Error in business-day logic in CustomBusinessDay?
#### Code Sample, a copy-pastable example if possible

```python
# Your code here

# Labor Day calendar

import pandas as pd
from pandas.tseries.holiday import AbstractHolidayCalendar, USLaborDay

class testCalendar(AbstractHolidayCalendar):
    rules = [
        USLaborDay,
    ]

cal = testCalendar()
workDay = pd.offsets.CustomBusinessDay(calendar=cal)

# Print dates of Labor Day
for yr in [2021, 2032]:
    print("Labor day", yr, "is on ",  cal.holidays(pd.to_datetime(str(yr-1)+'-12-31'), 
                                                    pd.to_datetime(str(yr) + '-12-31')))

print("\n")
                                                                   
# Check next working day for Saturday before Labor Day
for dateText in ['2021-09-04', '2032-09-04']:
    date = pd.to_datetime(dateText)
    print(dateText, "is a", date.strftime('%A') + ". Roll forward to", date + 0 * workDay)


```
#### Problem description

Here's the output:

Labor day 2021 is on  DatetimeIndex(['2021-09-06'], dtype='datetime64[ns]', freq='WOM-1MON')
Labor day 2032 is on  DatetimeIndex(['2032-09-06'], dtype='datetime64[ns]', freq='WOM-1MON')


2021-09-04 is a Saturday. Roll forward to 2021-09-07 00:00:00
2032-09-04 is a Saturday. Roll forward to 2032-09-06 00:00:00

The calendar knows that Labor day is on Monday, Sept. 6 in both 2021 and 2032. However, when I ask to move to the next working day from Saturday, Sept. 4, I get the (correct) answer Sept.7 for 2021, but the (wrong) answer Sept 6 (which is Labor Day) for 2032.

Is this a bug, or am I doing something wrong?

Thanks.

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#### Expected Output

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




<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Darwin
OS-release: 17.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.2
pytest: 5.0.1
pip: 19.1.1
setuptools: 41.0.1
Cython: 0.29.12
numpy: 1.16.4
scipy: 1.3.0
pyarrow: None
xarray: None
IPython: 7.6.1
sphinx: 2.1.2
patsy: 0.5.1
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: 1.2.1
tables: 3.5.2
numexpr: 2.6.9
feather: None
matplotlib: 3.1.0
openpyxl: 2.6.2
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.8
lxml.etree: 4.3.4
bs4: 4.7.1
html5lib: 1.0.1
sqlalchemy: 1.3.5
pymysql: None
psycopg2: None
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
</details>
