Error when run demo with pretrained model mvit_b_16_conv

I run with command: python3 tools/run_net.py --cfg configs/Kinetics/DemoMvit_B_16x4_Conv.yaml \
DATA.PATH_TO_DATA_DIR /mnt/Ubuntu/Dataset/valid_result \
TEST.CHECKPOINT_FILE_PATH model/K400_MVIT_B_16x4_CONV.pyth \
TRAIN.ENABLE False NUM_GPUS 1

and my config file

TRAIN:
ENABLE: False
DATASET: kinetics
BATCH_SIZE: 16
EVAL_PERIOD: 10
CHECKPOINT_PERIOD: 10
AUTO_RESUME: True
DATA:
USE_OFFSET_SAMPLING: True
DECODING_BACKEND: torchvision
NUM_FRAMES: 16
SAMPLING_RATE: 4
TRAIN_JITTER_SCALES: [256, 320]
TRAIN_CROP_SIZE: 224
TEST_CROP_SIZE: 224
INPUT_CHANNEL_NUM: [3]
# PATH_TO_DATA_DIR: path-to-k400-dir
TRAIN_JITTER_SCALES_RELATIVE: [0.08, 1.0]
TRAIN_JITTER_ASPECT_RELATIVE: [0.75, 1.3333]
MVIT:
ZERO_DECAY_POS_CLS: False
SEP_POS_EMBED: True
DEPTH: 16
NUM_HEADS: 1
EMBED_DIM: 96
PATCH_KERNEL: (3, 7, 7)
PATCH_STRIDE: (2, 4, 4)
PATCH_PADDING: (1, 3, 3)
MLP_RATIO: 4.0
QKV_BIAS: True
DROPPATH_RATE: 0.2
NORM: "layernorm"
MODE: "conv"
CLS_EMBED_ON: True
DIM_MUL: [[1, 2.0], [3, 2.0], [14, 2.0]]
HEAD_MUL: [[1, 2.0], [3, 2.0], [14, 2.0]]
POOL_KVQ_KERNEL: [3, 3, 3]
POOL_KV_STRIDE_ADAPTIVE: [1, 8, 8]
POOL_Q_STRIDE: [[1, 1, 2, 2], [3, 1, 2, 2], [14, 1, 2, 2]]
DROPOUT_RATE: 0.0
AUG:
NUM_SAMPLE: 2
ENABLE: True
COLOR_JITTER: 0.4
AA_TYPE: rand-m7-n4-mstd0.5-inc1
INTERPOLATION: bicubic
RE_PROB: 0.25
RE_MODE: pixel
RE_COUNT: 1
RE_SPLIT: False
MIXUP:
ENABLE: True
ALPHA: 0.8
CUTMIX_ALPHA: 1.0
PROB: 1.0
SWITCH_PROB: 0.5
LABEL_SMOOTH_VALUE: 0.1
BN:
USE_PRECISE_STATS: False
NUM_BATCHES_PRECISE: 200
SOLVER:
ZERO_WD_1D_PARAM: True
CLIP_GRAD_L2NORM: 1.0
BASE_LR_SCALE_NUM_SHARDS: True
BASE_LR: 0.0001
COSINE_AFTER_WARMUP: True
COSINE_END_LR: 1e-6
WARMUP_START_LR: 1e-6
WARMUP_EPOCHS: 30.0
LR_POLICY: cosine
MAX_EPOCH: 200
MOMENTUM: 0.9
WEIGHT_DECAY: 0.05
OPTIMIZING_METHOD: adamw
MODEL:
NUM_CLASSES: 400
ARCH: mvit
MODEL_NAME: MViT
LOSS_FUNC: soft_cross_entropy
DROPOUT_RATE: 0.5
TEST:
ENABLE: False
DATASET: kinetics
BATCH_SIZE: 64
NUM_SPATIAL_CROPS: 1
DATA_LOADER:
NUM_WORKERS: 8
PIN_MEMORY: True
DEMO:
ENABLE: True
LABEL_FILE_PATH: model/kinetics_classnames.json # Path to json file providing class_name - id mapping.
INPUT_VIDEO: /mnt/Ubuntu/Dataset/valid_result/countingmoney_kEtlPacwlHw.avi # Path to input video file.
OUTPUT_FILE: /mnt/Ubuntu/Dataset/valid_result/countingmoney_kEtlPacwlHw_result.avi #Path to output video file to write results to.
# Leave an empty string if you would like to display results to a window.
THREAD_ENABLE: False # Run video reader/writer in the background with multi-threading.
# NUM_VIS_INSTANCES: 1 # Number of CPU(s)/processes use to run video visualizer.
# NUM_CLIPS_SKIP: 4 # Number of clips to skip prediction/visualization
# # (mostly to smoothen/improve display quality with wecam input).
NUM_GPUS: 8
NUM_SHARDS: 1
RNG_SEED: 0
OUTPUT_DIR: .

I get this error:
0it [00:04, ?it/s]
Traceback (most recent call last):
File "tools/run_net.py", line 46, in
main()
File "tools/run_net.py", line 42, in main
demo(cfg)
File "/mnt/Ubuntu/PoseEstimate/FacebookReasearch/SlowFast/tools/demo_net.py", line 114, in demo
for task in tqdm.tqdm(run_demo(cfg, frame_provider)):
File "/mnt/Ubuntu/PoseEstimate/FacebookReasearch/SlowFast/venv/lib/python3.8/site-packages/tqdm/std.py", line 1185, in __iter__
for obj in iterable:
File "/mnt/Ubuntu/PoseEstimate/FacebookReasearch/SlowFast/tools/demo_net.py", line 79, in run_demo
model.put(task)
File "/mnt/Ubuntu/PoseEstimate/FacebookReasearch/SlowFast/slowfast/visualization/predictor.py", line 142, in put
task = self.predictor(task)
File "/mnt/Ubuntu/PoseEstimate/FacebookReasearch/SlowFast/slowfast/visualization/predictor.py", line 104, in __call__
preds = self.model(inputs, bboxes)
File "/mnt/Ubuntu/PoseEstimate/FacebookReasearch/SlowFast/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1053, in _call_impl
return forward_call(*input, **kwargs)
TypeError: forward() takes 2 positional arguments but 3 were given

Can anyone help me fix this? Thank you very much!