code: def _flatten_dense_tensors(tensors):
      """Flatten dense tensors into a contiguous 1D buffer. Assume tensors are of
      same dense type.
  
      Since inputs are dense, the resulting tensor will be a concatenated 1D
      buffer. Element-wise operation on this buffer will be equivalent to
      operating individually.
  
      Args:
          tensors (Iterable[Tensor]): dense tensors to flatten.
  
      Returns:
          A contiguous 1D buffer containing input tensors.
      """
      return torch._C._nn.flatten_dense_tensors(tensors)
  
imports: import copyreg
  import functools
  import sys
  import traceback
  import warnings
  from collections import defaultdict
  from typing import Any, DefaultDict, List, Optional
  import torch
label_desc: Use image node_id 22 for calling a global function with example usage: _flatten_dense_tensors(tensors) and returns: torch