code: def parameters_to_vector(
      parameters: Iterable[torch.Tensor],
  ) -> torch.Tensor:
      r"""Flatten an iterable of parameters into a single vector.
  
      Args:
          parameters (Iterable[Tensor]): an iterable of Tensors that are the
              parameters of a model.
  
      Returns:
          The parameters represented by a single vector
      """
      # Flag for the device where the parameter is located
      param_device = None
  
      vec = []
      for param in parameters:
          # Ensure the parameters are located in the same device
          param_device = _check_param_device(param, param_device)
  
          vec.append(param.view(-1))
      return torch.cat(vec)
  
imports: import torch
  from typing import Iterable, Optional
label_desc: Use image node_id 1 for calling a global function with example usage: parameters_to_vector(parameters) and returns: torch