code: def _resize_output_check(out: TensorLikeType, shape: ShapeType):
      # If the shapes are correct there's nothing to do
      if utils.same_shape(out.shape, shape):
          return False
      if out.numel() != 0:
          msg = (
              f"An output with one or more elements was resized since it had shape {str(out.shape)} "
              "which does not match the required output shape {str(shape)}. "
              "This behavior is deprecated, and in a future PyTorch release outputs will not "
              "be resized unless they have zero elements. "
              "You can explicitly reuse an out tensor t by resizing it, inplace, to zero elements with t.resize_(0)."
          )
          warnings.warn(msg)
      return True
  
imports: import inspect
  import warnings
  from functools import wraps
  from itertools import chain
  from typing import Callable, NamedTuple, Optional, overload, Sequence, Tuple
  import torch
  import torch._prims_common
  from torch._prims_common import CustomOutParamAnnotation, ELEMENTWISE_TYPE_PROMOTION_KIND, Number, NumberType, ShapeType, TensorLike, TensorLikeType
  from torch.utils import _pytree
  from torch.utils._pytree import tree_flatten, tree_unflatten
label_desc: Use image node_id 8 for calling a global function with example usage: _resize_output_check(out, shape) and returns: True, False