code: def _get_pixel_label_3d(
      self, input_frames, output_masks, time_stride_loss=True, norm=True
  ):
      if time_stride_loss:
          input_frames = input_frames[
              :, :, :: self.cfg.MVIT.PATCH_STRIDE[0], :, :
          ]
      imgs = input_frames
      input_frames = input_frames.permute(0, 2, 3, 4, 1)
      labels = []
      for depth, output_mask in zip(self.pretrain_depth, output_masks):
          size = self.feat_stride[depth][-1]
          label = self._patchify(
              imgs, p=size, time_stride_loss=time_stride_loss
          )
          label = label[output_mask]
  
          if norm:  # self.norm_pix_loss:
              mean = label.mean(dim=-1, keepdim=True)
              var = label.var(dim=-1, keepdim=True)
              label = (label - mean) / (var + 1.0e-6) ** 0.5
          labels.append(
              (label, self.pred_pixel_wt / len(self.pretrain_depth))
          )
      return labels
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.init import trunc_normal_
  import slowfast.utils.logging
  import slowfast.utils.misc
  from slowfast.models import head_helper
  from slowfast.models.attention import attention_pool
  from slowfast.models.utils import calc_mvit_feature_geometry
  from slowfast.models.video_model_builder import MViT
  from .None import head_helper, operators, resnet_helper, stem_helper
  from .build import MODEL_REGISTRY
label_desc: Use image node_id 8 for calling the MaskMViT obj's underlying member method code with example usage: obj._get_pixel_label_3d(input_frames, output_masks, time_stride_loss, norm) and returns: labels