: + RANDOM_FLIP: True + REVERSE_INPUT_CHANNEL: False + SAMPLING_RATE: 16 + STD: [0.225, 0.225, 0.225] + TARGET_FPS: 30 + TEST_CROP_SIZE: 336 + TRAIN_CROP_SIZE: 336 + TRAIN_JITTER_ASPECT_RELATIVE: [0.75, 1.3333] + TRAIN_JITTER_MOTION_SHIFT: False + TRAIN_JITTER_SCALES: [384, 480] + TRAIN_JITTER_SCALES_RELATIVE: [0.08, 1.0] + TRAIN_PCA_EIGVAL: [0.225, 0.224, 0.229] + TRAIN_PCA_EIGVEC: [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]] + USE_OFFSET_SAMPLING: True +DATA_LOADER: + ENABLE_MULTI_THREAD_DECODE: False + NUM_WORKERS: 8 + PIN_MEMORY: True +DEMO: + BUFFER_SIZE: 0 + CLIP_VIS_SIZE: 10 + COMMON_CLASS_NAMES: ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'] + COMMON_CLASS_THRES: 0.7 + DETECTRON2_CFG: COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml + DETECTRON2_THRESH: 0.9 + DETECTRON2_WEIGHTS: detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl + DISPLAY_HEIGHT: 0 + DISPLAY_WIDTH: 0 + ENABLE: False + FPS: 30 + GT_BOXES: + INPUT_FORMAT: BGR + INPUT_VIDEO: + LABEL_FILE_PATH: + NUM_CLIPS_SKIP: 0 + NUM_VIS_INSTANCES: 2 + OUTPUT_FILE: + OUTPUT_FPS: -1 + PREDS_BOXES: + SLOWMO: 1 + STARTING_SECOND: 900 + THREAD_ENABLE: False + UNCOMMON_CLASS_THRES: 0.3 + VIS_MODE: thres + WEBCAM: -1 +DETECTION: + ALIGNED: True + ENABLE: False + ROI_XFORM_RESOLUTION: 7 + SPATIAL_SCALE_FACTOR: 16 +DIST_BACKEND: nccl +LOG_MODEL_INFO: True +LOG_PERIOD: 10 +MIXUP: + ALPHA: 0.8 + CUTMIX_ALPHA: 1.0 + ENABLE: False + LABEL_SMOOTH_VALUE: 0.1 + PROB: 1.0 + SWITCH_PROB: 0.5 +MODEL: + ARCH: uniformerv2 + CHECKPOINT_NUM: [24] + DROPCONNECT_RATE: 0.0 + DROPOUT_RATE: 0.5 + EMA_DECAY: 0.9999 + EMA_EPOCH: -1 + FC_INIT_STD: 0.01 + HEAD_ACT: softmax + LOSS_FUNC: cross_entropy + MODEL_NAME: Uniformerv2 + MULTI_PATHWAY_ARCH: ['slowfast'] + NUM_CLASSES: 2 + NUM_CLASSES_LIST: [400, 600, 700] + SINGLE_PATHWAY_ARCH: ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'] + USE_CHECKPOINT: True +MULTIGRID: + BN_BASE_SIZE: 8 + DEFAULT_B: 0 + DEFAULT_S: 0 + DEFAULT_T: 0 + EPOCH_FACTOR: 1.5 + EVAL_FREQ: 3 + LONG_CYCLE: False + LONG_CYCLE_FACTORS: [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)] + LONG_CYCLE_SAMPLING_RATE: 0 + SHORT_CYCLE: False + SHORT_CYCLE_FACTORS: [0.5, 0.7071067811865476] +MVIT: + CLS_EMBED_ON: True + DEPTH: 16 + DIM_MUL: [] + DROPOUT_RATE: 0.0 + DROPPATH_RATE: 0.1 + EMBED_DIM: 96 + HEAD_MUL: [] + MLP_RATIO: 4.0 + MODE: conv + NORM: layernorm + NORM_STEM: False + NUM_HEADS: 1 + PATCH_2D: False + PATCH_KERNEL: [3, 7, 7] + PATCH_PADDING: [2, 4, 4] + PATCH_STRIDE: [2, 4, 4] + POOL_KVQ_KERNEL: None + POOL_KV_STRIDE: [] + POOL_Q_STRIDE: [] + QKV_BIAS: True + SEP_POS_EMBED: False + ZERO_DECAY_POS_CLS: True +NONLOCAL: + GROUP: [[1], [1], [1], [1]] + INSTANTIATION: dot_product + LOCATION: [[[]], [[]], [[]], [[]]] + POOL: [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]] +NUM_GPUS: 2 +NUM_SHARDS: 1 +OUTPUT_DIR: ./k400_exp_crp_rpt +RESNET: + DEPTH: 50 + INPLACE_RELU: True + NUM_BLOCK_TEMP_KERNEL: [[3], [4], [6], [3]] + NUM_GROUPS: 1 + SPATIAL_DILATIONS: [[1], [1], [1], [1]] + SPATIAL_STRIDES: [[1], [2], [2], [2]] + STRIDE_1X1: False + TRANS_FUNC: bottleneck_transform + WIDTH_PER_GROUP: 64 + ZERO_INIT_FINAL_BN: False +RNG_SEED: 7 +SHARD_ID: 0 +SLOWFAST: + ALPHA: 8 + BETA_INV: 8 + FUSION_CONV_CHANNEL_RATIO: 2 + FUSION_KERNEL_SZ: 5 +SOLVER: + BACKBONE_LR_RATIO: 0.1 + BASE_LR: 1.5e-06 + BASE_LR_SCALE_NUM_SHARDS: False + CLIP_GRADIENT: 20 + COSINE_AFTER_WARMUP: True + COSINE_END_LR: 1e-06 + DAMPENING: 0.0 + GAMMA: 0.1 + LRS: [] + LR_POLICY: cosine + MAX_EPOCH: 50 + MOMENTUM: 0.9 + NESTEROV: True + OPTIMIZING_METHOD: adamw + SPECIAL_LIST: [] + SPECIAL_RATIO: 1.0 + STEPS: [] + STEP_SIZE: 1 + WARMUP_EPOCHS: 1.0 + WARMUP_FACTOR: 0.1 + WARMUP_START_LR: 1e-06 + WEIGHT_DECAY: 0.05 + ZERO_WD_1D_PARAM: True +TENSORBOARD: + CATEGORIES_PATH: + CLASS_NAMES_PATH: + CONFUSION_MATRIX: + ENABLE: False + FIGSIZE: [8, 8] + SUBSET_PATH: + ENABLE: False + HISTOGRAM: + ENABLE: False + FIGSIZE: [8, 8] + SUBSET_PATH: + TOPK: 10 + LOG_DIR: + MODEL_VIS: + ACTIVATIONS: False + COLORMAP: Pastel2 + ENABLE: False + GRAD_CAM: + COLORMAP: viridis + ENABLE: True + LAYER_LIST: [] + USE_TRUE_LABEL: False + INPUT_VIDEO: False + LAYER_LIST: [] + MODEL_WEIGHTS: False + TOPK_PREDS: 1 + PREDICTIONS_PATH: + WRONG_PRED_VIS: + ENABLE: False + SUBSET_PATH: + TAG: Incorrectly classified videos. +TEST: + ADD_SOFTMAX: True + BATCH_SIZE: 6 + CHECKPOINT_FILE_PATH: + CHECKPOINT_TYPE: pytorch + DATASET: kinetics_sparse + ENABLE: True + INTERVAL: 2000 + NUM_ENSEMBLE_VIEWS: 4 + NUM_SPATIAL_CROPS: 3 + SAVE_RESULTS_PATH: + TEST_BEST: True +TRAIN: + AUTO_RESUME: True + BATCH_SIZE: 4 + CHECKPOINT_CLEAR_NAME_PATTERN: () + CHECKPOINT_EPOCH_RESET: False + CHECKPOINT_FILE_PATH: + CHECKPOINT_INFLATE: False + CHECKPOINT_PERIOD: 50 + CHECKPOINT_TYPE: pytorch + DATASET: kinetics_sparse + ENABLE: True + EVAL_PERIOD: 1 + SAVE_LATEST: True +UNIFORMER: + ADD_MLP: True + ATTENTION_DROPOUT_RATE: 0 + DEPTH: [3, 4, 8, 3] + DPE: True + DROPOUT_RATE: 0 + DROP_DEPTH_RATE: 0.1 + EMBED_DIM: [64, 128, 320, 512] + HEAD_DIM: 64 + INIT_VALUE: 1.0 + KS: 5 + MBCONV: False + MLP_RATIO: [4.0, 4.0, 4.0, 4.0] + NUM_HEADS: [1, 2, 5, 8] + PRETRAIN_NAME: None + PRUNE_RATIO: [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]] + QKV_BIAS: True + QKV_SCALE: None + RATIO: 1 + REPRESENTATION_SIZE: None + SPLIT: False + STAGE_TYPE: [0, 0, 1, 1] + STD: False + TAU: 3 + TRADE_OFF: [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]] +UNIFORMERV2: + BACKBONE: uniformerv2_l14_336 + BACKBONE_DROP_PATH_RATE: 0.0 + CLS_DROPOUT: 0.5 + DELETE_SPECIAL_HEAD: True + DOUBLE_LMHRA: True + DROP_PATH_RATE: 0.0 + DW_REDUCTION: 1.5 + FROZEN: False + MLP_DROPOUT: [0.5, 0.5, 0.5, 0.5] + MLP_FACTOR: 4.0 + NO_LMHRA: True + N_DIM: 1024 + N_HEAD: 16 + N_LAYERS: 4 + PRETRAIN: + RETURN_LIST: [20, 21, 22, 23] + TEMPORAL_DOWNSAMPLE: False +VIP: + ATTENTION_DROPOUT_RATE: 0 + DROP_DEPTH_RATE: 0.1 + EMBED_DIMS: [192, 384, 384, 384] + LAYERS: [4, 3, 8, 3] + MLP_RATIOS: [3, 3, 3, 3] + PATCH_SIZE: 7 + PRETRAIN_NAME: None + QKV_BIAS: True + QKV_SCALE: None + SEGMENT_DIM: [32, 16, 16, 16] + ST_TYPE: st_skip + TRANSITIONS: [True, False, False, False] + T_STRIDE: 1 +X3D: + BN_LIN5: False + BOTTLENECK_FACTOR: 1.0 + CHANNELWISE_3x3x3: True + DEPTH_FACTOR: 1.0 + DIM_C1: 12 + DIM_C5: 2048 + SCALE_RES2: False + WIDTH_FACTOR: 1.0 +[03/13 12:30:46][INFO] uniformerv2_model.py: 71: Drop path rate: 0.0 +[03/13 12:30:46][INFO] uniformerv2_model.py: 75: No L_MHRA: True +[03/13 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'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 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'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/data/DERI-AVA/data_dirs/rwf_2000/data_raw_2/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ' ', 'PATH_PREFIX': '/data/DERI-AVA/data_dirs/rwf_2000/data_raw_2', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 04:46:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 04:46:34][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 04:46:34][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:46:34][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 04:51:41][INFO] train_net.py: 411: Train with config: +[11/21 04:51:41][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 8, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/data/DERI-AVA/data_dirs/rwf_2000/data_raw_2/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ' ', 'PATH_PREFIX': '/data/DERI-AVA/data_dirs/rwf_2000/data_raw_2', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 04:51:41][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:41][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:41][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:41][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:41][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:41][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:41][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:41][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:41][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 04:51:42][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 04:51:42][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:51:42][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 04:51:43][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 04:51:43][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 04:51:43][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 04:51:43][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 04:58:27][INFO] train_net.py: 411: Train with config: +[11/21 04:58:27][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 8, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ' ', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:27][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:27][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 04:58:28][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 04:58:28][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 04:58:28][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 04:58:29][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 04:58:29][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 04:58:29][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 04:58:29][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:03:10][INFO] train_net.py: 411: Train with config: +[11/21 05:03:10][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 8, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ' ', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:03:11][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 05:03:11][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 05:03:11][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:03:12][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:03:12][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:03:12][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:03:12][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 05:03:12][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 05:03:12][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 05:03:12][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 05:03:12][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:17:25][INFO] train_net.py: 411: Train with config: +[11/21 05:17:25][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 8, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ' ', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 05:17:25][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:25][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:25][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:25][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:25][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:25][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:25][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:25][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:25][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:25][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:25][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:25][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 05:17:26][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 05:17:26][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:17:26][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:17:27][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 05:17:27][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 05:17:27][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 05:17:27][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 05:17:27][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:20:02][INFO] train_net.py: 411: Train with config: +[11/21 05:20:02][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 8, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ',', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 05:20:02][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:02][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:02][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:02][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:02][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:02][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:02][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:02][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 05:20:03][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 05:20:03][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:20:03][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 05:20:04][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 05:20:04][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 05:20:04][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 05:20:04][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:20:04][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 1599) from /workspace/data_paths/train.csv +[11/21 05:22:23][INFO] train_net.py: 411: Train with config: +[11/21 05:22:23][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 8, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ',', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:23][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:23][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 05:22:24][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 05:22:24][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:22:24][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 