BUG: SeriesGroupBy.value_counts is inconsistent with Series.value_counts when the Series is categorical
- [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.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

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

```python
import pandas as pd

df = pd.DataFrame()
df["col1"] = ["A", "A", "B", "B"]
df["col2"] = pd.Categorical(["1", "2", "1", "1"], categories=["1", "2", "3"])

print(df.groupby("col1").col2.value_counts())

```



#### Problem description

A *value_counts* applied to the col2 Series:
```python
df.col2.value_counts()
```

 yields:
```
1      3
2      1
3      0
Name: col2, dtype: int64
```
Because col2 is categorical we get the 0 count for value 3, as desired.

If we groupby col1 first 
```python
df.groupby("col1").col2.value_counts()
```
we get the following output:
```
col1  col2
A     1       1
      2       1
B     1       2
Name: col2, dtype: int64
```

#### Expected Output

The expected output can be achieved with a workaround:
```python
df.groupby("col1").col2.apply(pd.Series.value_counts)
```

which yields:
```
col1   
A     2    1
      1    1
      3    0
B     1    2
      3    0
      2    0
Name: col2, dtype: int64
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : 67a3d4241ab84419856b84fc3ebc9abcbe66c6b3
python           : 3.7.5.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.1.4
numpy            : 1.19.1
pytz             : 2019.3
dateutil         : 2.8.0
pip              : 20.2.3
setuptools       : 41.2.0
Cython           : 0.29.21
pytest           : 5.3.5
hypothesis       : None
sphinx           : 2.4.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.4.1
html5lib         : 1.0.1
pymysql          : 0.9.3
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.8.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : None
fsspec           : 0.6.0
fastparquet      : None
gcsfs            : None
matplotlib       : 3.1.3
numexpr          : None
odfpy            : None
openpyxl         : 3.0.0
pandas_gbq       : None
pyarrow          : 1.0.1
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.10
tables           : None
tabulate         : 0.8.6
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : None

</details>
