Error when trying to train X3D model using AVA dataset

Hello,

I am getting this error when I am trying to train a X3D model using AVA dataset.

File "tools/run_net.py", line 45, in
main()
File "tools/run_net.py", line 26, in main
launch_job(cfg=cfg, init_method=args.init_method, func=train)
File "/mnt/batch/tasks/shared/LS_root/mounts/clusters/daemon/code/Users/saicharithreddy.pasula/SCOUT-%20Behavior%20Anomaly%20Detection/trainer/SlowFast/slowfast/utils/misc.py", line 296, in launch_job
torch.multiprocessing.spawn(
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torch/multiprocessing/spawn.py", line 240, in spawn
return start_processes(fn, args, nprocs, join, daemon, start_method='spawn')
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torch/multiprocessing/spawn.py", line 198, in start_processes
while not context.join():
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torch/multiprocessing/spawn.py", line 160, in join
raise ProcessRaisedException(msg, error_index, failed_process.pid)
torch.multiprocessing.spawn.ProcessRaisedException:

-- Process 0 terminated with the following error:
Traceback (most recent call last):
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torch/multiprocessing/spawn.py", line 69, in _wrap
fn(i, *args)
File "/mnt/batch/tasks/shared/LS_root/mounts/clusters/daemon/code/Users/saicharithreddy.pasula/SCOUT-%20Behavior%20Anomaly%20Detection/trainer/SlowFast/slowfast/utils/multiprocessing.py", line 60, in run
ret = func(cfg)
File "/mnt/batch/tasks/shared/LS_root/mounts/clusters/daemon/code/Users/saicharithreddy.pasula/SCOUT-%20Behavior%20Anomaly%20Detection/trainer/SlowFast/tools/train_net.py", line 711, in train
train_epoch(
File "/mnt/batch/tasks/shared/LS_root/mounts/clusters/daemon/code/Users/saicharithreddy.pasula/SCOUT-%20Behavior%20Anomaly%20Detection/trainer/SlowFast/tools/train_net.py", line 156, in train_epoch
loss = loss_fun(preds, labels)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torch/nn/modules/loss.py", line 1164, in forward
return F.cross_entropy(input, target, weight=self.weight,
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torch/nn/functional.py", line 3014, in cross_entropy
return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index, label_smoothing)
TypeError: cross_entropy_loss(): argument 'input' (position 1) must be Tensor, not list

It looks like the model is returning the predictions as a python list instead of a pytorch tensor. Did anyone encounter this error?

P.S: The config I am using is

TRAIN:
ENABLE: True
DATASET: ava
BATCH_SIZE: 16
EVAL_PERIOD: 1
CHECKPOINT_PERIOD: 1
AUTO_RESUME: True
CHECKPOINT_FILE_PATH: 'checkpoints/x3d_l.pyth'
CHECKPOINT_TYPE: pytorch
CHECKPOINT_EPOCH_RESET: True
CHECKPOINT_INFLATE: False
MIXED_PRECISION: False

DATA:
NUM_FRAMES: 15
SAMPLING_RATE: 6
TRAIN_JITTER_SCALES: [256, 320]
TRAIN_CROP_SIZE: 224
TEST_CROP_SIZE: 224
INPUT_CHANNEL_NUM: [3]
DECODING_BACKEND: torchvision

DETECTION:
ENABLE: True
ALIGNED: True

AVA:
FRAME_DIR: ‘path/frames'
FRAME_LIST_DIR: ‘path/frames_list'
ANNOTATION_DIR: ‘path/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"]

X3D:
WIDTH_FACTOR: 2.0
DEPTH_FACTOR: 2.2
BOTTLENECK_FACTOR: 2.25
DIM_C5: 2048
DIM_C1: 12

RESNET:
ZERO_INIT_FINAL_BN: True
TRANS_FUNC: x3d_transform
STRIDE_1X1: False

BN:
USE_PRECISE_STATS: False
NUM_BATCHES_PRECISE: 200

SOLVER:
BASE_LR: 0.1
BASE_LR_SCALE_NUM_SHARDS: True
LR_POLICY: steps_with_relative_lrs
STEPS: [0, 10, 15, 20]
LRS: [1, 0.1, 0.01, 0.001]
MAX_EPOCH: 1
WEIGHT_DECAY: 1e-7
WARMUP_EPOCHS: 5.0
WARMUP_START_LR: 0.000125
OPTIMIZING_METHOD: sgd

MODEL:
NUM_CLASSES: 7
ARCH: x3d
MODEL_NAME: X3D
LOSS_FUNC: cross_entropy
DROPOUT_RATE: 0.5
HEAD_ACT: sigmoid

TEST:
ENABLE: False
DATASET: ava
BATCH_SIZE: 1

DATA_LOADER:
NUM_WORKERS: 5
PIN_MEMORY: True

NUM_GPUS: 2
NUM_SHARDS: 1
RNG_SEED: 0
OUTPUT_DIR: ./x3d