05:22:25][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 05:22:25][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 05:22:25][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 05:22:25][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:22:25][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 1599) from /workspace/data_paths/train.csv +[11/21 05:22:25][INFO] kinetics_sparse.py: 78: Constructing Kinetics val... +[11/21 05:22:25][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 400) from /workspace/data_paths/val.csv +[11/21 05:22:25][INFO] tensorboard_vis.py: 54: To see logged results in Tensorboard, please launch using the command `tensorboard --port= --logdir ./exp/RWF_exp/runs-kinetics_sparse` +[11/21 05:22:25][INFO] train_net.py: 456: Start epoch: 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 151 from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi; trial 0 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 261 from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 151 from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi; trial 1 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 261 from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 151 from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi; trial 2 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 261 from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi; trial 2 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 151 from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 261 from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 151 from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi; trial 4 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 261 from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi; trial 4 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1257 from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 151 from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 261 from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 99 from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 151 from /workspace/RWF-2000-Cropped/NonFight/GgT095uX_0.avi; trial 6 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 261 from /workspace/RWF-2000-Cropped/NonFight/HbfZYAXw_0.avi; trial 6 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1257 from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/gNUhUpxZ_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/gNUhUpxZ_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 99 from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/d3WwO8eM_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/d3WwO8eM_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1257 from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi; trial 2 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 109 from /workspace/RWF-2000-Cropped/NonFight/gNUhUpxZ_0.avi; trial 7 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 561 from /workspace/RWF-2000-Cropped/NonFight/d3WwO8eM_0.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/bzw-HKuuQbg_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/bzw-HKuuQbg_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/DC10fyQgNqo_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/DC10fyQgNqo_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 99 from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi; trial 2 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1257 from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi; trial 3 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 809 from /workspace/RWF-2000-Cropped/Fight/bzw-HKuuQbg_1.avi; trial 8 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1158 from /workspace/RWF-2000-Cropped/Fight/DC10fyQgNqo_1.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/uKFI67bUzfg_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/uKFI67bUzfg_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 99 from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1414 from /workspace/RWF-2000-Cropped/Fight/uKFI67bUzfg_0.avi; trial 9 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1257 from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/xWBtjX00_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/xWBtjX00_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 440 from /workspace/RWF-2000-Cropped/NonFight/xWBtjX00_0.avi; trial 9 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 99 from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi; trial 4 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 463 from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi; trial 0 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1257 from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi; trial 5 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 99 from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1257 from /workspace/RWF-2000-Cropped/Fight/OAfV0xPIhZw_0.avi; trial 6 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 99 from /workspace/RWF-2000-Cropped/NonFight/qrWTk-2a13o_2.avi; trial 6 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/as4zD6d86q0_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/as4zD6d86q0_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 996 from /workspace/RWF-2000-Cropped/Fight/as4zD6d86q0_1.avi; trial 7 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 463 from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/QaIY5Au8yOc_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/QaIY5Au8yOc_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1453 from /workspace/RWF-2000-Cropped/Fight/QaIY5Au8yOc_1.avi; trial 8 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1313 from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/DC10fyQgNqo_2.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/DC10fyQgNqo_2.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1595 from /workspace/RWF-2000-Cropped/Fight/DC10fyQgNqo_2.avi; trial 9 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1232 from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 463 from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi; trial 2 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1313 from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi; trial 1 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1232 from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi; trial 1 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 463 from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 300 from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 300 from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/b6XfVAZC9Zs_7.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/b6XfVAZC9Zs_7.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1380 from /workspace/RWF-2000-Cropped/Fight/b6XfVAZC9Zs_7.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 300 from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi; trial 2 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1313 from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi; trial 2 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1232 from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi; trial 2 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 463 from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi; trial 4 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 931 from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 300 from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 931 from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 300 from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 931 from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi; trial 2 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 463 from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1232 from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi; trial 3 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 300 from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1313 from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 931 from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 300 from /workspace/RWF-2000-Cropped/NonFight/arXD3QM2_0.avi; trial 6 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/oLs9ckoV_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/oLs9ckoV_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 931 from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 631 from /workspace/RWF-2000-Cropped/NonFight/oLs9ckoV_0.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 463 from /workspace/RWF-2000-Cropped/NonFight/J2rsCgMC_0.avi; trial 6 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1232 from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi; trial 4 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1313 from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/t2z75yT2S_M_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/t2z75yT2S_M_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 931 from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1115 from /workspace/RWF-2000-Cropped/Fight/t2z75yT2S_M_1.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/ypdSZICv_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/ypdSZICv_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 931 from /workspace/RWF-2000-Cropped/Fight/1XFiS6Lt_0.avi; trial 6 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/iRnSE1TL_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/iRnSE1TL_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 502 from /workspace/RWF-2000-Cropped/NonFight/ypdSZICv_0.avi; trial 8 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 521 from /workspace/RWF-2000-Cropped/NonFight/iRnSE1TL_0.avi; trial 9 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/i5xJxtv4gXs_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/i5xJxtv4gXs_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/ar5ns2zW4lY_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/ar5ns2zW4lY_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 219 from /workspace/RWF-2000-Cropped/NonFight/i5xJxtv4gXs_0.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/bQHNsRpQOIE_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/bQHNsRpQOIE_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 266 from /workspace/RWF-2000-Cropped/NonFight/bQHNsRpQOIE_0.avi; trial 9 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1313 from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1232 from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1463 from /workspace/RWF-2000-Cropped/Fight/ar5ns2zW4lY_1.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/lmfaDmCCRoY_5.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/lmfaDmCCRoY_5.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1244 from /workspace/RWF-2000-Cropped/Fight/lmfaDmCCRoY_5.avi; trial 8 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 814 from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/vBwKQfJYG1Q_2.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/vBwKQfJYG1Q_2.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/ATDMY6PzK9U_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/ATDMY6PzK9U_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1053 from /workspace/RWF-2000-Cropped/Fight/vBwKQfJYG1Q_2.avi; trial 9 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1313 from /workspace/RWF-2000-Cropped/Fight/RYFG_779.avi; trial 6 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1232 from /workspace/RWF-2000-Cropped/Fight/1dsLuL5Lvbc_0.avi; trial 6 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 758 from /workspace/RWF-2000-Cropped/NonFight/ATDMY6PzK9U_0.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 814 from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/X6V5o-uCYF4_4.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/X6V5o-uCYF4_4.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/4RgIlSIB_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/4RgIlSIB_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/La60qonu_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/La60qonu_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 42 from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi; trial 0 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1206 from /workspace/RWF-2000-Cropped/Fight/X6V5o-uCYF4_4.avi; trial 7 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 410 from /workspace/RWF-2000-Cropped/NonFight/4RgIlSIB_0.avi; trial 9 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 203 from /workspace/RWF-2000-Cropped/NonFight/La60qonu_0.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 42 from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 42 from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi; trial 2 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/FB3eqRE8_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/FB3eqRE8_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 42 from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/sadffg_950.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/sadffg_950.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 477 from /workspace/RWF-2000-Cropped/NonFight/FB3eqRE8_0.avi; trial 8 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1307 from /workspace/RWF-2000-Cropped/Fight/sadffg_950.