BUG: to_hdf and HDFStore raise KeyError for DataFrame subclasses
- [x ] I have checked that this issue has not already been reported.

- [x ] I have confirmed this bug exists on the latest version of pandas.
---
#### Code Sample, a copy-pastable example

```python
import pandas as pd
class SubDataFrame(pd.DataFrame):
    @property
    def _constructor(self):
        return SubDataFrame

# fails with KeyError
sdf = SubDataFrame({'a':[1,2], 'b':[3,4]})
sdf.to_hdf('test.h5', 'test')

with pd.HDFStore('test.h5') as store:
    store.put('test', sdf)
```

#### Problem description

``to_hdf()`` and ``HDFStore.put()`` fail for DataFrame subclasses.

This happens because in ``pandas/io/pytables.py`` in ``_create_storer`` line 1578 (or thereabouts), the ``_TYPE_MAP`` is accessed by ``type()``, whereas upon ``_create_storer`` entry, the check is done using ``isinstance()``. 

#### Expected Output

The check upon entry of ``_create_storer`` should at least be consistent with the way ``_TYPE_MAP`` is accessed. So if the choice is not to support writing DataFrame subclasses to HDF, instead of a ``KeyError``, a ``TypeError("value must be None, Series, or DataFrame")`` should be raised.

But ideally, storing subclasses of DataFrame to HDF should be supported.

#### Output of ``pd.show_versions()``
<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.10.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.14.111-1.el7.centos.x86_64
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.3.post20200325
Cython           : None
pytest           : 5.4.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.4 (dt dec pq3 ext lo64)
jinja2           : 2.10.3
IPython          : 7.10.2
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : None
fastparquet      : 0.3.2
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.4.1
pyxlsb           : None
s3fs             : 0.4.0
scipy            : 1.2.1
sqlalchemy       : 1.3.11
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : 0.46.0

</details>
