RuntimeError: stack expects each tensor to be equal size, but got [3, 8, 224, 280] at entry 0 and [3, 8, 224, 398] at entry 1

when I use ava datasets to perform a test without trainning, some questions raised:

> Original Traceback (most recent call last):
File "/home/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop
data = fetcher.fetch(index)
File "/home/lanaconda3/envs/pytorch/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 47, in fetch
return self.collate_fn(data)
File "/home/PoseEstimation/SlowFast-master_test/slowfast/datasets/loader.py", line 56, in detection_collate
inputs, video_idx = default_collate(inputs), default_collate(video_idx)
File "/home/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/utils/data/_utils/collate.py", line 84, in default_collate
return [default_collate(samples) for samples in transposed]
File "/home/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/utils/data/_utils/collate.py", line 84, in
return [default_collate(samples) for samples in transposed]
File "/home/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/utils/data/_utils/collate.py", line 56, in default_collate
return torch.stack(batch, 0, out=out)
RuntimeError: stack expects each tensor to be equal size, but got [3, 8, 224, 280] at entry 0 and [3, 8, 224, 398] at entry 1

I used `SLOWFAST_32x2_R50_SHORT.yaml`to perform the test, this is my yaml:

> TRAIN:
ENABLE: False
DATASET: ava
BATCH_SIZE: 64
EVAL_PERIOD: 5
CHECKPOINT_PERIOD: 1
AUTO_RESUME: True
# CHECKPOINT_FILE_PATH: path to the pretrain checkpoint file.
CHECKPOINT_TYPE: caffe2
DATA:
NUM_FRAMES: 32
SAMPLING_RATE: 2
TRAIN_JITTER_SCALES: [256, 320]
TRAIN_CROP_SIZE: 224
TEST_CROP_SIZE: 224
INPUT_CHANNEL_NUM: [3, 3]
PATH_TO_DATA_DIR: '/home/PoseEstimation/data/ava'
DETECTION:
ENABLE: True
ALIGNED: True
AVA:
FRAME_DIR: '/home/PoseEstimation/data/ava/frames'
FRAME_LIST_DIR: '/home/PoseEstimation/data/ava/frame_lists'
ANNOTATION_DIR: '/home/PoseEstimation/data/ava/annotations'
DETECTION_SCORE_THRESH: 0.8
TRAIN_PREDICT_BOX_LISTS: [
"ava_train_v2.2.csv",
"person_box_67091280_iou90/ava_detection_train_boxes_and_labels_include_negative_v2.2.csv",
]
TEST_PREDICT_BOX_LISTS: ["person_box_67091280_iou90/ava_detection_val_boxes_and_labels.csv"]
SLOWFAST:
ALPHA: 4
BETA_INV: 8
FUSION_CONV_CHANNEL_RATIO: 2
FUSION_KERNEL_SZ: 7
RESNET:
ZERO_INIT_FINAL_BN: True
WIDTH_PER_GROUP: 64
NUM_GROUPS: 1
DEPTH: 50
TRANS_FUNC: bottleneck_transform
STRIDE_1X1: False
NUM_BLOCK_TEMP_KERNEL: [[3, 3], [4, 4], [6, 6], [3, 3]]
SPATIAL_DILATIONS: [[1, 1], [1, 1], [1, 1], [2, 2]]
SPATIAL_STRIDES: [[1, 1], [2, 2], [2, 2], [1, 1]]
NONLOCAL:
LOCATION: [[[], []], [[], []], [[], []], [[], []]]
GROUP: [[1, 1], [1, 1], [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]]]
BN:
USE_PRECISE_STATS: False
NUM_BATCHES_PRECISE: 200
SOLVER:
BASE_LR: 0.1
LR_POLICY: steps_with_relative_lrs
STEPS: [0, 10, 15, 20]
LRS: [1, 0.1, 0.01, 0.001]
MAX_EPOCH: 20
MOMENTUM: 0.9
WEIGHT_DECAY: 1e-7
WARMUP_EPOCHS: 5.0
WARMUP_START_LR: 0.000125
OPTIMIZING_METHOD: sgd
MODEL:
NUM_CLASSES: 80
ARCH: slowfast
MODEL_NAME: SlowFast
LOSS_FUNC: bce
DROPOUT_RATE: 0.5
HEAD_ACT: sigmoid
TEST:
ENABLE: True
DATASET: ava
BATCH_SIZE: 8
CHECKPOINT_FILE_PATH: '/home/PoseEstimation/SlowFast-master/configs/AVA/c2/SLOWFAST_32x2_R101_50_50test.pkl'
DATA_LOADER:
NUM_WORKERS: 2
PIN_MEMORY: True
NUM_GPUS: 1
NUM_SHARDS: 1
RNG_SEED: 0
OUTPUT_DIR: 'out_test'

Please give some advie~ Thank you in advance~