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 42 from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 42 from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi; trial 5 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 42 from /workspace/RWF-2000-Cropped/NonFight/_q5Nwh4Z6ao_0.avi; trial 6 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/cAp5A44HRS8_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/cAp5A44HRS8_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/NxtwlqSnLbY_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/NxtwlqSnLbY_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 814 from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi; trial 2 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1243 from /workspace/RWF-2000-Cropped/Fight/cAp5A44HRS8_0.avi; trial 9 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 782 from /workspace/RWF-2000-Cropped/NonFight/NxtwlqSnLbY_1.avi; trial 9 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/4yTlGiDoxBo_2.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/4yTlGiDoxBo_2.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 816 from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi; trial 0 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 937 from /workspace/RWF-2000-Cropped/Fight/4yTlGiDoxBo_2.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 816 from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 816 from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi; trial 2 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 816 from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/nNUeqFgG_3.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/nNUeqFgG_3.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1179 from /workspace/RWF-2000-Cropped/Fight/nNUeqFgG_3.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 816 from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_2.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_2.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1511 from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_2.avi; trial 9 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 816 from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi; trial 5 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 816 from /workspace/RWF-2000-Cropped/Fight/T56HlypCEyU_1.avi; trial 6 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 814 from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/JRL5Vvql_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/JRL5Vvql_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1341 from /workspace/RWF-2000-Cropped/Fight/JRL5Vvql_1.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 814 from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/YQkE7oOf_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/YQkE7oOf_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 230 from /workspace/RWF-2000-Cropped/NonFight/YQkE7oOf_0.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 814 from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi; trial 5 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/NxtwlqSnLbY_4.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/NxtwlqSnLbY_4.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 839 from /workspace/RWF-2000-Cropped/Fight/NxtwlqSnLbY_4.avi; trial 9 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 814 from /workspace/RWF-2000-Cropped/Fight/YaWxiAtCwxE_1.avi; trial 6 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/8SWZq5we_fk_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/8SWZq5we_fk_2.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 327 from /workspace/RWF-2000-Cropped/NonFight/8SWZq5we_fk_2.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/ytjGIK9m_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/ytjGIK9m_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 662 from /workspace/RWF-2000-Cropped/NonFight/ytjGIK9m_0.avi; trial 8 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 737 from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/0H2s9UJcNJ0_5.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/0H2s9UJcNJ0_5.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 896 from /workspace/RWF-2000-Cropped/Fight/0H2s9UJcNJ0_5.avi; trial 9 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 737 from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 737 from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi; trial 2 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 737 from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi; trial 3 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 384 from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 737 from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1117 from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 384 from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1117 from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi; trial 1 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 702 from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi; trial 0 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1117 from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi; trial 2 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 702 from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi; trial 1 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 384 from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi; trial 2 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 737 from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1117 from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1117 from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1117 from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 702 from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi; trial 2 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 384 from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi; trial 3 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 737 from /workspace/RWF-2000-Cropped/NonFight/kExp3yhspR0_1.avi; trial 6 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1117 from /workspace/RWF-2000-Cropped/Fight/aKK0B4kpKZA_0.avi; trial 6 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/yldWawWf_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/yldWawWf_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 697 from /workspace/RWF-2000-Cropped/NonFight/yldWawWf_0.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/b6XfVAZC9Zs_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/b6XfVAZC9Zs_2.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 384 from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi; trial 4 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 702 from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi; trial 3 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 526 from /workspace/RWF-2000-Cropped/NonFight/b6XfVAZC9Zs_2.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/Qqfn1urQ_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/Qqfn1urQ_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 719 from /workspace/RWF-2000-Cropped/NonFight/Qqfn1urQ_0.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/4_223.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/4_223.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1133 from /workspace/RWF-2000-Cropped/Fight/4_223.avi; trial 9 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/FZDDNtcaBcw_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/FZDDNtcaBcw_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 384 from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 702 from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi; trial 4 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 350 from /workspace/RWF-2000-Cropped/NonFight/FZDDNtcaBcw_0.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/Jt4WbOZeT7s_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/Jt4WbOZeT7s_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 702 from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi; trial 5 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 384 from /workspace/RWF-2000-Cropped/NonFight/WHNtrI7MEUg_1.avi; trial 6 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1422 from /workspace/RWF-2000-Cropped/Fight/Jt4WbOZeT7s_0.avi; trial 9 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/aQysMqg0K7M_2.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/aQysMqg0K7M_2.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 702 from /workspace/RWF-2000-Cropped/NonFight/rRbZUKgk_0.avi; trial 6 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 249 from /workspace/RWF-2000-Cropped/NonFight/aQysMqg0K7M_2.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/lI17Q0j3_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/lI17Q0j3_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/DjLWv5mr_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/DjLWv5mr_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1387 from /workspace/RWF-2000-Cropped/Fight/lI17Q0j3_0.avi; trial 7 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 108 from /workspace/RWF-2000-Cropped/NonFight/DjLWv5mr_0.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/BUjGBAPb_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/BUjGBAPb_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/8_317.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/8_317.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 385 from /workspace/RWF-2000-Cropped/NonFight/BUjGBAPb_0.avi; trial 9 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 472 from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi; trial 0 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 822 from /workspace/RWF-2000-Cropped/Fight/8_317.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 472 from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi; trial 1 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/q2yEYFD5_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/q2yEYFD5_0.avi... +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 421 from /workspace/RWF-2000-Cropped/NonFight/q2yEYFD5_0.avi; trial 9 +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 472 from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi; trial 2 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 472 from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi; trial 3 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 472 from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi; trial 4 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 472 from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi; trial 5 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 472 from /workspace/RWF-2000-Cropped/NonFight/8MuRpAyP_0.avi; trial 6 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/mRqg-WXiR7Q_0.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/mRqg-WXiR7Q_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1299 from /workspace/RWF-2000-Cropped/Fight/mRqg-WXiR7Q_0.avi; trial 7 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/Fight/pKOUG5AqLpY_1.avi with error Error reading /workspace/RWF-2000-Cropped/Fight/pKOUG5AqLpY_1.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 1006 from /workspace/RWF-2000-Cropped/Fight/pKOUG5AqLpY_1.avi; trial 8 +[11/21 05:22:25][INFO] kinetics_sparse.py: 221: Failed to load video from /workspace/RWF-2000-Cropped/NonFight/1A3zEkCHBl8_0.avi with error Error reading /workspace/RWF-2000-Cropped/NonFight/1A3zEkCHBl8_0.avi... +[11/21 05:22:25][WARNING] kinetics_sparse.py: 228: Failed to load video idx 191 from /workspace/RWF-2000-Cropped/NonFight/1A3zEkCHBl8_0.avi; trial 9 +[11/21 05:24:33][INFO] train_net.py: 411: Train with config: +[11/21 05:24:33][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 8, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ',', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 05:24:34][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 05:24:34][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:24:34][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 05:24:35][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 05:24:35][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 05:24:35][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 05:24:35][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:24:35][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 1599) from /workspace/data_paths/train.csv +[11/21 05:24:35][INFO] kinetics_sparse.py: 78: Constructing Kinetics val... +[11/21 05:24:35][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 400) from /workspace/data_paths/val.csv +[11/21 05:24:35][INFO] tensorboard_vis.py: 54: To see logged results in Tensorboard, please launch using the command `tensorboard --port= --logdir ./exp/RWF_exp/runs-kinetics_sparse` +[11/21 05:24:35][INFO] train_net.py: 456: Start epoch: 1 +[11/21 05:26:32][INFO] train_net.py: 411: Train with config: +[11/21 05:26:32][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 4, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ',', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 05:26:32][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:32][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:32][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:32][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:32][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:32][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:32][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:32][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:32][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 