REGR: Series.__repr__ is broken for SparseDtype("datetime64[ns]")
Regression due to https://github.com/pandas-dev/pandas/commit/1fa063552eef57ecec9c6a867ff2ae4bb3961e3d :

```python
import pandas as pd

print(pd.__version__)

values = [pd.Timestamp('2012-05-01T01:00:00.000000'), pd.Timestamp('2016-05-01T01:00:00.000000')]
arr = pd.arrays.SparseArray(values)
ser = pd.Series(arr)
ser
```

```python
1.2.0.dev0+147.g07983803b
Out[1]: ---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
~/opt/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/IPython/core/formatters.py in __call__(self, obj)
    700                 type_pprinters=self.type_printers,
    701                 deferred_pprinters=self.deferred_printers)
--> 702             printer.pretty(obj)
    703             printer.flush()
    704             return stream.getvalue()

~/opt/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/IPython/lib/pretty.py in pretty(self, obj)
    392                         if cls is not object \
    393                                 and callable(cls.__dict__.get('__repr__')):
--> 394                             return _repr_pprint(obj, self, cycle)
    395
    396             return _default_pprint(obj, self, cycle)

~/opt/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/IPython/lib/pretty.py in _repr_pprint(obj, p, cycle)
    698     """A pprint that just redirects to the normal repr function."""
    699     # Find newlines and replace them with p.break_()
--> 700     output = repr(obj)
    701     lines = output.splitlines()
    702     with p.group():

~/pandas/pandas/core/series.py in __repr__(self)
   1315         show_dimensions = get_option("display.show_dimensions")
   1316
-> 1317         self.to_string(
   1318             buf=buf,
   1319             name=self.name,

~/pandas/pandas/core/series.py in to_string(self, buf, na_rep, float_format, header, index, length, dtype, name, max_rows, min_rows)
   1386             max_rows=max_rows,
   1387         )
-> 1388         result = formatter.to_string()
   1389
   1390         # catch contract violations

~/pandas/pandas/io/formats/format.py in to_string(self)
    356
    357         fmt_index, have_header = self._get_formatted_index()
--> 358         fmt_values = self._get_formatted_values()
    359
    360         if self.truncate_v:

~/pandas/pandas/io/formats/format.py in _get_formatted_values(self)
    341
    342     def _get_formatted_values(self) -> List[str]:
--> 343         return format_array(
    344             self.tr_series._values,
    345             None,

~/pandas/pandas/io/formats/format.py in format_array(values, formatter, float_format, na_rep, digits, space, justify, decimal, leading_space, quoting)
   1179     )
   1180
-> 1181     return fmt_obj.get_result()
   1182
   1183

~/pandas/pandas/io/formats/format.py in get_result(self)
   1210
   1211     def get_result(self) -> List[str]:
-> 1212         fmt_values = self._format_strings()
   1213         return _make_fixed_width(fmt_values, self.justify)
   1214

~/pandas/pandas/io/formats/format.py in _format_strings(self)
   1467
   1468         if not isinstance(values, DatetimeIndex):
-> 1469             values = DatetimeIndex(values)
   1470
   1471         if self.formatter is not None and callable(self.formatter):

~/pandas/pandas/core/indexes/datetimes.py in __new__(cls, data, freq, tz, normalize, closed, ambiguous, dayfirst, yearfirst, dtype, copy, name)
    269         name = maybe_extract_name(name, data, cls)
    270
--> 271         dtarr = DatetimeArray._from_sequence(
    272             data,
    273             dtype=dtype,

~/pandas/pandas/core/arrays/datetimes.py in _from_sequence(cls, data, dtype, copy, tz, freq, dayfirst, yearfirst, ambiguous)
    314         freq, freq_infer = dtl.maybe_infer_freq(freq)
    315
--> 316         subarr, tz, inferred_freq = sequence_to_dt64ns(
    317             data,
    318             dtype=dtype,

~/pandas/pandas/core/arrays/datetimes.py in sequence_to_dt64ns(data, dtype, copy, tz, dayfirst, yearfirst, ambiguous)
   1957     if is_datetime64tz_dtype(data_dtype):
   1958         # DatetimeArray -> ndarray
-> 1959         tz = _maybe_infer_tz(tz, data.tz)
   1960         result = data._data
   1961

AttributeError: 'SparseArray' object has no attribute 'tz'
```

xref https://github.com/pandas-dev/pandas/issues/35762