SeriesGroupby transform unique not working in Pandas 1.0.1
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
import pandas as pd
df = pd.DataFrame({"title":['a','b','c','c','a'], "asset_id":['a1','b1','c1','c2','c1']})
df.groupby("title").asset_id.transform("unique")

```
#### Problem description
Since pandas 1.0.1, unique does not seem to be a whitelisted transform function for SeriesGroupby objects anymore. The above code works with pandas 0.25.3 but not with 1.0.1 It raises a ValueError exception:

```pytb
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-1-ccb0ce21c35f> in <module>
      1 import pandas as pd
      2 df = pd.DataFrame({"title":['a','b','c','c','a'], "asset_id":['a1','b1','c1','c2','c1']})
----> 3 df.groupby("title").asset_id.transform("unique")

~/sandbox/pandas/pandas/core/groupby/generic.py in transform(self, func, *args, **kwargs)
    470         elif func not in base.transform_kernel_whitelist:
    471             msg = f"'{func}' is not a valid function name for transform(name)"
--> 472             raise ValueError(msg)
    473         elif func in base.cythonized_kernels:
    474             # cythonized transform or canned "agg+broadcast"

ValueError: 'unique' is not a valid function name for transform(name)

```


I tried to find a documentation on that changed but was not succesful. If that is the intended behaviour, I think it would be helpful to document it.
#### Expected Output
0    [a1, c1]
1     [b1]
2    [c1, c2]
3    [c1, c2]
4    [a1, c1]
Name: asset_id, dtype: object
#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.1.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.UTF-8
pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 19.0.3
setuptools       : 40.8.0
Cython           : None
pytest           : 5.3.5
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.3.5
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : 1.3.13
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None
</details>