05:26:33][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 05:26:33][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:26:33][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:26:34][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:26:34][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 05:26:34][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 05:26:34][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 05:26:34][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 05:26:34][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:26:34][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 1599) from /workspace/data_paths/train.csv +[11/21 05:26:34][INFO] kinetics_sparse.py: 78: Constructing Kinetics val... +[11/21 05:26:34][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 400) from /workspace/data_paths/val.csv +[11/21 05:26:34][INFO] tensorboard_vis.py: 54: To see logged results in Tensorboard, please launch using the command `tensorboard --port= --logdir ./exp/RWF_exp/runs-kinetics_sparse` +[11/21 05:26:34][INFO] train_net.py: 456: Start epoch: 1 +[11/21 05:27:31][INFO] train_net.py: 411: Train with config: +[11/21 05:27:31][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 4, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ',', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:32][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:32][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:32][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:32][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:27:32][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:27:32][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:27:32][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 05:27:32][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 05:27:32][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:27:32][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:27:32][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:27:32][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:27:32][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 05:27:32][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 05:27:32][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 05:27:32][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 05:27:32][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:27:32][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 1599) from /workspace/data_paths/train.csv +[11/21 05:27:32][INFO] kinetics_sparse.py: 78: Constructing Kinetics val... +[11/21 05:27:32][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 400) from /workspace/data_paths/val.csv +[11/21 05:27:32][INFO] tensorboard_vis.py: 54: To see logged results in Tensorboard, please launch using the command `tensorboard --port= --logdir ./exp/RWF_exp/runs-kinetics_sparse` +[11/21 05:27:32][INFO] train_net.py: 456: Start epoch: 1 +[11/21 05:30:12][INFO] train_net.py: 411: Train with config: +[11/21 05:30:12][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 2, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ',', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'decord', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 8, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:12][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:12][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 05:30:13][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 05:30:13][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:30:13][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 05:30:13][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 05:30:13][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 05:30:14][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 05:30:14][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:30:14][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 1599) from /workspace/data_paths/train.csv +[11/21 05:30:14][INFO] kinetics_sparse.py: 78: Constructing Kinetics val... +[11/21 05:30:14][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 400) from /workspace/data_paths/val.csv +[11/21 05:30:14][INFO] tensorboard_vis.py: 54: To see logged results in Tensorboard, please launch using the command `tensorboard --port= --logdir ./exp/RWF_exp/runs-kinetics_sparse` +[11/21 05:30:14][INFO] train_net.py: 456: Start epoch: 1 +[11/21 05:30:42][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.67351, "dt_data": 0.00729, "dt_net": 2.66622, "epoch": "1/51", "eta": "1 day, 6:15:16", "gpu_mem": "33.25G", "iter": "10/799", "loss": 0.79260, "lr": 0.00000, "top1_err": 50.00000, "top5_err": 0.00000} +[11/21 05:31:09][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.68601, "dt_data": 0.00868, "dt_net": 2.67733, "epoch": "1/51", "eta": "1 day, 6:23:18", "gpu_mem": "33.25G", "iter": "20/799", "loss": 1.00757, "lr": 0.00000, "top1_err": 50.00000, "top5_err": 0.00000} +[11/21 05:31:36][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.68865, "dt_data": 0.00795, "dt_net": 2.68071, "epoch": "1/51", "eta": "1 day, 6:24:39", "gpu_mem": "33.25G", "iter": "30/799", "loss": 0.61774, "lr": 0.00000, "top1_err": 50.00000, "top5_err": 0.00000} +[11/21 05:32:03][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.69164, "dt_data": 0.00861, "dt_net": 2.68302, "epoch": "1/51", "eta": "1 day, 6:26:13", "gpu_mem": "33.25G", "iter": "40/799", "loss": 0.52838, "lr": 0.00000, "top1_err": 25.00000, "top5_err": 0.00000} +[11/21 05:32:30][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.69028, "dt_data": 0.00727, "dt_net": 2.68301, "epoch": "1/51", "eta": "1 day, 6:24:51", "gpu_mem": "33.25G", "iter": "50/799", "loss": 0.76038, "lr": 0.00000, "top1_err": 50.00000, "top5_err": 0.00000} +[11/21 05:32:57][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.69015, "dt_data": 0.00786, "dt_net": 2.68229, "epoch": "1/51", "eta": "1 day, 6:24:19", "gpu_mem": "33.25G", "iter": "60/799", "loss": 0.72400, "lr": 0.00000, "top1_err": 50.00000, "top5_err": 0.00000} +[11/21 05:48:30][INFO] train_net.py: 411: Train with config: +[11/21 05:48:30][INFO] train_net.py: 412: CfgNode({'BN': CfgNode({'USE_PRECISE_STATS': False, 'NUM_BATCHES_PRECISE': 200, 'WEIGHT_DECAY': 0.0, 'NORM_TYPE': 'batchnorm', 'NUM_SPLITS': 1, 'NUM_SYNC_DEVICES': 1}), 'TRAIN': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 2, 'EVAL_PERIOD': 1, 'CHECKPOINT_PERIOD': 52, 'AUTO_RESUME': True, 'CHECKPOINT_FILE_PATH': '', 'CHECKPOINT_TYPE': 'pytorch', 'CHECKPOINT_INFLATE': False, 'CHECKPOINT_EPOCH_RESET': False, 'CHECKPOINT_CLEAR_NAME_PATTERN': (), 'SAVE_LATEST': True}), 'AUG': CfgNode({'ENABLE': True, 'NUM_SAMPLE': 1, 'COLOR_JITTER': 0.4, 'AA_TYPE': 'rand-m7-n4-mstd0.5-inc1', 'INTERPOLATION': 'bicubic', 'RE_PROB': 0.0, 'RE_MODE': 'pixel', 'RE_COUNT': 1, 'RE_SPLIT': False}), 'MIXUP': CfgNode({'ENABLE': False, 'ALPHA': 0.8, 'CUTMIX_ALPHA': 1.0, 'PROB': 1.0, 'SWITCH_PROB': 0.5, 'LABEL_SMOOTH_VALUE': 0.1}), 'TEST': CfgNode({'ENABLE': True, 'DATASET': 'kinetics_sparse', 'BATCH_SIZE': 6, 'CHECKPOINT_FILE_PATH': '', 'NUM_ENSEMBLE_VIEWS': 4, 'NUM_SPATIAL_CROPS': 3, 'CHECKPOINT_TYPE': 'pytorch', 'SAVE_RESULTS_PATH': '', 'TEST_BEST': True, 'ADD_SOFTMAX': True, 'INTERVAL': 2000}), 'RESNET': CfgNode({'TRANS_FUNC': 'bottleneck_transform', 'NUM_GROUPS': 1, 'WIDTH_PER_GROUP': 64, 'INPLACE_RELU': True, 'STRIDE_1X1': False, 'ZERO_INIT_FINAL_BN': False, 'DEPTH': 50, 'NUM_BLOCK_TEMP_KERNEL': [[3], [4], [6], [3]], 'SPATIAL_STRIDES': [[1], [2], [2], [2]], 'SPATIAL_DILATIONS': [[1], [1], [1], [1]]}), 'X3D': CfgNode({'WIDTH_FACTOR': 1.0, 'DEPTH_FACTOR': 1.0, 'BOTTLENECK_FACTOR': 1.0, 'DIM_C5': 2048, 'DIM_C1': 12, 'SCALE_RES2': False, 'BN_LIN5': False, 'CHANNELWISE_3x3x3': True}), 'NONLOCAL': CfgNode({'LOCATION': [[[]], [[]], [[]], [[]]], 'GROUP': [[1], [1], [1], [1]], 'INSTANTIATION': 'dot_product', 'POOL': [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]]}), 'MODEL': CfgNode({'ARCH': 'uniformerv2', 'MODEL_NAME': 'Uniformerv2', 'NUM_CLASSES': 2, 'NUM_CLASSES_LIST': [400, 600, 700], 'LOSS_FUNC': 'cross_entropy', 'SINGLE_PATHWAY_ARCH': ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'], 'MULTI_PATHWAY_ARCH': ['slowfast'], 'DROPOUT_RATE': 0.5, 'DROPCONNECT_RATE': 0.0, 'FC_INIT_STD': 0.01, 'HEAD_ACT': 'softmax', 'USE_CHECKPOINT': True, 'CHECKPOINT_NUM': [24], 'EMA_DECAY': 0.9999, 'EMA_EPOCH': -1}), 'MVIT': CfgNode({'MODE': 'conv', 'CLS_EMBED_ON': True, 'PATCH_KERNEL': [3, 7, 7], 'PATCH_STRIDE': [2, 4, 4], 'PATCH_PADDING': [2, 4, 4], 'PATCH_2D': False, 'EMBED_DIM': 96, 'NUM_HEADS': 1, 'MLP_RATIO': 4.0, 'QKV_BIAS': True, 'DROPPATH_RATE': 0.1, 'DEPTH': 16, 'NORM': 'layernorm', 'DIM_MUL': [], 'HEAD_MUL': [], 'POOL_KV_STRIDE': [], 'POOL_Q_STRIDE': [], 'POOL_KVQ_KERNEL': None, 'ZERO_DECAY_POS_CLS': True, 'NORM_STEM': False, 'SEP_POS_EMBED': False, 'DROPOUT_RATE': 0.0}), 'SLOWFAST': CfgNode({'BETA_INV': 8, 'ALPHA': 8, 'FUSION_CONV_CHANNEL_RATIO': 2, 'FUSION_KERNEL_SZ': 5}), 'UNIFORMER': CfgNode({'EMBED_DIM': [64, 128, 320, 512], 'DEPTH': [3, 4, 8, 3], 'NUM_HEADS': [1, 2, 5, 8], 'HEAD_DIM': 64, 'MLP_RATIO': [4.0, 4.0, 4.0, 4.0], 'QKV_BIAS': True, 'QKV_SCALE': None, 'REPRESENTATION_SIZE': None, 'DROPOUT_RATE': 0, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'SPLIT': False, 'STAGE_TYPE': [0, 0, 1, 1], 'STD': False, 'KS': 5, 'DPE': True, 'RATIO': 1, 'MBCONV': False, 'ADD_MLP': True, 'TAU': 3, 'PRUNE_RATIO': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'TRADE_OFF': [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 'INIT_VALUE': 1.0}), 'VIP': CfgNode({'LAYERS': [4, 3, 8, 3], 'TRANSITIONS': [True, False, False, False], 'SEGMENT_DIM': [32, 16, 16, 16], 'T_STRIDE': 1, 'MLP_RATIOS': [3, 3, 3, 3], 'EMBED_DIMS': [192, 384, 384, 384], 'PATCH_SIZE': 7, 'QKV_SCALE': None, 'QKV_BIAS': True, 'ATTENTION_DROPOUT_RATE': 0, 'DROP_DEPTH_RATE': 0.1, 'PRETRAIN_NAME': None, 'ST_TYPE': 'st_skip'}), 'UNIFORMERV2': CfgNode({'BACKBONE': 'uniformerv2_l14_336', 'N_LAYERS': 4, 'N_DIM': 1024, 'N_HEAD': 16, 'MLP_FACTOR': 4.0, 'BACKBONE_DROP_PATH_RATE': 0.0, 'DROP_PATH_RATE': 0.0, 'MLP_DROPOUT': [0.5, 0.5, 0.5, 0.5], 'CLS_DROPOUT': 0.5, 'RETURN_LIST': [20, 21, 22, 23], 'DW_REDUCTION': 1.5, 'TEMPORAL_DOWNSAMPLE': False, 'NO_LMHRA': True, 'DOUBLE_LMHRA': True, 'PRETRAIN': '', 'DELETE_SPECIAL_HEAD': True, 'FROZEN': False}), 'DATA': CfgNode({'PATH_TO_DATA_DIR': '/workspace/data_paths', 'EXTRA_PATH_TO_DATA_DIR': '', 'PATH_TO_DATA_DIR_LIST': [''], 'PATH_LABEL_SEPARATOR': ',', 'PATH_PREFIX': '/workspace/RWF-2000-Cropped', 'PATH_PREFIX_LIST': [''], 'LABEL_PATH_TEMPLATE': 'somesomev1_rgb_{}_split.txt', 'IMAGE_TEMPLATE': '{:05d}.jpg', 'NUM_FRAMES': 64, 'SAMPLING_RATE': 16, 'TRAIN_PCA_EIGVAL': [0.225, 0.224, 0.229], 'TRAIN_PCA_EIGVEC': [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]], 'PATH_TO_PRELOAD_IMDB': '', 'MEAN': [0.45, 0.45, 0.45], 'INPUT_CHANNEL_NUM': [3], 'STD': [0.225, 0.225, 0.225], 'TRAIN_JITTER_SCALES': [384, 480], 'TRAIN_JITTER_SCALES_RELATIVE': [0.08, 1.0], 'TRAIN_JITTER_ASPECT_RELATIVE': [0.75, 1.3333], 'USE_OFFSET_SAMPLING': True, 'TRAIN_JITTER_MOTION_SHIFT': False, 'TRAIN_CROP_SIZE': 336, 'TEST_CROP_SIZE': 336, 'TARGET_FPS': 30, 'DECODING_BACKEND': 'pyav', 'INV_UNIFORM_SAMPLE': False, 'RANDOM_FLIP': True, 'MULTI_LABEL': False, 'ENSEMBLE_METHOD': 'sum', 'REVERSE_INPUT_CHANNEL': False, 'MC': False}), 'SOLVER': CfgNode({'BASE_LR': 1.5e-06, 'LR_POLICY': 'cosine', 'COSINE_END_LR': 1e-06, 'GAMMA': 0.1, 'STEP_SIZE': 1, 'STEPS': [], 'LRS': [], 'MAX_EPOCH': 51, 'MOMENTUM': 0.9, 'DAMPENING': 0.0, 'NESTEROV': True, 'WEIGHT_DECAY': 0.05, 'WARMUP_FACTOR': 0.1, 'WARMUP_EPOCHS': 1.0, 'WARMUP_START_LR': 1e-06, 'OPTIMIZING_METHOD': 'adamw', 'BASE_LR_SCALE_NUM_SHARDS': False, 'COSINE_AFTER_WARMUP': True, 'ZERO_WD_1D_PARAM': True, 'CLIP_GRADIENT': 20, 'BACKBONE_LR_RATIO': 0.1, 'SPECIAL_LIST': [], 'SPECIAL_RATIO': 1.0}), 'NUM_GPUS': 1, 'NUM_SHARDS': 1, 'SHARD_ID': 0, 'OUTPUT_DIR': './exp/RWF_exp', 'RNG_SEED': 7, 'LOG_PERIOD': 10, 'LOG_MODEL_INFO': True, 'DIST_BACKEND': 'nccl', 'BENCHMARK': CfgNode({'NUM_EPOCHS': 5, 'LOG_PERIOD': 100, 'SHUFFLE': True}), 'DATA_LOADER': CfgNode({'NUM_WORKERS': 2, 'PIN_MEMORY': True, 'ENABLE_MULTI_THREAD_DECODE': False}), 'DETECTION': CfgNode({'ENABLE': False, 'ALIGNED': True, 'SPATIAL_SCALE_FACTOR': 16, 'ROI_XFORM_RESOLUTION': 7}), 'AVA': CfgNode({'FRAME_DIR': '/mnt/fair-flash3-east/ava_trainval_frames.img/', 'FRAME_LIST_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'ANNOTATION_DIR': '/mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/', 'TRAIN_LISTS': ['train.csv'], 'TEST_LISTS': ['val.csv'], 'TRAIN_GT_BOX_LISTS': ['ava_train_v2.2.csv'], 'TRAIN_PREDICT_BOX_LISTS': [], 'TEST_PREDICT_BOX_LISTS': ['ava_val_predicted_boxes.csv'], 'DETECTION_SCORE_THRESH': 0.9, 'BGR': False, 'TRAIN_USE_COLOR_AUGMENTATION': False, 'TRAIN_PCA_JITTER_ONLY': True, 'TEST_FORCE_FLIP': False, 'FULL_TEST_ON_VAL': False, 'LABEL_MAP_FILE': 'ava_action_list_v2.2_for_activitynet_2019.pbtxt', 'EXCLUSION_FILE': 'ava_val_excluded_timestamps_v2.2.csv', 'GROUNDTRUTH_FILE': 'ava_val_v2.2.csv', 'IMG_PROC_BACKEND': 'cv2'}), 'MULTIGRID': CfgNode({'EPOCH_FACTOR': 1.5, 'SHORT_CYCLE': False, 'SHORT_CYCLE_FACTORS': [0.5, 0.7071067811865476], 'LONG_CYCLE': False, 'LONG_CYCLE_FACTORS': [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)], 