Bug: AttributeError: 'MaskingTextSamplers' object has no attribute 'sampler_params' when using TextExplainer with MaskingTextSamplers

[nickt121]

When using the default values for TextExplainer, it fails reutrning:

AttributeError                            Traceback (most recent call last)
File ~\.conda\envs\eli5-pip\lib\site-packages\IPython\core\formatters.py:973, in MimeBundleFormatter.__call__(self, obj, include, exclude)
    970     method = get_real_method(obj, self.print_method)
    972     if method is not None:
--> 973         return method(include=include, exclude=exclude)
    974     return None
    975 else:

File ~\.conda\envs\eli5-pip\lib\site-packages\sklearn\base.py:629, in BaseEstimator._repr_mimebundle_(self, **kwargs)
    627 def _repr_mimebundle_(self, **kwargs):
    628     """Mime bundle used by jupyter kernels to display estimator"""
--> 629     output = {"text/plain": repr(self)}
    630     if get_config()["display"] == "diagram":
    631         output["text/html"] = estimator_html_repr(self)

File ~\.conda\envs\eli5-pip\lib\site-packages\sklearn\base.py:279, in BaseEstimator.__repr__(self, N_CHAR_MAX)
    271 # use ellipsis for sequences with a lot of elements
    272 pp = _EstimatorPrettyPrinter(
    273     compact=True,
    274     indent=1,
    275     indent_at_name=True,
    276     n_max_elements_to_show=N_MAX_ELEMENTS_TO_SHOW,
    277 )
--> 279 repr_ = pp.pformat(self)
    281 # Use bruteforce ellipsis when there are a lot of non-blank characters
    282 n_nonblank = len("".join(repr_.split()))

File ~\.conda\envs\eli5-pip\lib\pprint.py:157, in PrettyPrinter.pformat(self, object)
    155 def pformat(self, object):
    156     sio = _StringIO()
--> 157     self._format(object, sio, 0, 0, {}, 0)
    158     return sio.getvalue()

File ~\.conda\envs\eli5-pip\lib\pprint.py:174, in PrettyPrinter._format(self, object, stream, indent, allowance, context, level)
    172     self._readable = False
    173     return
--> 174 rep = self._repr(object, context, level)
    175 max_width = self._width - indent - allowance
    176 if len(rep) > max_width:

File ~\.conda\envs\eli5-pip\lib\pprint.py:454, in PrettyPrinter._repr(self, object, context, level)
    453 def _repr(self, object, context, level):
--> 454     repr, readable, recursive = self.format(object, context.copy(),
    455                                             self._depth, level)
    456     if not readable:
    457         self._readable = False

File ~\.conda\envs\eli5-pip\lib\site-packages\sklearn\utils\_pprint.py:189, in _EstimatorPrettyPrinter.format(self, object, context, maxlevels, level)
    188 def format(self, object, context, maxlevels, level):
--> 189     return _safe_repr(
    190         object, context, maxlevels, level, changed_only=self._changed_only
    191     )

File ~\.conda\envs\eli5-pip\lib\site-packages\sklearn\utils\_pprint.py:452, in _safe_repr(object, context, maxlevels, level, changed_only)
    448 for k, v in items:
    449     krepr, kreadable, krecur = saferepr(
    450         k, context, maxlevels, level, changed_only=changed_only
    451     )
--> 452     vrepr, vreadable, vrecur = saferepr(
    453         v, context, maxlevels, level, changed_only=changed_only
    454     )
    455     append("%s=%s" % (krepr.strip("'"), vrepr))
    456     readable = readable and kreadable and vreadable

File ~\.conda\envs\eli5-pip\lib\site-packages\sklearn\utils\_pprint.py:440, in _safe_repr(object, context, maxlevels, level, changed_only)
    438 recursive = False
    439 if changed_only:
--> 440     params = _changed_params(object)
    441 else:
    442     params = object.get_params(deep=False)

File ~\.conda\envs\eli5-pip\lib\site-packages\sklearn\utils\_pprint.py:93, in _changed_params(estimator)
     89 def _changed_params(estimator):
     90     """Return dict (param_name: value) of parameters that were given to
     91     estimator with non-default values."""
---> 93     params = estimator.get_params(deep=False)
     94     init_func = getattr(estimator.__init__, "deprecated_original", estimator.__init__)
     95     init_params = inspect.signature(init_func).parameters

File ~\.conda\envs\eli5-pip\lib\site-packages\sklearn\base.py:211, in BaseEstimator.get_params(self, deep)
    209 out = dict()
    210 for key in self._get_param_names():
--> 211     value = getattr(self, key)
    212     if deep and hasattr(value, "get_params"):
    213         deep_items = value.get_params().items()

AttributeError: 'MaskingTextSamplers' object has no attribute 'sampler_params'

Or alternative non jupyter run:

C:\Users\admin\.conda\envs\eli5-pip\lib\site-packages\sklearn\linear_model\_stochastic_gradient.py:173: FutureWarning: The loss 'log' was deprecated in v1.1 and will be removed in version 1.3. Use `loss='log_loss'` which is equivalent.
  warnings.warn(
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Users\admin\.conda\envs\eli5-pip\lib\site-packages\sklearn\base.py", line 279, in __repr__
    repr_ = pp.pformat(self)
  File "C:\Users\admin\.conda\envs\eli5-pip\lib\pprint.py", line 157, in pformat
    self._format(object, sio, 0, 0, {}, 0)
  File "C:\Users\admin\.conda\envs\eli5-pip\lib\pprint.py", line 174, in _format
    rep = self._repr(object, context, level)
  File "C:\Users\admin\.conda\envs\eli5-pip\lib\pprint.py", line 454, in _repr
    repr, readable, recursive = self.format(object, context.copy(),
  File "C:\Users\admin\.conda\envs\eli5-pip\lib\site-packages\sklearn\utils\_pprint.py", line 189, in format
    return _safe_repr(
  File "C:\Users\admin\.conda\envs\eli5-pip\lib\site-packages\sklearn\utils\_pprint.py", line 452, in _safe_repr
    vrepr, vreadable, vrecur = saferepr(
  File "C:\Users\admin\.conda\envs\eli5-pip\lib\site-packages\sklearn\utils\_pprint.py", line 440, in _safe_repr
    params = _changed_params(object)
  File "C:\Users\admin\.conda\envs\eli5-pip\lib\site-packages\sklearn\utils\_pprint.py", line 93, in _changed_params
    params = estimator.get_params(deep=False)
  File "C:\Users\admin\.conda\envs\eli5-pip\lib\site-packages\sklearn\base.py", line 211, in get_params
    value = getattr(self, key)
AttributeError: 'MaskingTextSamplers' object has no attribute 'sampler_params'

This seems to be more of an issue relating to sklearn rather than to eli5 itself. However, an easy fix would be to include the sampler_params as an attribute in the MaskingTextSamplers class.

Do let me know if there is something that I have done wrong here.