First of all，thanks for your great work! My question is shown in the title, and the specific error message is as follows:

[> ] 777/19881, 1.0 task/s, elapsed: 769s, ETA: 18903sTraceback (most recent call last): File "tools/test.py", line 364, in main() File "tools/test.py", line 349, in main outputs = inference_pytorch(args, cfg, distributed, data_loader) File "tools/test.py", line 167, in inference_pytorch args.gpu_collect) File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/mmcv/engine/test.py", line 70, in multi_gpu_test for i, data in enumerate(data_loader): File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 530, in next data = self._next_data() File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1224, in _next_data return self._process_data(data) File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1250, in _process_data data.reraise() File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/torch/_utils.py", line 457, in reraise raise exception decord._ffi.base.DECORDError: Caught DECORDError in DataLoader worker process 0. Original Traceback (most recent call last): File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop data = fetcher.fetch(index) File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 49, in data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/lzh/2022/tjq/adapt-image-models/mmaction/datasets/base.py", line 285, in getitem return self.prepare_test_frames(idx) File "/home/lzh/2022/tjq/adapt-image-models/mmaction/datasets/base.py", line 276, in prepare_test_frames return self.pipeline(results) File "/home/lzh/2022/tjq/adapt-image-models/mmaction/datasets/pipelines/compose.py", line 41, in call data = t(data) File "/home/lzh/2022/tjq/adapt-image-models/mmaction/datasets/pipelines/loading.py", line 965, in call container = decord.VideoReader(file_obj, num_threads=self.num_threads) File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/decord/video_reader.py", line 42, in init ba, ctx.device_type, ctx.device_id, width, height, num_threads, 2) File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/decord/_ffi/_ctypes/function.py", line 175, in call ctypes.byref(ret_val), ctypes.byref(ret_tcode))) File "/home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/decord/_ffi/base.py", line 63, in check_call raise DECORDError(py_str(_LIB.DECORDGetLastError())) decord._ffi.base.DECORDError: [15:44:17] /io/decord/src/video/video_reader.cc:125: Check failed: st_nb >= 0 (-1381258232 vs. 0) ERROR cannot find video stream with wanted index: -1

Stack trace returned 10 entries: [bt] (0) /home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/decord/libdecord.so(dmlc::StackTrace(unsigned long)+0x50) [0x7f4606a29990] [bt] (1) /home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/decord/libdecord.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x1d) [0x7f4606a2aa7d] [bt] (2) /home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/decord/libdecord.so(decord::VideoReader::SetVideoStream(int)+0xee) [0x7f4606a7a6ae] [bt] (3) /home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/decord/libdecord.so(decord::VideoReader::VideoReader(std::string, DLContext, int, int, int, int)+0x3cd) [0x7f4606a7b28d] [bt] (4) /home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/decord/libdecord.so(+0x6a039) [0x7f4606a6a039] [bt] (5) /home/lzh/anaconda3/envs/AIM/lib/python3.7/site-packages/decord/libdecord.so(DECORDFuncCall+0x52) [0x7f4606a26572] [bt] (6) /home/lzh/anaconda3/envs/AIM/lib/python3.7/lib-dynload/../../libffi.so.7(+0x69dd) [0x7f465f9679dd] [bt] (7) /home/lzh/anaconda3/envs/AIM/lib/python3.7/lib-dynload/../../libffi.so.7(+0x6067) [0x7f465f967067] [bt] (8) /home/lzh/anaconda3/envs/AIM/lib/python3.7/lib-dynload/_ctypes.cpython-37m-x86_64-linux-gnu.so(_ctypes_callproc+0x2e7) [0x7f465c9ec437] [bt] (9) /home/lzh/anaconda3/envs/AIM/lib/python3.7/lib-dynload/_ctypes.cpython-37m-x86_64-linux-gnu.so(+0x12ea4) [0x7f465c9ecea4]

The k400 dataset in my project is located in https://github.com/cvdfoundation/kinetics-dataset I downloaded it from, but I ensured that none of my videos were damaged. Is there an error in my configuration file? My configuration file is as follows：

model = dict( backbone=dict(drop_path_rate=0.2, adapter_scale=0.5, num_frames=8), cls_head=dict(num_classes=400), test_cfg=dict(max_testing_views=4))

dataset settings

dataset_type = 'VideoDataset'

data_root = 'data/kinetics400/train_256'

data_root_val = 'data/kinetics400/val_256'

ann_file_train = 'data/kinetics400/train_video_list.txt'

ann_file_val = 'data/kinetics400/val_video_list.txt'

ann_file_test = 'data/kinetics400/val_video_list.txt'

data_root = '/data/K400/k400/train' data_root_val = '/data/K400/k400/' ann_file_train = '/data/K400/kinetics400/kinetics400_train_list.txt' ann_file_val = '/data/K400/kinetics400/kinetics400_val_list.txt' ann_file_test = '/data/K400/kinetics400/kinetics400_test_list.txt' img_norm_cfg = dict( mean=[122.769, 116.74, 104.04], std=[68.493, 66.63, 70.321], to_bgr=False) train_pipeline = [ dict(type='DecordInit'), dict(type='SampleFrames', clip_len=8, frame_interval=16, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='Normalize', img_norm_cfg), dict(type='FormatShape', input_format='NCTHW'), dict(type='Collect', keys=['imgs', 'label'], meta_keys=[]), dict(type='ToTensor', keys=['imgs', 'label']) ] val_pipeline = [ dict(type='DecordInit'), dict( type='SampleFrames', clip_len=8, frame_interval=16, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='Flip', flip_ratio=0), dict(type='Normalize', img_norm_cfg), dict(type='FormatShape', input_format='NCTHW'), dict(type='Collect', keys=['imgs', 'label'], meta_keys=[]), dict(type='ToTensor', keys=['imgs']) ] test_pipeline = [ dict(type='DecordInit'), dict( type='SampleFrames', clip_len=8, frame_interval=16, num_clips=3, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 224)), dict(type='CenterCrop', crop_size=224), dict(type='Flip', flip_ratio=0), dict(type='Normalize', img_norm_cfg), dict(type='FormatShape', input_format='NCTHW'), dict(type='Collect', keys=['imgs', 'label'], meta_keys=[]), dict(type='ToTensor', keys=['imgs']) ] data** = dict( videos_per_gpu=8, workers_per_gpu=2, val_dataloader=dict( videos_per_gpu=1, workers_per_gpu=1 ), test_dataloader=dict( videos_per_gpu=1, workers_per_gpu=1 ), train=dict( type=dataset_type, ann_file=ann_file_train, data_prefix=data_root, pipeline=train_pipeline), val=dict( type=dataset_type, ann_file=ann_file_val, data_prefix=data_root_val, pipeline=val_pipeline), test=dict( type=dataset_type, ann_file=ann_file_test, data_prefix=data_root_val, pipeline=test_pipeline)) evaluation = dict( interval=5, metrics=['top_k_accuracy', 'mean_class_accuracy'])

I think it's a problem with the decord version, but when I tried to replace it with decord=0.6.0/0.40/0.4.1, the same error was reported

So, I have no choice but to bother you. Looking forward to your reply, thank you very much!

taoyang1122 / adapt-image-models

Encoding error while loading val data on k400 #33