'BN_BASE_SIZE': 8, 'EVAL_FREQ': 3, 'LONG_CYCLE_SAMPLING_RATE': 0, 'DEFAULT_B': 0, 'DEFAULT_T': 0, 'DEFAULT_S': 0}), 'TENSORBOARD': CfgNode({'ENABLE': True, 'PREDICTIONS_PATH': '', 'LOG_DIR': '', 'CLASS_NAMES_PATH': '', 'CATEGORIES_PATH': '', 'CONFUSION_MATRIX': CfgNode({'ENABLE': True, 'FIGSIZE': [10, 10], 'SUBSET_PATH': ''}), 'HISTOGRAM': CfgNode({'ENABLE': False, 'SUBSET_PATH': '', 'TOPK': 10, 'FIGSIZE': [8, 8]}), 'MODEL_VIS': CfgNode({'ENABLE': False, 'MODEL_WEIGHTS': False, 'ACTIVATIONS': False, 'INPUT_VIDEO': False, 'LAYER_LIST': [], 'TOPK_PREDS': 1, 'COLORMAP': 'Pastel2', 'GRAD_CAM': CfgNode({'ENABLE': True, 'LAYER_LIST': [], 'USE_TRUE_LABEL': False, 'COLORMAP': 'viridis'})}), 'WRONG_PRED_VIS': CfgNode({'ENABLE': False, 'TAG': 'Incorrectly classified videos.', 'SUBSET_PATH': ''})}), 'DEMO': CfgNode({'ENABLE': False, 'LABEL_FILE_PATH': '', 'WEBCAM': -1, 'INPUT_VIDEO': '', 'DISPLAY_WIDTH': 0, 'DISPLAY_HEIGHT': 0, 'DETECTRON2_CFG': 'COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml', 'DETECTRON2_WEIGHTS': 'detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl', 'DETECTRON2_THRESH': 0.9, 'BUFFER_SIZE': 0, 'OUTPUT_FILE': '', 'OUTPUT_FPS': -1, 'INPUT_FORMAT': 'BGR', 'CLIP_VIS_SIZE': 10, 'NUM_VIS_INSTANCES': 2, 'PREDS_BOXES': '', 'THREAD_ENABLE': False, 'NUM_CLIPS_SKIP': 0, 'GT_BOXES': '', 'STARTING_SECOND': 900, 'FPS': 30, 'VIS_MODE': 'thres', 'COMMON_CLASS_THRES': 0.7, 'UNCOMMON_CLASS_THRES': 0.3, 'COMMON_CLASS_NAMES': ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'], 'SLOWMO': 1})}) +[11/21 05:48:30][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:30][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:48:30][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:48:30][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:30][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:48:30][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:48:30][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:30][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:48:30][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:31][INFO] 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True +[11/21 05:48:31][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/21 05:48:31][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/21 05:48:31][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/21 05:48:31][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:48:31][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:48:31][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:48:32][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/21 05:48:32][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/21 05:48:32][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/21 05:48:32][INFO] uniformerv2_model.py: 374: Init center: True +[11/21 05:48:32][INFO] optimizer.py: 71: bn 0, non bn 132, zero 251 +[11/21 05:48:32][INFO] kinetics_sparse.py: 78: Constructing Kinetics train... +[11/21 05:48:32][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 1599) from /workspace/data_paths/train.csv +[11/21 05:48:32][INFO] kinetics_sparse.py: 78: Constructing Kinetics val... +[11/21 05:48:32][INFO] kinetics_sparse.py: 125: Constructing kinetics dataloader (size: 400) from /workspace/data_paths/val.csv +[11/21 05:48:32][INFO] tensorboard_vis.py: 54: To see logged results in Tensorboard, please launch using the command `tensorboard --port= --logdir ./exp/RWF_exp/runs-kinetics_sparse` +[11/21 05:48:32][INFO] train_net.py: 456: Start epoch: 1 +[11/21 05:49:00][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.66585, "dt_data": 0.00865, "dt_net": 2.65720, "epoch": "1/51", "eta": "1 day, 6:10:04", "gpu_mem": "33.25G", "iter": "10/799", "loss": 0.96252, "lr": 0.00000, "top1_err": 50.00000, "top5_err": 0.00000} +[11/21 05:49:27][INFO] logging.py: 99: json_stats: 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------------------------------------------------------------ +[11/21 06:30:13][INFO] meters.py: 956: NonFight: +[11/21 06:30:13][INFO] meters.py: 957: Precision: 89.13% +[11/21 06:30:13][INFO] meters.py: 958: Recall: 82.00% +[11/21 06:30:13][INFO] meters.py: 959: F1-Score: 85.42% +[11/21 06:30:13][INFO] meters.py: 960: Support: 200 +[11/21 06:30:13][INFO] meters.py: 956: Fight: +[11/21 06:30:13][INFO] meters.py: 957: Precision: 83.33% +[11/21 06:30:13][INFO] meters.py: 958: Recall: 90.00% +[11/21 06:30:13][INFO] meters.py: 959: F1-Score: 86.54% +[11/21 06:30:13][INFO] meters.py: 960: Support: 200 +[11/21 06:30:13][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/21 06:30:13][INFO] meters.py: 964: ------------------------------------------------------------ +[11/21 06:30:13][INFO] meters.py: 965: Precision: 86.23% +[11/21 06:30:13][INFO] meters.py: 966: Recall: 86.00% +[11/21 06:30:13][INFO] meters.py: 967: F1-Score: 85.98% +[11/21 06:30:13][INFO] meters.py: 970: +Confusion Matrix: 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------------------------------------------------------------ +[11/21 07:53:39][INFO] meters.py: 956: NonFight: +[11/21 07:53:39][INFO] meters.py: 957: Precision: 84.19% +[11/21 07:53:39][INFO] meters.py: 958: Recall: 90.50% +[11/21 07:53:39][INFO] meters.py: 959: F1-Score: 87.23% +[11/21 07:53:39][INFO] meters.py: 960: Support: 200 +[11/21 07:53:39][INFO] meters.py: 956: Fight: +[11/21 07:53:39][INFO] meters.py: 957: Precision: 89.73% +[11/21 07:53:39][INFO] meters.py: 958: Recall: 83.00% +[11/21 07:53:39][INFO] meters.py: 959: F1-Score: 86.23% +[11/21 07:53:39][INFO] meters.py: 960: Support: 200 +[11/21 07:53:39][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/21 07:53:39][INFO] meters.py: 964: ------------------------------------------------------------ +[11/21 07:53:39][INFO] meters.py: 965: Precision: 86.96% +[11/21 07:53:39][INFO] meters.py: 966: Recall: 86.75% +[11/21 07:53:39][INFO] meters.py: 967: F1-Score: 86.73% +[11/21 07:53:39][INFO] meters.py: 970: +Confusion Matrix: 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+[11/21 09:09:01][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.68388, "dt_data": 0.00857, "dt_net": 2.67530, "epoch": "5/51", "eta": "1 day, 3:26:14", "gpu_mem": "33.25G", "iter": "750/799", "loss": 0.32079, "lr": 0.00000, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 09:09:28][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.67831, "dt_data": 0.00857, "dt_net": 2.66974, "epoch": "5/51", "eta": "1 day, 3:22:23", "gpu_mem": "33.25G", "iter": "760/799", "loss": 0.02047, "lr": 0.00000, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 09:09:54][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.67851, "dt_data": 0.00826, "dt_net": 2.67026, "epoch": "5/51", "eta": "1 day, 3:22:03", "gpu_mem": "33.25G", "iter": "770/799", "loss": 0.50036, "lr": 0.00000, "top1_err": 25.00000, "top5_err": 0.00000} +[11/21 09:10:21][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.68121, "dt_data": 0.00863, "dt_net": 2.67258, "epoch": "5/51", "eta": "1 day, 3:23:16", "gpu_mem": "33.25G", "iter": "780/799", "loss": 0.01078, "lr": 0.00000, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 09:10:48][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.68427, "dt_data": 0.00861, "dt_net": 2.67566, "epoch": "5/51", "eta": "1 day, 3:24:41", "gpu_mem": "33.25G", "iter": "790/799", "loss": 0.37357, "lr": 0.00000, "top1_err": 25.00000, "top5_err": 0.00000} +[11/21 09:11:12][INFO] logging.py: 99: json_stats: {"RAM": "8.28/73.87G", "_type": "train_epoch", "dt": 0.00008, "dt_data": 0.00008, "dt_net": 2.67272, "epoch": "5/51", "eta": "0:00:02", "gpu_mem": "33.25G", "loss": 0.59241, "lr": 0.00000, "top1_err": 23.46683, "top5_err": 0.00000} +[11/21 09:11:12][INFO] train_net.py: 494: Epoch 4 takes 2142.08s. Epochs from 0 to 4 take 2143.17s in average and 2142.36s in median. +[11/21 09:11:12][INFO] train_net.py: 500: For epoch 4, each iteraction takes 2.68s in average. From epoch 0 to 4, each iteraction takes 2.68s in average. +[11/21 09:11:36][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "5/51", "eta": "0:05:35", "gpu_mem": "33.25G", "iter": "10/200", "time_diff": 1.76520, "top1_err": 25.00000, "top5_err": 0.00000} +[11/21 09:11:53][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "5/51", "eta": "0:05:18", "gpu_mem": "33.25G", "iter": "20/200", "time_diff": 1.76904, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 09:12:11][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "5/51", "eta": "0:05:00", "gpu_mem": "33.25G", "iter": "30/200", "time_diff": 1.77025, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 09:12:29][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "5/51", "eta": "0:04:43", "gpu_mem": "33.25G", "iter": "40/200", "time_diff": 1.77135, "top1_err": 50.00000, "top5_err": 0.00000} +[11/21 09:12:46][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "5/51", 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"0:00:17", "gpu_mem": "33.25G", "iter": "190/200", "time_diff": 1.77085, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 09:17:12][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "5/51", "eta": "0:00:00", "gpu_mem": "33.25G", "iter": "200/200", "time_diff": 1.77390, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 09:17:12][INFO] meters.py: 804: +============================================================ +[11/21 09:17:12][INFO] meters.py: 805: BEST VALIDATION EPOCH 5 +[11/21 09:17:12][INFO] meters.py: 943: +============================================================ +[11/21 09:17:12][INFO] meters.py: 944: CLASSIFICATION METRICS +[11/21 09:17:12][INFO] meters.py: 945: ============================================================ +[11/21 09:17:12][INFO] meters.py: 948: Overall Accuracy: 86.75% +[11/21 09:17:12][INFO] meters.py: 950: ROC-AUC Score: 0.9582 +[11/21 09:17:12][INFO] meters.py: 953: +Per-Class Metrics: +[11/21 09:17:12][INFO] meters.py: 954: ------------------------------------------------------------ +[11/21 09:17:12][INFO] meters.py: 956: NonFight: +[11/21 09:17:12][INFO] meters.py: 957: Precision: 95.09% +[11/21 09:17:12][INFO] meters.py: 958: Recall: 77.50% +[11/21 09:17:12][INFO] meters.py: 959: F1-Score: 85.40% +[11/21 09:17:12][INFO] meters.py: 960: Support: 200 +[11/21 09:17:12][INFO] meters.py: 956: Fight: +[11/21 09:17:12][INFO] meters.py: 957: Precision: 81.01% +[11/21 09:17:12][INFO] meters.py: 958: Recall: 96.00% +[11/21 09:17:12][INFO] meters.py: 959: F1-Score: 87.87% +[11/21 09:17:12][INFO] meters.py: 960: Support: 200 +[11/21 09:17:12][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/21 09:17:12][INFO] meters.py: 964: ------------------------------------------------------------ +[11/21 09:17:12][INFO] meters.py: 965: Precision: 88.05% +[11/21 09:17:12][INFO] meters.py: 966: Recall: 86.75% +[11/21 09:17:12][INFO] meters.py: 967: F1-Score: 86.64% +[11/21 09:17:12][INFO] meters.py: 970: +Confusion Matrix: 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Epochs from 0 to 7 take 2142.12s in average and 2142.22s in median. +[11/21 11:16:15][INFO] train_net.py: 500: For epoch 7, each iteraction takes 2.67s in average. 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------------------------------------------------------------ +[11/21 11:22:11][INFO] meters.py: 956: NonFight: +[11/21 11:22:11][INFO] meters.py: 957: Precision: 90.61% +[11/21 11:22:11][INFO] meters.py: 958: Recall: 82.00% +[11/21 11:22:11][INFO] meters.py: 959: F1-Score: 86.09% +[11/21 11:22:11][INFO] meters.py: 960: Support: 200 +[11/21 11:22:11][INFO] meters.py: 956: Fight: +[11/21 11:22:11][INFO] meters.py: 957: Precision: 83.56% +[11/21 11:22:11][INFO] meters.py: 958: Recall: 91.50% +[11/21 11:22:11][INFO] meters.py: 959: F1-Score: 87.35% +[11/21 11:22:11][INFO] meters.py: 960: Support: 200 +[11/21 11:22:11][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/21 11:22:11][INFO] meters.py: 964: ------------------------------------------------------------ +[11/21 11:22:11][INFO] meters.py: 965: Precision: 87.08% +[11/21 11:22:11][INFO] meters.py: 966: Recall: 86.75% +[11/21 11:22:11][INFO] meters.py: 967: F1-Score: 86.72% +[11/21 11:22:11][INFO] meters.py: 970: +Confusion Matrix: +[11/21 11:22:11][INFO] meters.py: 971: ------------------------------------------------------------ +[11/21 11:22:11][INFO] meters.py: 978: True\Pred NonFight Fight +[11/21 11:22:11][INFO] meters.py: 985: NonFight 164 36 +[11/21 11:22:11][INFO] meters.py: 985: Fight 17 183 +[11/21 11:22:11][INFO] meters.py: 987: ============================================================ + +[11/21 11:22:11][INFO] logging.py: 99: json_stats: {"RAM": "8.44/73.87G", "_type": "val_epoch", "epoch": "8/51", "gpu_mem": "33.25G", "min_top1_err": 13.25000, "min_top5_err": 0.00000, "time_diff": 0.00017, "top1_err": 13.25000, "top5_err": 0.00000, "val_accuracy": 86.75000, "val_macro_f1": 86.72004, "val_macro_precision": 87.08469, "val_macro_recall": 86.75000, "val_roc_auc": 0.95143} +[11/21 11:22:44][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.67349, "dt_data": 0.00855, "dt_net": 2.66494, "epoch": "9/51", "eta": "1 day, 1:30:26", "gpu_mem": "33.25G", "iter": "10/799", "loss": 0.40749, 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+[11/21 13:20:39][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.67073, "dt_data": 0.00815, "dt_net": 2.66258, "epoch": "11/51", "eta": "23:43:00", "gpu_mem": "33.25G", "iter": "790/799", "loss": 0.56963, "lr": 0.00000, "top1_err": 25.00000, "top5_err": 0.00000} +[11/21 13:21:03][INFO] logging.py: 99: json_stats: {"RAM": "8.22/73.87G", "_type": "train_epoch", "dt": 0.00007, "dt_data": 0.00007, "dt_net": 2.66552, "epoch": "11/51", "eta": "0:00:01", "gpu_mem": "33.25G", "loss": 0.53312, "lr": 0.00000, "top1_err": 19.64956, "top5_err": 0.00000} +[11/21 13:21:03][INFO] train_net.py: 494: Epoch 10 takes 2137.07s. Epochs from 0 to 10 take 2140.94s in average and 2142.05s in median. +[11/21 13:21:03][INFO] train_net.py: 500: For epoch 10, each iteraction takes 2.67s in average. 