code: def gradinit(self, dataloader, config):
      raise ValueError("GradInit not implemented for deepspeed.")
  
file_path: bert-ultrafast/training/cramming/backend/deepspeed_integration.py
imports: import torch
  import os
  import json
  from functools import partial
  import logging
  from omegaconf import OmegaConf
  from .utils import group_parameters, prepare_pretraining_dataloader
  from .optimizers import get_schedule_fn
label_desc: Use image node_id 4 for calling a global function with example usage: gradinit(dataloader, config) without return types