code: def to_flattened_numpy(x):
      """Flatten a torch tensor `x` and convert it to numpy."""
      return x.detach().cpu().numpy().reshape((-1,))
  
imports: import torch
  from scipy import integrate
  from .correctors import Corrector, corrector_dict
  from .predictors import Predictor, ReverseDiffusionPredictor, predictor_dict
label_desc: Use image node_id 1 for calling a global function with example usage: to_flattened_numpy(x) and returns: x