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"epoch": "11/51", "eta": "0:00:17", "gpu_mem": "33.25G", "iter": "190/200", "time_diff": 1.75803, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 13:27:01][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "11/51", "eta": "0:00:00", "gpu_mem": "33.25G", "iter": "200/200", "time_diff": 1.75818, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 13:27:01][INFO] meters.py: 804: +============================================================ +[11/21 13:27:01][INFO] meters.py: 805: BEST VALIDATION EPOCH 11 +[11/21 13:27:01][INFO] meters.py: 943: +============================================================ +[11/21 13:27:01][INFO] meters.py: 944: CLASSIFICATION METRICS +[11/21 13:27:01][INFO] meters.py: 945: ============================================================ +[11/21 13:27:01][INFO] meters.py: 948: Overall Accuracy: 88.25% +[11/21 13:27:01][INFO] meters.py: 950: ROC-AUC Score: 0.9627 +[11/21 13:27:01][INFO] meters.py: 953: +Per-Class Metrics: +[11/21 13:27:01][INFO] meters.py: 954: ------------------------------------------------------------ +[11/21 13:27:01][INFO] meters.py: 956: NonFight: +[11/21 13:27:01][INFO] meters.py: 957: Precision: 92.74% +[11/21 13:27:01][INFO] meters.py: 958: Recall: 83.00% +[11/21 13:27:01][INFO] meters.py: 959: F1-Score: 87.60% +[11/21 13:27:01][INFO] meters.py: 960: Support: 200 +[11/21 13:27:01][INFO] meters.py: 956: Fight: +[11/21 13:27:01][INFO] meters.py: 957: Precision: 84.62% +[11/21 13:27:01][INFO] meters.py: 958: Recall: 93.50% +[11/21 13:27:01][INFO] meters.py: 959: F1-Score: 88.84% +[11/21 13:27:01][INFO] meters.py: 960: Support: 200 +[11/21 13:27:01][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/21 13:27:01][INFO] meters.py: 964: ------------------------------------------------------------ +[11/21 13:27:01][INFO] meters.py: 965: Precision: 88.68% +[11/21 13:27:01][INFO] meters.py: 966: Recall: 88.25% +[11/21 13:27:01][INFO] meters.py: 967: F1-Score: 88.22% +[11/21 13:27:01][INFO] meters.py: 970: +Confusion Matrix: +[11/21 13:27:01][INFO] meters.py: 971: ------------------------------------------------------------ +[11/21 13:27:01][INFO] meters.py: 978: True\Pred NonFight Fight +[11/21 13:27:01][INFO] meters.py: 985: NonFight 166 34 +[11/21 13:27:01][INFO] meters.py: 985: Fight 13 187 +[11/21 13:27:01][INFO] meters.py: 987: ============================================================ + +[11/21 13:27:01][INFO] logging.py: 99: json_stats: {"RAM": "7.92/73.87G", "_type": "val_epoch", "epoch": "11/51", "gpu_mem": "33.25G", "min_top1_err": 11.75000, "min_top5_err": 0.00000, "time_diff": 0.00018, "top1_err": 11.75000, "top5_err": 0.00000, "val_accuracy": 88.25000, "val_macro_f1": 88.21752, "val_macro_precision": 88.67641, "val_macro_recall": 88.25000, "val_roc_auc": 0.96265} +[11/21 13:27:35][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.66902, "dt_data": 0.00818, "dt_net": 2.66083, "epoch": "12/51", "eta": "23:41:15", "gpu_mem": "33.25G", "iter": "10/799", 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"epoch": "13/51", "eta": "0:00:17", "gpu_mem": "33.25G", "iter": "190/200", "time_diff": 1.75865, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 14:50:11][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "13/51", "eta": "0:00:00", "gpu_mem": "33.25G", "iter": "200/200", "time_diff": 1.75470, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 14:50:11][INFO] meters.py: 804: +============================================================ +[11/21 14:50:11][INFO] meters.py: 805: BEST VALIDATION EPOCH 13 +[11/21 14:50:11][INFO] meters.py: 943: +============================================================ +[11/21 14:50:11][INFO] meters.py: 944: CLASSIFICATION METRICS +[11/21 14:50:11][INFO] meters.py: 945: ============================================================ +[11/21 14:50:11][INFO] meters.py: 948: Overall Accuracy: 88.25% +[11/21 14:50:11][INFO] meters.py: 950: ROC-AUC Score: 0.9598 +[11/21 14:50:11][INFO] meters.py: 953: +Per-Class Metrics: +[11/21 14:50:11][INFO] meters.py: 954: ------------------------------------------------------------ +[11/21 14:50:11][INFO] meters.py: 956: NonFight: +[11/21 14:50:11][INFO] meters.py: 957: Precision: 90.48% +[11/21 14:50:11][INFO] meters.py: 958: Recall: 85.50% +[11/21 14:50:11][INFO] meters.py: 959: F1-Score: 87.92% +[11/21 14:50:11][INFO] meters.py: 960: Support: 200 +[11/21 14:50:11][INFO] meters.py: 956: Fight: +[11/21 14:50:11][INFO] meters.py: 957: Precision: 86.26% +[11/21 14:50:11][INFO] meters.py: 958: Recall: 91.00% +[11/21 14:50:11][INFO] meters.py: 959: F1-Score: 88.56% +[11/21 14:50:11][INFO] meters.py: 960: Support: 200 +[11/21 14:50:11][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/21 14:50:11][INFO] meters.py: 964: ------------------------------------------------------------ +[11/21 14:50:11][INFO] meters.py: 965: Precision: 88.37% +[11/21 14:50:11][INFO] meters.py: 966: Recall: 88.25% +[11/21 14:50:11][INFO] meters.py: 967: F1-Score: 88.24% +[11/21 14:50:11][INFO] meters.py: 970: +Confusion Matrix: +[11/21 14:50:11][INFO] meters.py: 971: ------------------------------------------------------------ +[11/21 14:50:11][INFO] meters.py: 978: True\Pred NonFight Fight +[11/21 14:50:11][INFO] meters.py: 985: NonFight 171 29 +[11/21 14:50:11][INFO] meters.py: 985: Fight 18 182 +[11/21 14:50:11][INFO] meters.py: 987: ============================================================ + +[11/21 14:50:11][INFO] logging.py: 99: json_stats: {"RAM": "8.05/73.87G", "_type": "val_epoch", "epoch": "13/51", "gpu_mem": "33.25G", "min_top1_err": 11.75000, "min_top5_err": 0.00000, "time_diff": 0.00022, "top1_err": 11.75000, "top5_err": 0.00000, "val_accuracy": 88.25000, "val_macro_f1": 88.24111, "val_macro_precision": 88.36606, "val_macro_recall": 88.25000, "val_roc_auc": 0.95978} +[11/21 14:50:45][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.66898, "dt_data": 0.00824, "dt_net": 2.66074, "epoch": "14/51", "eta": "22:30:09", "gpu_mem": "33.25G", "iter": "10/799", 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Epochs from 0 to 15 take 2139.43s in average and 2138.71s in median. +[11/21 16:48:58][INFO] train_net.py: 500: For epoch 15, each iteraction takes 2.67s in average. 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"epoch": "16/51", "eta": "0:00:17", "gpu_mem": "33.25G", "iter": "190/200", "time_diff": 1.75774, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 16:54:55][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "16/51", "eta": "0:00:00", "gpu_mem": "33.25G", "iter": "200/200", "time_diff": 1.75671, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 16:54:55][INFO] meters.py: 804: +============================================================ +[11/21 16:54:55][INFO] meters.py: 805: BEST VALIDATION EPOCH 16 +[11/21 16:54:55][INFO] meters.py: 943: +============================================================ +[11/21 16:54:55][INFO] meters.py: 944: CLASSIFICATION METRICS +[11/21 16:54:55][INFO] meters.py: 945: ============================================================ +[11/21 16:54:55][INFO] meters.py: 948: Overall Accuracy: 88.50% +[11/21 16:54:55][INFO] meters.py: 950: ROC-AUC Score: 0.9598 +[11/21 16:54:55][INFO] meters.py: 953: +Per-Class Metrics: +[11/21 16:54:55][INFO] meters.py: 954: ------------------------------------------------------------ +[11/21 16:54:55][INFO] meters.py: 956: NonFight: +[11/21 16:54:55][INFO] meters.py: 957: Precision: 90.96% +[11/21 16:54:55][INFO] meters.py: 958: Recall: 85.50% +[11/21 16:54:55][INFO] meters.py: 959: F1-Score: 88.14% +[11/21 16:54:55][INFO] meters.py: 960: Support: 200 +[11/21 16:54:55][INFO] meters.py: 956: Fight: +[11/21 16:54:55][INFO] meters.py: 957: Precision: 86.32% +[11/21 16:54:55][INFO] meters.py: 958: Recall: 91.50% +[11/21 16:54:55][INFO] meters.py: 959: F1-Score: 88.83% +[11/21 16:54:55][INFO] meters.py: 960: Support: 200 +[11/21 16:54:55][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/21 16:54:55][INFO] meters.py: 964: ------------------------------------------------------------ +[11/21 16:54:55][INFO] meters.py: 965: Precision: 88.64% +[11/21 16:54:55][INFO] meters.py: 966: Recall: 88.50% +[11/21 16:54:55][INFO] meters.py: 967: F1-Score: 88.49% +[11/21 16:54:55][INFO] meters.py: 970: +Confusion Matrix: +[11/21 16:54:55][INFO] meters.py: 971: ------------------------------------------------------------ +[11/21 16:54:55][INFO] meters.py: 978: True\Pred NonFight Fight +[11/21 16:54:55][INFO] meters.py: 985: NonFight 171 29 +[11/21 16:54:55][INFO] meters.py: 985: Fight 17 183 +[11/21 16:54:55][INFO] meters.py: 987: ============================================================ + +[11/21 16:54:55][INFO] logging.py: 99: json_stats: {"RAM": "7.80/73.87G", "_type": "val_epoch", "epoch": "16/51", "gpu_mem": "33.25G", "min_top1_err": 11.50000, "min_top5_err": 0.00000, "time_diff": 0.00017, "top1_err": 11.50000, "top5_err": 0.00000, "val_accuracy": 88.50000, "val_macro_f1": 88.48964, "val_macro_precision": 88.63910, "val_macro_recall": 88.50000, "val_roc_auc": 0.95983} +[11/21 16:55:28][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.67023, "dt_data": 0.00858, "dt_net": 2.66165, "epoch": "17/51", "eta": "20:44:06", "gpu_mem": "33.25G", "iter": "10/799", 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Epochs from 0 to 16 take 2139.44s in average and 2139.64s in median. +[11/21 17:30:40][INFO] train_net.py: 500: For epoch 16, each iteraction takes 2.68s in average. 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"epoch": "17/51", "eta": "0:00:17", "gpu_mem": "33.25G", "iter": "190/200", "time_diff": 1.75910, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 17:36:38][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "17/51", "eta": "0:00:00", "gpu_mem": "33.25G", "iter": "200/200", "time_diff": 1.76199, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 17:36:38][INFO] meters.py: 804: +============================================================ +[11/21 17:36:38][INFO] meters.py: 805: BEST VALIDATION EPOCH 17 +[11/21 17:36:38][INFO] meters.py: 943: +============================================================ +[11/21 17:36:38][INFO] meters.py: 944: CLASSIFICATION METRICS +[11/21 17:36:38][INFO] meters.py: 945: ============================================================ +[11/21 17:36:38][INFO] meters.py: 948: Overall Accuracy: 89.00% +[11/21 17:36:38][INFO] meters.py: 950: ROC-AUC Score: 0.9589 +[11/21 17:36:38][INFO] meters.py: 953: +Per-Class Metrics: +[11/21 17:36:38][INFO] meters.py: 954: ------------------------------------------------------------ +[11/21 17:36:38][INFO] meters.py: 956: NonFight: +[11/21 17:36:38][INFO] meters.py: 957: Precision: 92.39% +[11/21 17:36:38][INFO] meters.py: 958: Recall: 85.00% +[11/21 17:36:38][INFO] meters.py: 959: F1-Score: 88.54% +[11/21 17:36:38][INFO] meters.py: 960: Support: 200 +[11/21 17:36:38][INFO] meters.py: 956: Fight: +[11/21 17:36:38][INFO] meters.py: 957: Precision: 86.11% +[11/21 17:36:38][INFO] meters.py: 958: Recall: 93.00% +[11/21 17:36:38][INFO] meters.py: 959: F1-Score: 89.42% +[11/21 17:36:38][INFO] meters.py: 960: Support: 200 +[11/21 17:36:38][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/21 17:36:38][INFO] meters.py: 964: ------------------------------------------------------------ +[11/21 17:36:38][INFO] meters.py: 965: Precision: 89.25% +[11/21 17:36:38][INFO] meters.py: 966: Recall: 89.00% +[11/21 17:36:38][INFO] meters.py: 967: F1-Score: 88.98% +[11/21 17:36:38][INFO] meters.py: 970: 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Epochs from 0 to 20 take 2138.99s in average and 2137.34s in median. +[11/21 20:17:04][INFO] train_net.py: 500: For epoch 20, each iteraction takes 2.68s in average. 