The meaning of these methods is not consistent with how sklearn uses
them.

For them, fit_transform(X, y) means
fit(X, y).transform(X), but we were using it as
fit(transform(X), y). So just rename fit_transform() to fit(), and now
it has the correct meaning.

What's more, the transform method isn't used external to the class, and
I don't think it should be. The public API should only deal with
TrainingPairs, it shouldn't deal with the
calculated distances. Rename it to _distances()

The old fit() method now is just an internal helper method that deals
with already calculated distance data.

It is already done in self._fit()

Now it prints something like `[arg-type]` when it errors, so you can add
`# type: ignore[arg-type]` and be specific
about the error you are silencing

It's not actually used anywhere besides from creating the initial set
of candidate predicates

it's only used internally, so make that obvious

Already is part of the Learner base class

DisagreementLearner is really reaching far down into the contained
objects. The lower classes themselves should be responsible for this
sort of thing. Sure, it makes the code more complicated, but the way it
is is fooling ourselves that it is simple,
and making it prone to breaking int he future.

It's not actually used anywhere.

See dedupeio#1065 (comment)

We were only testing the very small component of labeler.

Now we actually go through most lines of code. Check out coverage.

- Remove many unused methods of MatchLearner like mark() and pop().
  I think these used to get used when this was the only learner class,
  but now they aren;t used anywhere.
- Just set MatchLeaner.candidates in constructor. It makes it way
  easier to reason about.
- Adjust the inheritance. Now DisagreementLearner is out of the
heirarchy that MatchLEarner and BlockLearner are in. This is good,
because DisagreementLEarner OWNS these other two it is not a "is a"
  relationship
- Remove the mark() function from the sub-learners. They just have the
fit() method now, but they don't actually persist
  this training data, which is in line with the
  naming of fit().
- Make `candidates` a RO attribute, makes it easier to reason about, we
  don't have to worry about someone outside of the calss coming in
  and changing it.
- Fix a bug in BlockLearner where `remove` never actually removed entry from
  `candidates`, so if you broke the cahce of _cached_scores and ended up
  calling `self._predict(self.candidates)`, you would get the result
  from all of the original candidates.
- In the test, actually check for the values of the candidates, not
  just the number of them.
- Rename `_remove` to `remove` in the sublearners, since they are
  publicly used in DisagreementLEarner
- Remove the unused candidate_scores from the DisagreementLearner
  public API
- Always make a copy in sample_records() to avoid footguns

The config in setup.cfg is ignored.

Makes it consistent between the MatchLEarner and BlockLearner.

Also fixes a bug where self._fitted was never set to True