code: def index(feat, uv):
      """
      extract image features at floating coordinates with bilinear interpolation
      args:
          feat: [B, C, H, W] image features
          uv: [B, 2, N] normalized image coordinates ranged in [-1, 1]
      return:
          [B, C, N] sampled pixel values
      """
      uv = uv.transpose(1, 2)
      uv = uv.unsqueeze(2)
      samples = torch.nn.functional.grid_sample(
          feat, uv, align_corners=True
      )
      return samples[:, :, :, 0]
  
label_desc: Use image node_id 1 for calling a global function with example usage: index(feat, uv) and returns: samples