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"epoch": "21/51", "eta": "0:00:17", "gpu_mem": "33.25G", "iter": "190/200", "time_diff": 1.76254, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 20:23:02][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "21/51", "eta": "0:00:00", "gpu_mem": "33.25G", "iter": "200/200", "time_diff": 1.76148, "top1_err": 0.00000, "top5_err": 0.00000} +[11/21 20:23:02][INFO] meters.py: 804: +============================================================ +[11/21 20:23:02][INFO] meters.py: 805: BEST VALIDATION EPOCH 21 +[11/21 20:23:02][INFO] meters.py: 943: +============================================================ +[11/21 20:23:02][INFO] meters.py: 944: CLASSIFICATION METRICS +[11/21 20:23:02][INFO] meters.py: 945: ============================================================ +[11/21 20:23:02][INFO] meters.py: 948: Overall Accuracy: 90.25% +[11/21 20:23:02][INFO] meters.py: 950: ROC-AUC Score: 0.9579 +[11/21 20:23:02][INFO] meters.py: 953: +Per-Class Metrics: +[11/21 20:23:02][INFO] meters.py: 954: ------------------------------------------------------------ +[11/21 20:23:02][INFO] meters.py: 956: NonFight: +[11/21 20:23:02][INFO] meters.py: 957: Precision: 90.86% +[11/21 20:23:02][INFO] meters.py: 958: Recall: 89.50% +[11/21 20:23:02][INFO] meters.py: 959: F1-Score: 90.18% +[11/21 20:23:02][INFO] meters.py: 960: Support: 200 +[11/21 20:23:02][INFO] meters.py: 956: Fight: +[11/21 20:23:02][INFO] meters.py: 957: Precision: 89.66% +[11/21 20:23:02][INFO] meters.py: 958: Recall: 91.00% +[11/21 20:23:02][INFO] meters.py: 959: F1-Score: 90.32% +[11/21 20:23:02][INFO] meters.py: 960: Support: 200 +[11/21 20:23:02][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/21 20:23:02][INFO] meters.py: 964: ------------------------------------------------------------ +[11/21 20:23:02][INFO] meters.py: 965: Precision: 90.26% +[11/21 20:23:02][INFO] meters.py: 966: Recall: 90.25% +[11/21 20:23:02][INFO] meters.py: 967: F1-Score: 90.25% +[11/21 20:23:02][INFO] meters.py: 970: +Confusion Matrix: +[11/21 20:23:02][INFO] meters.py: 971: ------------------------------------------------------------ +[11/21 20:23:02][INFO] meters.py: 978: True\Pred NonFight Fight +[11/21 20:23:02][INFO] meters.py: 985: NonFight 179 21 +[11/21 20:23:02][INFO] meters.py: 985: Fight 18 182 +[11/21 20:23:02][INFO] meters.py: 987: ============================================================ + +[11/21 20:23:02][INFO] logging.py: 99: json_stats: {"RAM": "7.74/73.87G", "_type": "val_epoch", "epoch": "21/51", "gpu_mem": "33.25G", "min_top1_err": 9.75000, "min_top5_err": 0.00000, "time_diff": 0.00020, "top1_err": 9.75000, "top5_err": 0.00000, "val_accuracy": 90.25000, "val_macro_f1": 90.24945, "val_macro_precision": 90.25906, "val_macro_recall": 90.25000, "val_roc_auc": 0.95790} +[11/21 20:23:35][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.67264, "dt_data": 0.00883, "dt_net": 2.66380, "epoch": "22/51", "eta": "17:47:16", "gpu_mem": "33.25G", "iter": "10/799", "loss": 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Epochs from 0 to 27 take 2138.92s in average and 2138.27s in median. +[11/22 01:08:23][INFO] train_net.py: 500: For epoch 27, each iteraction takes 2.68s in average. 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Epochs from 0 to 28 take 2138.88s in average and 2137.69s in median. +[11/22 01:49:58][INFO] train_net.py: 500: For epoch 28, each iteraction takes 2.68s in average. 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Epochs from 0 to 33 take 2138.55s in average and 2137.46s in median. +[11/22 05:17:51][INFO] train_net.py: 500: For epoch 33, each iteraction takes 2.67s in average. 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Epochs from 0 to 34 take 2138.49s in average and 2137.34s in median. +[11/22 05:59:25][INFO] train_net.py: 500: For epoch 34, each iteraction takes 2.67s in average. From epoch 0 to 34, each iteraction takes 2.68s in average. +[11/22 05:59:48][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "35/51", "eta": "0:05:33", "gpu_mem": "33.25G", "iter": "10/200", "time_diff": 1.75587, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 06:00:06][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "35/51", "eta": "0:05:16", "gpu_mem": "33.25G", "iter": "20/200", "time_diff": 1.75701, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 06:00:23][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "35/51", "eta": "0:04:58", "gpu_mem": "33.25G", "iter": "30/200", "time_diff": 1.75856, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 06:00:41][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "35/51", "eta": "0:04:41", "gpu_mem": "33.25G", "iter": "40/200", "time_diff": 1.76036, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 06:00:58][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": 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"epoch": "35/51", "eta": "0:00:17", "gpu_mem": "33.25G", "iter": "190/200", "time_diff": 1.76131, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 06:05:22][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "35/51", "eta": "0:00:00", "gpu_mem": "33.25G", "iter": "200/200", "time_diff": 1.76159, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 06:05:22][INFO] meters.py: 804: +============================================================ +[11/22 06:05:22][INFO] meters.py: 805: BEST VALIDATION EPOCH 35 +[11/22 06:05:22][INFO] meters.py: 943: +============================================================ +[11/22 06:05:22][INFO] meters.py: 944: CLASSIFICATION METRICS +[11/22 06:05:22][INFO] meters.py: 945: ============================================================ +[11/22 06:05:22][INFO] meters.py: 948: Overall Accuracy: 90.25% +[11/22 06:05:22][INFO] meters.py: 950: ROC-AUC Score: 0.9654 +[11/22 06:05:22][INFO] meters.py: 953: +Per-Class Metrics: +[11/22 06:05:22][INFO] meters.py: 954: ------------------------------------------------------------ +[11/22 06:05:22][INFO] meters.py: 956: NonFight: +[11/22 06:05:22][INFO] meters.py: 957: Precision: 91.28% +[11/22 06:05:22][INFO] meters.py: 958: Recall: 89.00% +[11/22 06:05:22][INFO] meters.py: 959: F1-Score: 90.13% +[11/22 06:05:22][INFO] meters.py: 960: Support: 200 +[11/22 06:05:22][INFO] meters.py: 956: Fight: +[11/22 06:05:22][INFO] meters.py: 957: Precision: 89.27% +[11/22 06:05:22][INFO] meters.py: 958: Recall: 91.50% +[11/22 06:05:22][INFO] meters.py: 959: F1-Score: 90.37% +[11/22 06:05:22][INFO] meters.py: 960: Support: 200 +[11/22 06:05:22][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/22 06:05:22][INFO] meters.py: 964: ------------------------------------------------------------ +[11/22 06:05:22][INFO] meters.py: 965: Precision: 90.28% +[11/22 06:05:22][INFO] meters.py: 966: Recall: 90.25% +[11/22 06:05:22][INFO] meters.py: 967: F1-Score: 90.25% +[11/22 06:05:22][INFO] meters.py: 970: +Confusion Matrix: +[11/22 06:05:22][INFO] meters.py: 971: ------------------------------------------------------------ +[11/22 06:05:22][INFO] meters.py: 978: True\Pred NonFight Fight +[11/22 06:05:22][INFO] meters.py: 985: NonFight 178 22 +[11/22 06:05:22][INFO] meters.py: 985: Fight 17 183 +[11/22 06:05:22][INFO] meters.py: 987: ============================================================ + +[11/22 06:05:22][INFO] logging.py: 99: json_stats: {"RAM": "7.95/73.87G", "_type": "val_epoch", "epoch": "35/51", "gpu_mem": "33.25G", "min_top1_err": 9.75000, "min_top5_err": 0.00000, "time_diff": 0.00017, "top1_err": 9.75000, "top5_err": 0.00000, "val_accuracy": 90.25000, "val_macro_f1": 90.24848, "val_macro_precision": 90.27517, "val_macro_recall": 90.25000, "val_roc_auc": 0.96535} +[11/22 06:05:58][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.66795, "dt_data": 0.00867, "dt_net": 2.65928, "epoch": "36/51", "eta": "9:28:00", "gpu_mem": "33.25G", "iter": "10/799", "loss": 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Epochs from 0 to 36 take 2138.47s in average and 2137.34s in median. +[11/22 07:22:43][INFO] train_net.py: 500: For epoch 36, each iteraction takes 2.67s in average. 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Epochs from 0 to 37 take 2138.42s in average and 2137.32s in median. +[11/22 08:04:18][INFO] train_net.py: 500: For epoch 37, each iteraction takes 2.67s in average. 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Epochs from 0 to 38 take 2138.41s in average and 2137.34s in median. +[11/22 08:45:54][INFO] train_net.py: 500: For epoch 38, each iteraction takes 2.68s in average. 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Epochs from 0 to 39 take 2138.40s in average and 2137.46s in median. +[11/22 09:27:30][INFO] train_net.py: 500: For epoch 39, each iteraction takes 2.68s in average. 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Epochs from 0 to 40 take 2138.51s in average and 2137.59s in median. +[11/22 10:09:11][INFO] train_net.py: 500: For epoch 40, each iteraction takes 2.68s in average. 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Epochs from 0 to 42 take 2138.43s in average and 2137.34s in median. +[11/22 11:32:22][INFO] train_net.py: 500: For epoch 42, each iteraction takes 2.67s in average. 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Epochs from 0 to 46 take 2138.32s in average and 2137.34s in median. +[11/22 14:18:42][INFO] train_net.py: 500: For epoch 46, each iteraction takes 2.67s in average. 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Epochs from 0 to 48 take 2138.37s in average and 2137.56s in median. +[11/22 15:41:57][INFO] train_net.py: 500: For epoch 48, each iteraction takes 2.68s in average. 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"epoch": "49/51", "eta": "0:00:17", "gpu_mem": "33.25G", "iter": "190/200", "time_diff": 1.76191, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 15:47:55][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "49/51", "eta": "0:00:00", "gpu_mem": "33.25G", "iter": "200/200", "time_diff": 1.75939, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 15:47:55][INFO] meters.py: 804: +============================================================ +[11/22 15:47:55][INFO] meters.py: 805: BEST VALIDATION EPOCH 49 +[11/22 15:47:55][INFO] meters.py: 943: +============================================================ +[11/22 15:47:55][INFO] meters.py: 944: CLASSIFICATION METRICS +[11/22 15:47:55][INFO] meters.py: 945: ============================================================ +[11/22 15:47:55][INFO] meters.py: 948: Overall Accuracy: 90.25% +[11/22 15:47:55][INFO] meters.py: 950: ROC-AUC Score: 0.9668 +[11/22 15:47:55][INFO] meters.py: 953: +Per-Class Metrics: +[11/22 15:47:55][INFO] meters.py: 954: ------------------------------------------------------------ +[11/22 15:47:55][INFO] meters.py: 956: NonFight: +[11/22 15:47:55][INFO] meters.py: 957: Precision: 90.86% +[11/22 15:47:55][INFO] meters.py: 958: Recall: 89.50% +[11/22 15:47:55][INFO] meters.py: 959: F1-Score: 90.18% +[11/22 15:47:55][INFO] meters.py: 960: Support: 200 +[11/22 15:47:55][INFO] meters.py: 956: Fight: +[11/22 15:47:55][INFO] meters.py: 957: Precision: 89.66% +[11/22 15:47:55][INFO] meters.py: 958: Recall: 91.00% +[11/22 15:47:55][INFO] meters.py: 959: F1-Score: 90.32% +[11/22 15:47:55][INFO] meters.py: 960: Support: 200 +[11/22 15:47:55][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/22 15:47:55][INFO] meters.py: 964: ------------------------------------------------------------ +[11/22 15:47:55][INFO] meters.py: 965: Precision: 90.26% +[11/22 15:47:55][INFO] meters.py: 966: Recall: 90.25% +[11/22 15:47:55][INFO] meters.py: 967: F1-Score: 90.25% +[11/22 15:47:55][INFO] meters.py: 970: +Confusion Matrix: +[11/22 15:47:55][INFO] meters.py: 971: ------------------------------------------------------------ +[11/22 15:47:55][INFO] meters.py: 978: True\Pred NonFight Fight +[11/22 15:47:55][INFO] meters.py: 985: NonFight 179 21 +[11/22 15:47:55][INFO] meters.py: 985: Fight 18 182 +[11/22 15:47:55][INFO] meters.py: 987: ============================================================ + +[11/22 15:47:55][INFO] logging.py: 99: json_stats: {"RAM": "8.50/73.87G", "_type": "val_epoch", "epoch": "49/51", "gpu_mem": "33.25G", "min_top1_err": 9.75000, "min_top5_err": 0.00000, "time_diff": 0.00017, "top1_err": 9.75000, "top5_err": 0.00000, "val_accuracy": 90.25000, "val_macro_f1": 90.24945, "val_macro_precision": 90.25906, "val_macro_recall": 90.25000, "val_roc_auc": 0.96680} +[11/22 15:48:27][INFO] logging.py: 99: json_stats: {"_type": "train_iter", "dt": 2.67384, "dt_data": 0.00843, "dt_net": 2.66540, "epoch": "50/51", "eta": "1:10:46", "gpu_mem": "33.25G", "iter": "10/799", "loss": 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Epochs from 0 to 49 take 2138.37s in average and 2137.58s in median. +[11/22 16:23:38][INFO] train_net.py: 500: For epoch 49, each iteraction takes 2.68s in average. 