ModuleNotFoundError: No module named 'torch.utils.model_zoo'

I am on the latest PyTorch and torchaudio and I get this error when I import torchaudio. Any ideas?

1 # Imports used through the rest of the notebook.
      2 import torch
----> 3 import torchaudio
      4 import torch.nn as nn
      5 import torch.nn.functional as F

File ~/.python/current/lib/python3.10/site-packages/torchaudio/
----> 1 from torchaudio import (  # noqa: F401
      2     _extension,
      3     compliance,
      4     datasets,
      5     functional,
      6     io,
      7     kaldi_io,
      8     models,
      9     pipelines,
     10     sox_effects,
     11     transforms,
     12     utils,
     13 )
     14 from torchaudio.backend import get_audio_backend, list_audio_backends, set_audio_backend
     16 try:
     25         progress_bar (bool, optional): Display a progress bar (Default: ``True``).
     26     """

ModuleNotFoundError: No module named 'torch.utils.model_zoo'

Details on my environment is here:

Collecting environment information...
PyTorch version: 1.13.1+cu117
Is debug build: False
CUDA used to build PyTorch: 11.7
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.5 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: 10.0.0-4ubuntu1 
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.10.4 (main, Nov 29 2022, 20:00:25) [GCC 9.4.0] (64-bit runtime)
Python platform: Linux-5.4.0-1094-azure-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: Tesla V100-PCIE-16GB
Nvidia driver version: 520.61.05
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] rotary-embedding-torch==0.2.1
[pip3] torch==1.13.1
[pip3] torchaudio==0.13.1
[conda] No relevant packages

I cannot reproduce the issue using the same versions:

>>> import torch
>>> torch.__version__
>>> import torchaudio
>>> torchaudio.__version__

Are you using multiple virtual environments or could another PyTorch version have been installed into the base env?