- Always have clients send back an 'InitReply' after the first
  'TrainingManager' setup step happened without error.
- Then, rely on step-specific query-reply exchanges for further
  steps (SecAgg, DP-SGD and/or Fairness setup).

When a '__all__' value is provided in a public module, make use of
it instead of collecting each and every member.

This fixes the collection breaking upon encountering external
packages such as 'warnings' in an '__init__.py' file.

Fix the case when the batch size for a given subset is
exactly a multiple of the number of samples for that
subset, which would result in an exception (at least
with in-memory data).

- Add shared code in the unit tests suite.
- Add dedicated data and tests in FairGrad and FairBatch subclasses.

- Expose some subroutines under setup and fairness round,
  for the mere sake of making tests easier to perform, as
  well as to enable variants over current algorithms in
  the future / in experiments.
- Rename some methods and re-order some arguments.
- Refactor server-side aggregation of metrics, making it
  part of 'FairnessControllerServer' rather than part of
  'FederatedServer' backend code.

- Replace 'FairfedFairnessFunction' with 'FairfedValueComputer'.
- Add explicit 'target' keyword argument to the controller classes.

- Revise 'FairnessAccuracyComputer' into 'FairnessMetricsComputer'.
  - Revise name and documentation to reflect broader scope.
  - Remove specific accuracy and loss computation routines.
  - Introduce more generic metrics-computation routines.
  - Add methods to set up accuracy and loss-computation metrics.
- Revise 'FairnessControllerClient.compute_fairness_measures':
  - Have unshared values be returned as a nested dict,
    to limit redundant (un)packing operations and code.
  - Add 'setup_fairness_metrics' method to define metrics
    to compute. By default, compute group-wise accuracy.
  - By default, scale and share all metrics defined by
    `setup_fairness_metrics`, and compute (but do not
    share) local fairness values.
- Propagate this change across all subclasses, effectively
  trimming some redundant boilerplate code.

- Until now, 'TomlConfig' fields were either mandatory of had a
  fixed default value. In some cases, the latter may be refined
  based on other values; however, they could not be missing in
  TOML files.
- With the added 'autofield_fields' class attribute, some fields
  can be explicitly marked as having a dynamically-created default
  value. In that case, it can safely be ignored in TOML files.
- This is now used to support omitting 'evaluate' and 'fairness'
  fields when writing down a 'FLRunConfig' as a TOML file.

Debug 'FederatedClient' along the way, mostly improving error
catching and raising behaviors' consistency with other methods.