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json_stats: {"RAM": "7.70/73.87G", "_type": "train_epoch", "dt": 0.00007, "dt_data": 0.00007, "dt_net": 2.66327, "epoch": "51/51", "eta": "0:00:00", "gpu_mem": "33.25G", "loss": 0.31416, "lr": 0.00000, "top1_err": 9.57447, "top5_err": 0.00000} +[11/22 17:05:13][INFO] train_net.py: 494: Epoch 50 takes 2137.70s. Epochs from 0 to 50 take 2138.36s in average and 2137.59s in median. +[11/22 17:05:13][INFO] train_net.py: 500: For epoch 50, each iteraction takes 2.68s in average. From epoch 0 to 50, each iteraction takes 2.68s in average. +[11/22 17:05:36][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:05:33", "gpu_mem": "33.25G", "iter": "10/200", "time_diff": 1.75355, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:05:53][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:05:16", "gpu_mem": "33.25G", "iter": "20/200", "time_diff": 1.75877, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:06:11][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:04:59", "gpu_mem": "33.25G", "iter": "30/200", "time_diff": 1.76054, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:06:28][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:04:41", "gpu_mem": "33.25G", "iter": "40/200", "time_diff": 1.76029, "top1_err": 25.00000, "top5_err": 0.00000} +[11/22 17:06:46][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:04:23", "gpu_mem": "33.25G", "iter": "50/200", "time_diff": 1.75899, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:07:04][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:04:06", "gpu_mem": "33.25G", "iter": "60/200", "time_diff": 1.75871, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:07:21][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:03:48", "gpu_mem": "33.25G", "iter": "70/200", "time_diff": 1.75985, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:07:39][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:03:31", "gpu_mem": "33.25G", "iter": "80/200", "time_diff": 1.76339, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:07:56][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:03:13", "gpu_mem": "33.25G", "iter": "90/200", "time_diff": 1.76108, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 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"time_diff": 1.76381, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:09:42][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:01:28", "gpu_mem": "33.25G", "iter": "150/200", "time_diff": 1.76033, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:10:00][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:01:10", "gpu_mem": "33.25G", "iter": "160/200", "time_diff": 1.76191, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:10:17][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:00:52", "gpu_mem": "33.25G", "iter": "170/200", "time_diff": 1.76258, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:10:35][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:00:35", "gpu_mem": "33.25G", "iter": "180/200", "time_diff": 1.76209, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:10:53][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:00:17", "gpu_mem": "33.25G", "iter": "190/200", "time_diff": 1.76298, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:11:10][INFO] logging.py: 99: json_stats: {"_type": "val_iter", "epoch": "51/51", "eta": "0:00:00", "gpu_mem": "33.25G", "iter": "200/200", "time_diff": 1.76028, "top1_err": 0.00000, "top5_err": 0.00000} +[11/22 17:11:10][INFO] meters.py: 804: +============================================================ +[11/22 17:11:10][INFO] meters.py: 805: BEST VALIDATION EPOCH 51 +[11/22 17:11:10][INFO] meters.py: 943: +============================================================ +[11/22 17:11:10][INFO] meters.py: 944: CLASSIFICATION METRICS +[11/22 17:11:10][INFO] meters.py: 945: ============================================================ +[11/22 17:11:10][INFO] meters.py: 948: Overall Accuracy: 90.75% +[11/22 17:11:10][INFO] meters.py: 950: ROC-AUC Score: 0.9689 +[11/22 17:11:10][INFO] meters.py: 953: +Per-Class Metrics: +[11/22 17:11:10][INFO] meters.py: 954: ------------------------------------------------------------ +[11/22 17:11:10][INFO] meters.py: 956: NonFight: +[11/22 17:11:10][INFO] meters.py: 957: Precision: 92.67% +[11/22 17:11:10][INFO] meters.py: 958: Recall: 88.50% +[11/22 17:11:10][INFO] meters.py: 959: F1-Score: 90.54% +[11/22 17:11:10][INFO] meters.py: 960: Support: 200 +[11/22 17:11:10][INFO] meters.py: 956: Fight: +[11/22 17:11:10][INFO] meters.py: 957: Precision: 89.00% +[11/22 17:11:10][INFO] meters.py: 958: Recall: 93.00% +[11/22 17:11:10][INFO] meters.py: 959: F1-Score: 90.95% +[11/22 17:11:10][INFO] meters.py: 960: Support: 200 +[11/22 17:11:10][INFO] meters.py: 963: +Macro-Averaged Metrics: +[11/22 17:11:10][INFO] meters.py: 964: ------------------------------------------------------------ +[11/22 17:11:10][INFO] meters.py: 965: Precision: 90.83% +[11/22 17:11:10][INFO] meters.py: 966: Recall: 90.75% +[11/22 17:11:10][INFO] meters.py: 967: F1-Score: 90.75% +[11/22 17:11:10][INFO] meters.py: 970: +Confusion Matrix: +[11/22 17:11:10][INFO] meters.py: 971: ------------------------------------------------------------ +[11/22 17:11:10][INFO] meters.py: 978: True\Pred NonFight Fight +[11/22 17:11:10][INFO] meters.py: 985: NonFight 177 23 +[11/22 17:11:10][INFO] meters.py: 985: Fight 14 186 +[11/22 17:11:10][INFO] meters.py: 987: ============================================================ + +[11/22 17:11:10][INFO] logging.py: 99: json_stats: {"RAM": "8.08/73.87G", "_type": "val_epoch", "epoch": "51/51", "gpu_mem": "33.25G", "min_top1_err": 9.25000, "min_top5_err": 0.00000, "time_diff": 0.00016, "top1_err": 9.25000, "top5_err": 0.00000, "val_accuracy": 90.75000, "val_macro_f1": 90.74531, "val_macro_precision": 90.83269, "val_macro_recall": 90.75000, "val_roc_auc": 0.96895} +[11/22 17:11:15][INFO] test_net.py: 160: Test with config: +[11/22 17:11:15][INFO] test_net.py: 161: AUG: + AA_TYPE: rand-m7-n4-mstd0.5-inc1 + COLOR_JITTER: 0.4 + ENABLE: True + INTERPOLATION: bicubic + NUM_SAMPLE: 1 + RE_COUNT: 1 + RE_MODE: pixel + RE_PROB: 0.0 + RE_SPLIT: False +AVA: + ANNOTATION_DIR: /mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/ + BGR: False + DETECTION_SCORE_THRESH: 0.9 + EXCLUSION_FILE: ava_val_excluded_timestamps_v2.2.csv + FRAME_DIR: /mnt/fair-flash3-east/ava_trainval_frames.img/ + FRAME_LIST_DIR: /mnt/vol/gfsai-flash3-east/ai-group/users/haoqifan/ava/frame_list/ + FULL_TEST_ON_VAL: False + GROUNDTRUTH_FILE: ava_val_v2.2.csv + IMG_PROC_BACKEND: cv2 + LABEL_MAP_FILE: ava_action_list_v2.2_for_activitynet_2019.pbtxt + TEST_FORCE_FLIP: False + TEST_LISTS: ['val.csv'] + TEST_PREDICT_BOX_LISTS: ['ava_val_predicted_boxes.csv'] + TRAIN_GT_BOX_LISTS: ['ava_train_v2.2.csv'] + TRAIN_LISTS: ['train.csv'] + TRAIN_PCA_JITTER_ONLY: True + TRAIN_PREDICT_BOX_LISTS: [] + TRAIN_USE_COLOR_AUGMENTATION: False +BENCHMARK: + LOG_PERIOD: 100 + NUM_EPOCHS: 5 + SHUFFLE: True +BN: + NORM_TYPE: batchnorm + NUM_BATCHES_PRECISE: 200 + NUM_SPLITS: 1 + NUM_SYNC_DEVICES: 1 + USE_PRECISE_STATS: False + WEIGHT_DECAY: 0.0 +DATA: + DECODING_BACKEND: pyav + ENSEMBLE_METHOD: sum + EXTRA_PATH_TO_DATA_DIR: + IMAGE_TEMPLATE: {:05d}.jpg + INPUT_CHANNEL_NUM: [3] + INV_UNIFORM_SAMPLE: False + LABEL_PATH_TEMPLATE: somesomev1_rgb_{}_split.txt + MC: False + MEAN: [0.45, 0.45, 0.45] + MULTI_LABEL: False + NUM_FRAMES: 64 + PATH_LABEL_SEPARATOR: , + PATH_PREFIX: /workspace/RWF-2000-Cropped + PATH_PREFIX_LIST: [''] + PATH_TO_DATA_DIR: /workspace/data_paths + PATH_TO_DATA_DIR_LIST: [''] + PATH_TO_PRELOAD_IMDB: + RANDOM_FLIP: True + REVERSE_INPUT_CHANNEL: False + SAMPLING_RATE: 16 + STD: [0.225, 0.225, 0.225] + TARGET_FPS: 30 + TEST_CROP_SIZE: 336 + TRAIN_CROP_SIZE: 336 + TRAIN_JITTER_ASPECT_RELATIVE: [0.75, 1.3333] + TRAIN_JITTER_MOTION_SHIFT: False + TRAIN_JITTER_SCALES: [384, 480] + TRAIN_JITTER_SCALES_RELATIVE: [0.08, 1.0] + TRAIN_PCA_EIGVAL: [0.225, 0.224, 0.229] + TRAIN_PCA_EIGVEC: [[-0.5675, 0.7192, 0.4009], [-0.5808, -0.0045, -0.814], [-0.5836, -0.6948, 0.4203]] + USE_OFFSET_SAMPLING: True +DATA_LOADER: + ENABLE_MULTI_THREAD_DECODE: False + NUM_WORKERS: 2 + PIN_MEMORY: True +DEMO: + BUFFER_SIZE: 0 + CLIP_VIS_SIZE: 10 + COMMON_CLASS_NAMES: ['watch (a person)', 'talk to (e.g., self, a person, a group)', 'listen to (a person)', 'touch (an object)', 'carry/hold (an object)', 'walk', 'sit', 'lie/sleep', 'bend/bow (at the waist)'] + COMMON_CLASS_THRES: 0.7 + DETECTRON2_CFG: COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml + DETECTRON2_THRESH: 0.9 + DETECTRON2_WEIGHTS: detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl + DISPLAY_HEIGHT: 0 + DISPLAY_WIDTH: 0 + ENABLE: False + FPS: 30 + GT_BOXES: + INPUT_FORMAT: BGR + INPUT_VIDEO: + LABEL_FILE_PATH: + NUM_CLIPS_SKIP: 0 + NUM_VIS_INSTANCES: 2 + OUTPUT_FILE: + OUTPUT_FPS: -1 + PREDS_BOXES: + SLOWMO: 1 + STARTING_SECOND: 900 + THREAD_ENABLE: False + UNCOMMON_CLASS_THRES: 0.3 + VIS_MODE: thres + WEBCAM: -1 +DETECTION: + ALIGNED: True + ENABLE: False + ROI_XFORM_RESOLUTION: 7 + SPATIAL_SCALE_FACTOR: 16 +DIST_BACKEND: nccl +LOG_MODEL_INFO: True +LOG_PERIOD: 10 +MIXUP: + ALPHA: 0.8 + CUTMIX_ALPHA: 1.0 + ENABLE: False + LABEL_SMOOTH_VALUE: 0.1 + PROB: 1.0 + SWITCH_PROB: 0.5 +MODEL: + ARCH: uniformerv2 + CHECKPOINT_NUM: [24] + DROPCONNECT_RATE: 0.0 + DROPOUT_RATE: 0.5 + EMA_DECAY: 0.9999 + EMA_EPOCH: -1 + FC_INIT_STD: 0.01 + HEAD_ACT: softmax + LOSS_FUNC: cross_entropy + MODEL_NAME: Uniformerv2 + MULTI_PATHWAY_ARCH: ['slowfast'] + NUM_CLASSES: 2 + NUM_CLASSES_LIST: [400, 600, 700] + SINGLE_PATHWAY_ARCH: ['2d', 'c2d', 'i3d', 'slow', 'x3d', 'mvit', 'uniformer', 'uniformerv2'] + USE_CHECKPOINT: True +MULTIGRID: + BN_BASE_SIZE: 8 + DEFAULT_B: 0 + DEFAULT_S: 0 + DEFAULT_T: 0 + EPOCH_FACTOR: 1.5 + EVAL_FREQ: 3 + LONG_CYCLE: False + LONG_CYCLE_FACTORS: [(0.25, 0.7071067811865476), (0.5, 0.7071067811865476), (0.5, 1), (1, 1)] + LONG_CYCLE_SAMPLING_RATE: 0 + SHORT_CYCLE: False + SHORT_CYCLE_FACTORS: [0.5, 0.7071067811865476] +MVIT: + CLS_EMBED_ON: True + DEPTH: 16 + DIM_MUL: [] + DROPOUT_RATE: 0.0 + DROPPATH_RATE: 0.1 + EMBED_DIM: 96 + HEAD_MUL: [] + MLP_RATIO: 4.0 + MODE: conv + NORM: layernorm + NORM_STEM: False + NUM_HEADS: 1 + PATCH_2D: False + PATCH_KERNEL: [3, 7, 7] + PATCH_PADDING: [2, 4, 4] + PATCH_STRIDE: [2, 4, 4] + POOL_KVQ_KERNEL: None + POOL_KV_STRIDE: [] + POOL_Q_STRIDE: [] + QKV_BIAS: True + SEP_POS_EMBED: False + ZERO_DECAY_POS_CLS: True +NONLOCAL: + GROUP: [[1], [1], [1], [1]] + INSTANTIATION: dot_product + LOCATION: [[[]], [[]], [[]], [[]]] + POOL: [[[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]], [[1, 2, 2], [1, 2, 2]]] +NUM_GPUS: 1 +NUM_SHARDS: 1 +OUTPUT_DIR: ./exp/RWF_exp +RESNET: + DEPTH: 50 + INPLACE_RELU: True + NUM_BLOCK_TEMP_KERNEL: [[3], [4], [6], [3]] + NUM_GROUPS: 1 + SPATIAL_DILATIONS: [[1], [1], [1], [1]] + SPATIAL_STRIDES: [[1], [2], [2], [2]] + STRIDE_1X1: False + TRANS_FUNC: bottleneck_transform + WIDTH_PER_GROUP: 64 + ZERO_INIT_FINAL_BN: False +RNG_SEED: 7 +SHARD_ID: 0 +SLOWFAST: + ALPHA: 8 + BETA_INV: 8 + FUSION_CONV_CHANNEL_RATIO: 2 + FUSION_KERNEL_SZ: 5 +SOLVER: + BACKBONE_LR_RATIO: 0.1 + BASE_LR: 1.5e-06 + BASE_LR_SCALE_NUM_SHARDS: False + CLIP_GRADIENT: 20 + COSINE_AFTER_WARMUP: True + COSINE_END_LR: 1e-06 + DAMPENING: 0.0 + GAMMA: 0.1 + LRS: [] + LR_POLICY: cosine + MAX_EPOCH: 51 + MOMENTUM: 0.9 + NESTEROV: True + OPTIMIZING_METHOD: adamw + SPECIAL_LIST: [] + SPECIAL_RATIO: 1.0 + STEPS: [] + STEP_SIZE: 1 + WARMUP_EPOCHS: 1.0 + WARMUP_FACTOR: 0.1 + WARMUP_START_LR: 1e-06 + WEIGHT_DECAY: 0.05 + ZERO_WD_1D_PARAM: True +TENSORBOARD: + CATEGORIES_PATH: + CLASS_NAMES_PATH: + CONFUSION_MATRIX: + ENABLE: True + FIGSIZE: [10, 10] + SUBSET_PATH: + ENABLE: True + HISTOGRAM: + ENABLE: False + FIGSIZE: [8, 8] + SUBSET_PATH: + TOPK: 10 + LOG_DIR: + MODEL_VIS: + ACTIVATIONS: False + COLORMAP: Pastel2 + ENABLE: False + GRAD_CAM: + COLORMAP: viridis + ENABLE: True + LAYER_LIST: [] + USE_TRUE_LABEL: False + INPUT_VIDEO: False + LAYER_LIST: [] + MODEL_WEIGHTS: False + TOPK_PREDS: 1 + PREDICTIONS_PATH: + WRONG_PRED_VIS: + ENABLE: False + SUBSET_PATH: + TAG: Incorrectly classified videos. +TEST: + ADD_SOFTMAX: True + BATCH_SIZE: 6 + CHECKPOINT_FILE_PATH: + CHECKPOINT_TYPE: pytorch + DATASET: kinetics_sparse + ENABLE: True + INTERVAL: 2000 + NUM_ENSEMBLE_VIEWS: 1 + NUM_SPATIAL_CROPS: 1 + SAVE_RESULTS_PATH: + TEST_BEST: True +TRAIN: + AUTO_RESUME: True + BATCH_SIZE: 2 + CHECKPOINT_CLEAR_NAME_PATTERN: () + CHECKPOINT_EPOCH_RESET: False + CHECKPOINT_FILE_PATH: + CHECKPOINT_INFLATE: False + CHECKPOINT_PERIOD: 52 + CHECKPOINT_TYPE: pytorch + DATASET: kinetics_sparse + ENABLE: True + EVAL_PERIOD: 1 + SAVE_LATEST: True +UNIFORMER: + ADD_MLP: True + ATTENTION_DROPOUT_RATE: 0 + DEPTH: [3, 4, 8, 3] + DPE: True + DROPOUT_RATE: 0 + DROP_DEPTH_RATE: 0.1 + EMBED_DIM: [64, 128, 320, 512] + HEAD_DIM: 64 + INIT_VALUE: 1.0 + KS: 5 + MBCONV: False + MLP_RATIO: [4.0, 4.0, 4.0, 4.0] + NUM_HEADS: [1, 2, 5, 8] + PRETRAIN_NAME: None + PRUNE_RATIO: [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]] + QKV_BIAS: True + QKV_SCALE: None + RATIO: 1 + REPRESENTATION_SIZE: None + SPLIT: False + STAGE_TYPE: [0, 0, 1, 1] + STD: False + TAU: 3 + TRADE_OFF: [[], [], [1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 0.5, 0.5]] +UNIFORMERV2: + BACKBONE: uniformerv2_l14_336 + BACKBONE_DROP_PATH_RATE: 0.0 + CLS_DROPOUT: 0.5 + DELETE_SPECIAL_HEAD: True + DOUBLE_LMHRA: True + DROP_PATH_RATE: 0.0 + DW_REDUCTION: 1.5 + FROZEN: False + MLP_DROPOUT: [0.5, 0.5, 0.5, 0.5] + MLP_FACTOR: 4.0 + NO_LMHRA: True + N_DIM: 1024 + N_HEAD: 16 + N_LAYERS: 4 + PRETRAIN: + RETURN_LIST: [20, 21, 22, 23] + TEMPORAL_DOWNSAMPLE: False +VIP: + ATTENTION_DROPOUT_RATE: 0 + DROP_DEPTH_RATE: 0.1 + EMBED_DIMS: [192, 384, 384, 384] + LAYERS: [4, 3, 8, 3] + MLP_RATIOS: [3, 3, 3, 3] + PATCH_SIZE: 7 + PRETRAIN_NAME: None + QKV_BIAS: True + QKV_SCALE: None + SEGMENT_DIM: [32, 16, 16, 16] + ST_TYPE: st_skip + TRANSITIONS: [True, False, False, False] + T_STRIDE: 1 +X3D: + BN_LIN5: False + BOTTLENECK_FACTOR: 1.0 + CHANNELWISE_3x3x3: True + DEPTH_FACTOR: 1.0 + DIM_C1: 12 + DIM_C5: 2048 + SCALE_RES2: False + WIDTH_FACTOR: 1.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:15][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:15][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 72: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 76: No L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 77: Double L_MHRA: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 247: Use checkpoint: True +[11/22 17:11:16][INFO] uniformerv2_model.py: 248: Checkpoint number: [24] +[11/22 17:11:16][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 189: Drop path rate: 0.0 +[11/22 17:11:16][INFO] uniformerv2_model.py: 528: load pretrained weights +[11/22 17:11:17][INFO] uniformerv2_model.py: 393: Inflate: conv1.weight, torch.Size([1024, 3, 14, 14]) => torch.Size([1024, 3, 1, 14, 14]) +[11/22 17:11:17][INFO] uniformerv2_model.py: 374: Init center: True +[11/22 17:11:17][INFO] checkpoint.py: 224: Loading network weights from ./exp/RWF_exp/best.pyth. +[11/22 17:11:18][INFO] checkpoint.py: 357: Load strict==True +[11/22 17:11:18][INFO] kinetics_sparse.py: 78: Constructing Kinetics test...