pandas 1.0.1 read_csv() is broken for some file-like objects
#### Code Sample

```python
import os
import pandas
import tempfile
import traceback

# pandas.show_versions()

fname = ''
with tempfile.NamedTemporaryFile(delete=False) as f:
    f.write('てすと\nこむ'.encode('shift-jis'))
    f.seek(0)
    fname = f.name

    try:
        result = pandas.read_csv(f, encoding='shift-jis')
        print('read shift-jis')
        print(result)

    except Exception as e:
        print(e)
        print(traceback.format_exc())

os.unlink(fname)

```
#### Problem description

Pandas 1.0.1, this sample does not work. But pandas 0.25.3, this sample works fine.
As stated in [issue #31575](https://github.com/pandas-dev/pandas/issues/31575), the encode of file-like object is ignored when its class is not io.BufferedIOBase neither RawIOBase.
However, some file-like objects are NOT inherited one of them, although the "actual" inner object is one of them.
In this code sample case, [according to the cpython implementation](https://github.com/python/cpython/blob/master/Lib/tempfile.py#L450), they has file as their attribute `self.file = file`, and `__getattr__()` returns the file's attribute as their attribute.
So the code is not work. The identic problems are in other file-like objects, for example, tempfile.*File class, werkzeug's FileStorage class, and so on.

**Note**: I first recognized this problem with using pandas via flask's posted file. The file-like object is an instance of werkzeug's FileStorage. I avoided this problem with following code:

```python
pandas.read_csv(request.files['file'].stream._file, encoding='shift-jis')
```

#### Expected Output

```
read shift-jis
  てすと
0  こむ
```

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.14.138-89.102.amzn1.x86_64
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : ja_JP.UTF-8
LOCALE           : ja_JP.UTF-8

pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 9.0.3
setuptools       : 36.2.7
Cython           : None
pytest           : 3.6.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.0.5
lxml.etree       : 4.2.1
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.10
IPython          : None
pandas_datareader: None
bs4              : 4.6.0
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.2.1
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 3.6.2
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : 1.3.4
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.1.0
xlwt             : None
xlsxwriter       : 1.0.5
numba            : None

</details>
