code: def from_flattened_numpy(x, shape):
      """Form a torch tensor with the given `shape` from a flattened numpy array `x`."""
      return torch.from_numpy(x.reshape(shape))
  
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 2 for calling a global function with example usage: from_flattened_numpy(x, shape) and returns: torch