code: def data_gen():
      # Generated from following code snippet
      #
      # from PIL import Image
      # import requests
      # from transformers import SamModel, SamProcessor
      #
      # model = SamModel.from_pretrained("facebook/sam-vit-base")
      # processor = SamProcessor.from_pretrained("facebook/sam-vit-base")
      #
      # img_url = "https://huggingface.co/ybelkada/segment-anything/resolve/main/assets/car.png"
      # raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB")
      # input_points = [[[450, 600]]] # 2D localization of a window
      # inputs = processor(raw_image, input_points=input_points, return_tensors="pt")
  
      pixel_values = torch.rand(1, 3, 1024, 1024, dtype=torch.float32)
      original_sizes = torch.tensor([[1764, 2646]], dtype=torch.int64)
      reshaped_input_sizes = torch.tensor(
          [[683, 1024]], dtype=torch.int64
      )
      input_points = torch.tensor(
          [[[[174.1497, 232.3129]]]], dtype=torch.float64
      )
      return dict(
          pixel_values=pixel_values,
          original_sizes=original_sizes,
          reshaped_input_sizes=reshaped_input_sizes,
          input_points=input_points,
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: data_gen() and returns: dict