code: def i3d_nl5_resnet50_v1_kinetics400(cfg):
      model = I3D_ResNetV1(
          num_classes=cfg.CONFIG.DATA.NUM_CLASSES,
          depth=50,
          pretrained=cfg.CONFIG.MODEL.PRETRAINED,
          pretrained_base=cfg.CONFIG.MODEL.PRETRAINED_BASE,
          feat_ext=cfg.CONFIG.INFERENCE.FEAT,
          num_segment=cfg.CONFIG.DATA.NUM_SEGMENT,
          num_crop=cfg.CONFIG.DATA.NUM_CROP,
          out_indices=[3],
          inflate_freq=(
              (1, 1, 1),
              (1, 0, 1, 0),
              (1, 0, 1, 0, 1, 0),
              (0, 1, 0),
          ),
          bn_eval=cfg.CONFIG.MODEL.BN_EVAL,
          partial_bn=cfg.CONFIG.MODEL.PARTIAL_BN,
          bn_frozen=cfg.CONFIG.MODEL.BN_FROZEN,
          nonlocal_stages=(1, 2),
          nonlocal_cfg=dict(nonlocal_type="gaussian"),
          nonlocal_freq=(
              (0, 0, 0),
              (0, 1, 0, 1),
              (0, 1, 0, 1, 0, 1),
              (0, 0, 0),
          ),
      )
  
      if cfg.CONFIG.MODEL.PRETRAINED:
          from ..model_store import get_model_file
  
          model.load_state_dict(
              torch.load(
                  get_model_file(
                      "i3d_nl5_resnet50_v1_kinetics400",
                      tag=cfg.CONFIG.MODEL.PRETRAINED,
                  )
              )
          )
      return model
  
imports: import torch
  import torch.nn
  from torch.nn import BatchNorm3d
  from .non_local import build_nonlocal_block
label_desc: Use image node_id 6 for calling a global function with example usage: i3d_nl5_resnet50_v1_kinetics400(cfg) and returns: model