code: def __init__(
      self,
      gamma: float = 0.8,
      resize_factor: float = 0.25,
      rescale_factor: float = 0.25,
      rescale_mode: str = "bilinear",
  ) -> None:
      super().__init__()
      self.gamma = gamma
      self.resize_factor = resize_factor
      self.rescale_factor = rescale_factor
      self.rescale_mode = rescale_mode
      self._weights = None
  
imports: from typing import List, Optional
  import torch
  from torch import nn, Tensor
  from torch.nn import functional
  from torchvision.prototype.models.depth.stereo.raft_stereo import grid_sample, make_coords_grid
label_desc: Use image node_id 1 to create a new FlowSequenceConsistencyLoss object from inherited base classes: nn with example: obj = FlowSequenceConsistencyLoss(gamma, resize_factor, rescale_factor, rescale_mode)