ml-frameworks/using-mlflow/train-and-deploy-pytorch fails due incompatible torchvision

I'm running https://github.com/Azure/MachineLearningNotebooks/tree/824d844cd7386d95edfa6ecec1642e799ca79dd7/how-to-use-azureml/ml-frameworks/using-mlflow/train-and-deploy-pytorch on a default compute instance with "Python 3.8 AzureML" kernel.

The following cell fails
```python
lib_path = os.path.abspath("scripts")
sys.path.append(lib_path)

import train
```

with

```python
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
in
2 sys.path.append(lib_path)
3
----> 4 import train

/mnt/batch/tasks/shared/LS_root/mounts/clusters/notebook142298/code/how-to-use-azureml/ml-frameworks/using-mlflow/train-and-deploy-pytorch/scripts/train.py in
15 import torch.nn.functional as F
16 import torch.optim as optim
---> 17 import torchvision
18 from torchvision import datasets, transforms
19

/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torchvision/__init__.py in
2
3 from torchvision import models
----> 4 from torchvision import datasets
5 from torchvision import ops
6 from torchvision import transforms

/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torchvision/datasets/__init__.py in
----> 1 from .lsun import LSUN, LSUNClass
2 from .folder import ImageFolder, DatasetFolder
3 from .coco import CocoCaptions, CocoDetection
4 from .cifar import CIFAR10, CIFAR100
5 from .stl10 import STL10

/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torchvision/datasets/lsun.py in
17 import pickle
18
---> 19 from .utils import verify_str_arg, iterable_to_str
20
21

/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torchvision/datasets/utils.py in
9 import torch
10 from torch.utils.model_zoo import tqdm
---> 11 from torch._six import PY3
12
13

ImportError: cannot import name 'PY3' from 'torch._six' (/anaconda/envs/azureml_py38/lib/python3.8/site-packages/torch/_six.py)
```


The conda azureml_py38 environment has the following:


Related to https://github.com/pytorch/vision/issues/1780

ml-frameworks/using-mlflow/train-and-deploy-pytorch にある参照先の notebook を開き、scripts を追加して train を import する失敗セルを再現します。scripts/train.py の torchvision の import 付近を読み、Python 環境の torch と torchvision のバージョンを確認します。報告された torch._six PY3 エラーなしで import が完了すれば完了です。

索引モデルが issue の本文から書いたものです。