code: def forward(self, img1, img2, flow, valid_flow_mask):
      if torch.rand(1) > self.p:
          return img1, img2, flow, valid_flow_mask
  
      for _ in range(torch.randint(self.max_erase, size=(1,)).item()):
          x, y, h, w, v = self.get_params(
              img2,
              scale=self.scale,
              ratio=self.ratio,
              value=[self.value],
          )
          img2 = F.erase(img2, x, y, h, w, v, self.inplace)
  
      return img1, img2, flow, valid_flow_mask
  
imports: import torch
  import torchvision.transforms
  import torchvision.transforms.functional
label_desc: Use image node_id 2 for calling the RandomErasing obj's underlying member method code with example usage: obj.forward(img1, img2, flow, valid_flow_mask) and returns: img1,  img2,  flow,  valid_flow_mask, img1,  img2,  flow,  valid_flow_mask