code: def split_input(model_input, total_pixels):
      """
      Split the input to fit Cuda memory for large resolution.
      Can decrease the value of n_pixels in case of cuda out of memory error.
      """
      n_pixels = 10000
      split = []
      for i, indx in enumerate(
          torch.split(
              torch.arange(total_pixels).cuda(), n_pixels, dim=0
          )
      ):
          data = model_input.copy()
          data["uv"] = torch.index_select(model_input["uv"], 1, indx)
          data["object_mask"] = torch.index_select(
              model_input["object_mask"], 1, indx
          )
          split.append(data)
      return split
  
file_path: insightface/reconstruction/PBIDR/code/utils/general.py
imports: import os
  from glob import glob
  import torch
label_desc: Use image node_id 4 for calling a global function with example usage: split_input(model_input, total_pixels) and returns: split