BUG: `pd.testing.assert_frame_equal` does not propagate precision to interval dtype
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [X] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
df1 = pd.DataFrame()
df1[0] = pd.arrays.IntervalArray.from_tuples([(1.0, 2.0)])

df2 = pd.DataFrame()
df2[0] = pd.arrays.IntervalArray.from_tuples([(1.0000000000001, 2.0)])

# Using very large tolerances do not propagate to the interval dtype, since this assert fails:
pd.testing.assert_frame_equal(df1, df2, check_exact=False, rtol=10., atol=10.)
```


### Issue Description

It seems that `pd.testing.assert_frame_equal` does not propagate chosen tolerances for `interval` dtype comparison.

### Expected Behavior

df1 = pd.DataFrame()
df1[0] = pd.arrays.IntervalArray.from_tuples([(1.0, 2.0)])
df2 = pd.DataFrame()
df2[0] = pd.arrays.IntervalArray.from_tuples([(1.0000000000001, 2.0)])
# This test should pass...
pd.testing.assert_frame_equal(df1, df2, check_exact=False, rtol=10., atol=10.)

### Installed Versions

<details>
INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.8.8.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             : fr_FR.UTF-8
LOCALE           : fr_FR.UTF-8

pandas           : 1.2.4
numpy            : 1.20.1
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 52.0.0.post20210125
Cython           : 0.29.23
pytest           : 6.2.3
hypothesis       : None
sphinx           : 4.0.1
blosc            : None
feather          : None
xlsxwriter       : 1.3.8
lxml.etree       : 4.6.3
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.22.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.9.0
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : 1.4.7
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 2.0.1
xlwt             : 1.3.0
numba            : 0.53.1
</details>
