prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Remove unused module
  [`torchaudio._internal.misc_ops`](https://github.com/pytorch/audio/blob/b059f08742e70700ce4c92296a1131118f67a588/torchaudio/_internal/misc_ops.py) is a residue from refactoring of I/O features in the past releases. We can get rid of the whole module.
  
  
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `torchaudio/_internal/misc_ops.py`
  Content:
  ```
  1 from typing import Union, Callable
  2 
  3 import torch
  4 from torch import Tensor
  5 
  6 
  7 def normalize_audio(signal: Tensor, normalization: Union[bool, float, Callable]) -> None:
  8     """Audio normalization of a tensor in-place.  The normalization can be a bool,
  9     a number, or a callable that takes the audio tensor as an input. SoX uses
  10     32-bit signed integers internally, thus bool normalizes based on that assumption.
  11     """
  12 
  13     if not normalization:
  14         return
  15 
  16     if isinstance(normalization, bool):
  17         normalization = 1 << 31
  18 
  19     if isinstance(normalization, (float, int)):
  20         # normalize with custom value
  21         signal /= normalization
  22     elif callable(normalization):
  23         signal /= normalization(signal)
  24 
  25 
  26 def check_input(src: Tensor) -> None:
  27     if not torch.is_tensor(src):
  28         raise TypeError('Expected a tensor, got %s' % type(src))
  29     if src.is_cuda:
  30         raise TypeError('Expected a CPU based tensor, got %s' % type(src))
  31
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/torchaudio/_internal/misc_ops.py b/torchaudio/_internal/misc_ops.py
  deleted file mode 100644
  --- a/torchaudio/_internal/misc_ops.py
  +++ /dev/null
  @@ -1,30 +0,0 @@
  -from typing import Union, Callable
  -
  -import torch
  -from torch import Tensor
  -
  -
  -def normalize_audio(signal: Tensor, normalization: Union[bool, float, Callable]) -> None:
  -    """Audio normalization of a tensor in-place.  The normalization can be a bool,
  -    a number, or a callable that takes the audio tensor as an input. SoX uses
  -    32-bit signed integers internally, thus bool normalizes based on that assumption.
  -    """
  -
  -    if not normalization:
  -        return
  -
  -    if isinstance(normalization, bool):
  -        normalization = 1 << 31
  -
  -    if isinstance(normalization, (float, int)):
  -        # normalize with custom value
  -        signal /= normalization
  -    elif callable(normalization):
  -        signal /= normalization(signal)
  -
  -
  -def check_input(src: Tensor) -> None:
  -    if not torch.is_tensor(src):
  -        raise TypeError('Expected a tensor, got %s' % type(src))
  -    if src.is_cuda:
  -        raise TypeError('Expected a CPU based tensor, got %s' % type(src))
  
verification_info: {"golden_diff": "diff --git a/torchaudio/_internal/misc_ops.py b/torchaudio/_internal/misc_ops.py\ndeleted file mode 100644\n--- a/torchaudio/_internal/misc_ops.py\n+++ /dev/null\n@@ -1,30 +0,0 @@\n-from typing import Union, Callable\n-\n-import torch\n-from torch import Tensor\n-\n-\n-def normalize_audio(signal: Tensor, normalization: Union[bool, float, Callable]) -> None:\n-    \"\"\"Audio normalization of a tensor in-place.  The normalization can be a bool,\n-    a number, or a callable that takes the audio tensor as an input. SoX uses\n-    32-bit signed integers internally, thus bool normalizes based on that assumption.\n-    \"\"\"\n-\n-    if not normalization:\n-        return\n-\n-    if isinstance(normalization, bool):\n-        normalization = 1 << 31\n-\n-    if isinstance(normalization, (float, int)):\n-        # normalize with custom value\n-        signal /= normalization\n-    elif callable(normalization):\n-        signal /= normalization(signal)\n-\n-\n-def check_input(src: Tensor) -> None:\n-    if not torch.is_tensor(src):\n-        raise TypeError('Expected a tensor, got %s' % type(src))\n-    if src.is_cuda:\n-        raise TypeError('Expected a CPU based tensor, got %s' % type(src))\n", "issue": "Remove unused module\n[`torchaudio._internal.misc_ops`](https://github.com/pytorch/audio/blob/b059f08742e70700ce4c92296a1131118f67a588/torchaudio/_internal/misc_ops.py) is a residue from refactoring of I/O features in the past releases. We can get rid of the whole module.\r\n\r\n\n", "before_files": [{"content": "from typing import Union, Callable\n\nimport torch\nfrom torch import Tensor\n\n\ndef normalize_audio(signal: Tensor, normalization: Union[bool, float, Callable]) -> None:\n    \"\"\"Audio normalization of a tensor in-place.  The normalization can be a bool,\n    a number, or a callable that takes the audio tensor as an input. SoX uses\n    32-bit signed integers internally, thus bool normalizes based on that assumption.\n    \"\"\"\n\n    if not normalization:\n        return\n\n    if isinstance(normalization, bool):\n        normalization = 1 << 31\n\n    if isinstance(normalization, (float, int)):\n        # normalize with custom value\n        signal /= normalization\n    elif callable(normalization):\n        signal /= normalization(signal)\n\n\ndef check_input(src: Tensor) -> None:\n    if not torch.is_tensor(src):\n        raise TypeError('Expected a tensor, got %s' % type(src))\n    if src.is_cuda:\n        raise TypeError('Expected a CPU based tensor, got %s' % type(src))\n", "path": "torchaudio/_internal/misc_ops.py"}], "after_files": [{"content": null, "path": "torchaudio/_internal/misc_ops.py"}]}