code: def forward(ctx, run_function, length, *args):
      ctx.run_function = run_function
      ctx.input_tensors = list(args[:length])
      ctx.input_params = list(args[length:])
      ctx.gpu_autocast_kwargs = {
          "enabled": torch.is_autocast_enabled(),
          "dtype": torch.get_autocast_gpu_dtype(),
          "cache_enabled": torch.is_autocast_cache_enabled(),
      }
      with torch.no_grad():
          output_tensors = ctx.run_function(*ctx.input_tensors)
      return output_tensors
  
imports: import os
  import math
  import torch
  import torch.nn
  import numpy
  from einops import repeat
  from ldm.util import instantiate_from_config
label_desc: Use image node_id 1 for calling the CheckpointFunction obj's underlying member method code with example usage: obj.forward(ctx, run_function, length) and returns: output_tensors