assert_series_equal(..., check_exact=True) reports identically constructed Series are not equal.
#### Code Sample

```python
#!/usr/bin/env python
import numpy as np
import pandas as pd
import pandas.testing as pdt

# Notice these are identically constructed objects
x = pd.Series([0,
               0.0131142231938,
               1.77774652865e-05,
               np.array([0.4722720840328748, 0.4216929783681722])])
y = pd.Series([0,
               0.0131142231938,
               1.77774652865e-05,
               np.array([0.4722720840328748, 0.4216929783681722])])

print(x)

pdt.assert_series_equal(x, x)  # Works as expected
pdt.assert_series_equal(x, x, check_exact=True)  # Works as expected
pdt.assert_series_equal(x, y)  # Works as expected
pdt.assert_series_equal(x, y, check_exact=True)  # Unexpectedly fails
```
#### Problem description

The current behavior reports that two identically constructed Series are different for `check_exact=True`.  Additionally, this operation emits unexpected warnings.  That is, I see the following:

```
$ ./recreate
0                                           0
1                                   0.0131142
2                                 1.77775e-05
3    [0.4722720840328748, 0.4216929783681722]
dtype: object
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
Exception ignored in: 'pandas._libs.lib.array_equivalent_object'
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
Traceback (most recent call last):
  File "./recreate", line 21, in <module>
    pdt.assert_series_equal(x, y, check_exact=True)  # Unexpectedly fails
  File "/nas/dft/ire/rhys/envs/testing/lib/python3.5/site-packages/pandas/util/testing.py", line 1215, in assert_series_equal
    obj='{obj}'.format(obj=obj),)
  File "/nas/dft/ire/rhys/envs/testing/lib/python3.5/site-packages/pandas/util/testing.py", line 1104, in assert_numpy_array_equal
    _raise(left, right, err_msg)
  File "/nas/dft/ire/rhys/envs/testing/lib/python3.5/site-packages/pandas/util/testing.py", line 1098, in _raise
    raise_assert_detail(obj, msg, left, right)
  File "/nas/dft/ire/rhys/envs/testing/lib/python3.5/site-packages/pandas/util/testing.py", line 1035, in raise_assert_detail
    raise AssertionError(msg)
AssertionError: Series are different

Series values are different (0.0 %)
[left]:  [0, 0.0131142231938, 1.77774652865e-05, [0.4722720840328748, 0.4216929783681722]]
[right]: [0, 0.0131142231938, 1.77774652865e-05, [0.4722720840328748, 0.4216929783681722]]
```

#### Expected Output

I expect two identically constructed Series to be equal, which would give:

```
$ ./recreate
0                                           0
1                                   0.0131142
2                                 1.77775e-05
3    [0.4722720840328748, 0.4216929783681722]
dtype: object
```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.5.final.0
python-bits: 64
OS: Linux
OS-release: 4.1.35-pv-ts2
machine: x86_64
processor:
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.utf8
LOCALE: en_US.UTF-8

pandas: 0.23.4
pytest: None
pip: 10.0.1
setuptools: 40.0.0
Cython: None
numpy: 1.15.0
scipy: None
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
None
</details>
