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v0.6.2

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New release 0.6.2 (#913)

New release 0.6.2

v0.6.1

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Bump version: 0.6.0 → 0.6.1 (#845)

Bump version after #844 which represents a breaking config schema
change.

v0.6.0

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Bump version: 0.5.1 → 0.6.0 (#795)

Especially for build system updates.

v0.5.1

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Bump version: 0.5.0 → 0.5.1 to mark a stable version before the big c…

…hanges (async Environment etc.) (#695)

v0.5.0

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Bump version: 0.4.2 → 0.5.0 (#672)

Let's cut a new minor release with the new functionality we've merged in
this week.

v0.4.2

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Bump version: 0.4.1 → 0.4.2 (#658)

v0.4.1

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Improve mlos-viz for multiple repeats of a config and add tests (#633)

- Mark `mlos_viz` as `typed` for `mypy`
- Bump version
- Mock calls to matplotlib/dabl for testing
- Add plotting of top-N configs
- Improve plots for handling repeat config trials via variance error
bars

---------

Co-authored-by: Sergiy Matusevych <sergiym@microsoft.com>

v0.4.0

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Refactor `mlos_bench.storage` and add `TunableConfigTrialGroup` prope…

…rty for `TrialData` and `ExperimentData` (#648)

Useful for grouping trials by the config they used. In use by upcoming
#633 for generating graphs with variance error bars for repeated
configs.

Also refactors a number of other things:
- Standardize on `experiment_id` instead of `exp_id`
  (but not the db schema for now)
- Standardize on `tunable_config_id` instead of `config_id` in the API
since we also call it `tunable_config` for the object fetching property
to distinguish from the `config` dict used internally.
  (but not the db schema for now)
- Rework the idea of `TunableConfigTrialGroup` as an object inaddition
to an ID (further methods can be added later to move back and forth
between types when doing interactive analysis).
- Rework the idea of a `TunableConfig` as an object for fetching tunable
value assignments (similar justification - easier grouping in the future
by fetching trial across experiments based on config - eventually could
be used to house the experiment merge logic).
- Rename `results` APIs to `results_df` (similar for others that return
`pandas.DataFrame`) to match the `results_dict` that return `dict`
- Refactor test fixtures to match other styles and for future use (moved
to #644).
- Expand tests

NOTE:
- We cut a new version with this commit since there are potentially
breaking API changes (e.g., `results` -> to `results_df` and `exp_id` ->
`experiment_id`).

Currently builds off of #644 and splits work out of #633

---------

Co-authored-by: Sergiy Matusevych <sergiym@microsoft.com>

v0.3.2

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PyPi publish makefile rules fixup (#640)

Prior Makefile rule consolidation tried to group dependencies for the
pattern rule into separate lines for readability, but apparently this
isn't allowed.

This minor changes separates those out into a variable we can reference
instead. Tested on a clean build tree locally.

v0.3.1

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Support for special tunable values outside of the range (#617)

Enables special values outside of the range (e.g., `-1` with a range of
`[0, 100]`).

To do we make use of "conditionals" in ConfigSpace to constrain the
space. This has a number of implementation implications, addressed
below:

* [x] Add support for special values to the `Tunable` class
* [x] Add unit tests for assigning special values outside of the range
to the `Tunable` objects
* [x] Add special values outside of the range to the unit tests for
`ConfigSpace` conversion
* [x] Implement proper `TunableGroups` to `ConfigSpace` conversion for
tunables with special values
* [x] Update `mlos_core` optimizers to support conditionals and special
values in `ConfigSpace`
* [x] Add more unit tests to check the conversion
* [x] Make LlamaTune adapter support conditionals in `ConfigSpace`

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Co-authored-by: Brian Kroth <bpkroth@users.noreply.github.com>