BUG: pandas EWM fails silently if data types are float32 instead of float64
- [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 numpy as np
import pandas as pd

kk = pd.DataFrame(np.random.rand(20, 3))
kk = kk.astype(np.float32)
print(kk.ewm(alpha=0.5, axis=1).mean().shape)
# (20, 0)

kk = kk.astype(np.float64)
print(kk.ewm(alpha=0.5, axis=1).mean().shape)

# (20, 3)
```

#### Problem description

This should not depend on dtypes.

#### Expected Output

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

<details>

commit           : 7c48ff4409c622c582c56a5702373f726de08e96
python           : 3.7.10.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 20.5.0
Version          : Darwin Kernel Version 20.5.0: Sat May  8 05:10:33 PDT 2021; root:xnu-7195.121.3~9/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.5
numpy            : 1.17.4
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 21.1.2
setuptools       : 57.0.0
Cython           : None
pytest           : 6.2.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.5 (dt dec pq3 ext lo64)
jinja2           : 2.10.3
IPython          : 7.23.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : 0.4.1
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : None
odfpy            : None
openpyxl         : 3.0.6
pandas_gbq       : None
pyarrow          : 0.17.1
pyxlsb           : None
s3fs             : None
scipy            : 1.5.4
sqlalchemy       : 1.3.19
tables           : None
tabulate         : 0.8.9
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : 0.53.1

</details>
