Blosc2-btune

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* New quality mode. This mode can be activated by using a tradeoff of 3 values:
(compression ratio, speed, quality) instead of just one value for lossless
compression (tradeoff). This mode is only supported for integer datasets
(mainly RGB and gray-scale images). For more info on how this works, take a look at
https://github.com/Blosc/Blosc2-Btune?tab=readme-ov-file#btune-quality-mode.

* Removed shuffle size from the tweaking parameters since it is no longer
supported in C-Blosc2.

* Removed block size from the tracing list since it is not changed by btune.

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* Slight variations in the way to decide the winner in the genetic
algorithm. This is to avoid that the same winner is always selected
when there is no improvement in the cratio (it can be speed too).

* Make exploration of threads a bit bolder. Although due to the overhead
in changing the threads, this is not very useful in practice.

* Express S.Speed in GB/s. This is more intuitive than previous figure.

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* Disable printing of Blocksize and Shufflesize in `BTUNE_TRACE` header.
This is because these values are not used in the tweaking process anymore.

* "Score" is now called "S.Score" (Speed Score) in the `BTUNE_TRACE` header.
This is the inverse of the previous score. It provides a better
interpretation (larger figures are better scores), and should read better.

* Provide some room for exploring a number of threads beyond usual limits.

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* Added both splitmode to inference, so no tweking is
needed when using the models.

* Fixed a bug in blosc2_btune.set_params_defaults when not
passing `models_dir` arg.

* Performace optimizations such as computing only once
the zeros speed needed to perform the inference
and reusing the already loaded models so that time and memory
are saved.

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* Support for Windows wheels is here.

* Wheels are not dependent on the Python version ABI anymore.
This is because Btune is essentially a C++ library, with no
calls to Python (or extension) ABI at all.

* There is support now for passing btune config through Python.
See new example at ``examples/btune_config.py``.

* Embedded tensorflow lite bumped to 2.14.0.

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* Call blosc2_init() during Btune initialization to get
access to user defined codecs and filters.

* Updated to use latest C-Blosc2 sources.