code: def _unmask_unattended_patched(
      expanded_mask: torch.Tensor,
      attention_mask: torch.Tensor,
      unmasked_value: Union[bool, float],
  ):
      return expanded_mask
  
imports: import dataclasses
  import functools
  import inspect
  import math
  import sys
  import types
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
  import transformers
  from packaging import version
  from transformers.models.speecht5.modeling_speecht5 import SpeechT5EncoderWithSpeechPrenet
  from transformers.utils import is_torch_available
  from ...configuration_utils import _transformers_version
  from ...utils import logging
label_desc: Use image node_id 3 for calling a global function with example usage: _unmask_unattended_patched(expanded_mask, attention_mask, unmasked_value) and returns: expanded_mask