code: def _check_shape_compatible(x: torch.Tensor, y: torch.Tensor) -> None:
      if x.ndim != y.ndim:
          raise ValueError(
              f"The operands must be the same dimension (got {x.ndim} and {y.ndim})."
          )
  
      for i in range(x.ndim - 1):
          xi = x.size(i)
          yi = y.size(i)
          if xi == yi or xi == 1 or yi == 1:
              continue
          raise ValueError(
              f"Leading dimensions of x and y are not broadcastable (got {x.shape} and {y.shape})."
          )
  
imports: import math
  import tempfile
  import warnings
  from collections.abc import Sequence
  from typing import List, Optional, Tuple, Union
  import torch
  import torchaudio
  from torch import Tensor
  from torchaudio._internal.module_utils import deprecated
  from .filtering import highpass_biquad, treble_biquad
label_desc: Use image node_id 47 for calling a global function with example usage: _check_shape_compatible(x, y) without return types