Demo run_net.py code problem

Hi, yesterday I downloaded SlowFast and now I am trying to run demo on my video, using the following command:
python tools/run_net.py --cfg demo/AVA/SLOWFAST_32x2_R101_50_50_MYTEST.yaml
I am running it on a video, following the instructions in "getting_started.md" (I changed _C.DEMO.DATA_SOURCE="" instead of 0, and edited yaml file).
However i run into the following error:

> Traceback (most recent call last):
> File "tools/run_net.py", line 37, in
> main()
> File "tools/run_net.py", line 19, in main
> cfg = load_config(args)
> File "/media/st4Tb/fbtools/slowfast/slowfast/utils/parser.py", line 78, in load_config
> cfg.merge_from_file(args.cfg_file)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/fvcore/common/config.py", line 109, in merge_from_file
> self.merge_from_other_cfg(loaded_cfg)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/fvcore/common/config.py", line 120, in merge_from_other_cfg
> return super().merge_from_other_cfg(cfg_other)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/yacs/config.py", line 217, in merge_from_other_cfg
> _merge_a_into_b(cfg_other, self, self, [])
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/yacs/config.py", line 464, in _merge_a_into_b
> _merge_a_into_b(v, b[k], root, key_list + [k])
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/yacs/config.py", line 477, in _merge_a_into_b
> raise KeyError("Non-existent config key: {}".format(full_key))
> KeyError: 'Non-existent config key: BN.MOMENTUM'

When I remove the entire BN section of yaml file, I get another error, connected with tensor sizes in the model:
Warnings:

> /media/st4Tb/fbtools/slowfast/slowfast/models/head_helper.py:111: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
> assert out.shape[2] == 1
> /media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/detectron2/layers/roi_align.py:93: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!

and finally the error:

> Traceback (most recent call last):
> File "tools/run_net.py", line 37, in
> main()
> File "tools/run_net.py", line 30, in main
> launch_job(cfg=cfg, init_method=args.init_method, func=demo)
> File "/media/st4Tb/fbtools/slowfast/slowfast/utils/misc.py", line 282, in launch_job
> func(cfg=cfg)
> File "/media/st4Tb/fbtools/slowfast/tools/demo_net.py", line 103, in demo
> misc.log_model_info(model, cfg)
> File "/media/st4Tb/fbtools/slowfast/slowfast/utils/misc.py", line 160, in log_model_info
> get_model_stats(model, cfg, "flop", use_train_input)
> File "/media/st4Tb/fbtools/slowfast/slowfast/utils/misc.py", line 138, in get_model_stats
> count_dict, _ = model_stats_fun(model, inputs)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/fvcore/nn/flop_count.py", line 55, in flop_count
> total_flop_counter, skipped_ops = get_jit_model_analysis(
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/fvcore/nn/jit_handles.py", line 98, in get_jit_model_analysis
> trace, _ = torch.jit._get_trace_graph(model, inputs)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/jit/__init__.py", line 277, in _get_trace_graph
> outs = ONNXTracedModule(f, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 532, in __call__
> result = self.forward(*input, **kwargs)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/jit/__init__.py", line 356, in forward
> graph, out = torch._C._create_graph_by_tracing(
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/jit/__init__.py", line 347, in wrapper
> outs.append(self.inner(*trace_inputs))
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 530, in __call__
> result = self._slow_forward(*input, **kwargs)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 516, in _slow_forward
> result = self.forward(*input, **kwargs)
> File "/media/st4Tb/fbtools/slowfast/slowfast/models/video_model_builder.py", line 393, in forward
> x = self.head(x, bboxes)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 530, in __call__
> result = self._slow_forward(*input, **kwargs)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 516, in _slow_forward
> result = self.forward(*input, **kwargs)
> File "/media/st4Tb/fbtools/slowfast/slowfast/models/head_helper.py", line 129, in forward
> x = self.act(x)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 530, in __call__
> result = self._slow_forward(*input, **kwargs)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 516, in _slow_forward
> result = self.forward(*input, **kwargs)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/nn/modules/activation.py", line 1018, in forward
> return F.softmax(input, self.dim, _stacklevel=5)
> File "/media/st4Tb/anaconda3/envs/torchenv/lib/python3.8/site-packages/torch/nn/functional.py", line 1231, in softmax
> ret = input.softmax(dim)
> IndexError: Dimension out of range (expected to be in range of [-2, 1], but got 4)
>

this is my YAML file (without BN section):

> TRAIN:
> ENABLE: False
> DATASET: ava
> BATCH_SIZE: 16
> EVAL_PERIOD: 1
> CHECKPOINT_PERIOD: 1
> AUTO_RESUME: True
> CHECKPOINT_FILE_PATH: "/media/st4Tb/fbtools/slowfast/demo/SLOWFAST_32x2_R101_50_50_v2.1.pkl" #path to pretrain model
> CHECKPOINT_TYPE: pytorch
> DATA:
> NUM_FRAMES: 32
> SAMPLING_RATE: 2
> TRAIN_JITTER_SCALES: [256, 320]
> TRAIN_CROP_SIZE: 224
> TEST_CROP_SIZE: 256
> INPUT_CHANNEL_NUM: [3, 3]
> DETECTION:
> ENABLE: True
> ALIGNED: False
> AVA:
> BGR: False
> DETECTION_SCORE_THRESH: 0.8
> 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: 5
> RESNET:
> ZERO_INIT_FINAL_BN: True
> WIDTH_PER_GROUP: 64
> NUM_GROUPS: 1
> DEPTH: 101
> 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: [[[], []], [[], []], [[6, 13, 20], []], [[], []]]
> GROUP: [[1, 1], [1, 1], [1, 1], [1, 1]]
> INSTANTIATION: dot_product
> POOL: [[[2, 2, 2], [2, 2, 2]], [[2, 2, 2], [2, 2, 2]], [[2, 2, 2], [2, 2, 2]], [[2, 2, 2], [2, 2, 2]]]
> SOLVER:
> MOMENTUM: 0.9
> WEIGHT_DECAY: 1e-7
> OPTIMIZING_METHOD: sgd
> MODEL:
> NUM_CLASSES: 80
> ARCH: slowfast
> LOSS_FUNC: bce
> DROPOUT_RATE: 0.5
> TEST:
> ENABLE: False
> DATASET: ava
> BATCH_SIZE: 8
> DATA_LOADER:
> NUM_WORKERS: 2
> PIN_MEMORY: True
> DEMO:
> ENABLE: True
> LABEL_FILE_PATH: "./demo/AVA/ava.names"
> DATA_SOURCE: "/media/st4Tb/fbtools/slowfast/demo/input_30sec.mp4"
> # DISPLAY_WIDTH: 640
> # DISPLAY_HEIGHT: 480
> DETECTRON2_OBJECT_DETECTION_MODEL_CFG: "COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml"
> DETECTRON2_OBJECT_DETECTION_MODEL_WEIGHTS: "detectron2://COCO-Detection/faster_rcnn_R_50_FPN_3x/137849458/model_final_280758.pkl"
> NUM_GPUS: 1
> NUM_SHARDS: 1
> RNG_SEED: 0
> OUTPUT_DIR: .

thank you in advance for your help!