BUG: get_dummies does not create dummy columns for values passed to CategoricalDtype
- [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.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd

from pandas.api.types import CategoricalDtype

df = pd.DataFrame({'country': ['russia', 'germany', 'russia', 'germany', 'germany']})

df["country"] = df["country"].astype('category',CategoricalDtype(categories=["germany","russia","japan"]))

# there should be a column called `japan`, but it's missing
pd.get_dummies(df["country"])
```

#### Problem description

Calling `pd.get_dummies()` on a DataFrame column of type `category` having extra `categories` passed does **not** generate columns for **extra categories** other than those that exist in the DataFrame.

#### Expected Output

The output should be a dataframe with one-hot encoded columns for values `germany`, `russia` **and** for `japan`. 

(This was the output in Pandas 0.24 when we could still use `.astype('category', categories=[...])` without needing to define a `CategoricalDtype`)


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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.9.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.3.0-42-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : pt_BR.UTF-8

pandas           : 1.0.3
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.3
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.0
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.2.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
