Sheeprl

* Fix bugs (174).

* Added Numpy buffers (169):
* The user can now decide if to use the `torch.as_tensor` function or the `torch.from_numpy` one to convert the Numpy buffer into tensors when sampling (172).
* Added optimizations to reduce training time (168).
* Added the possibility to keep only the last `n` checkpoints in an experiment to avoid filling up the disk (171).
* Fix bugs (167).
* Update documentation.

* Added `torch>=2.0` as dependency in 161
* Let `mlflow` be an optional package to be installed, i.e. the user can directly install it with `pip install sheeprl[mlflow]` in 164
* Fix the `resume_from_checkpoint` in 163. In particular:
- Added `save_configs` function to save the configs of the experiment in the `<log_dir>/config.yaml` file.
- Fix the `resume from checkpoint` of all the algorithms (restart from the correct policy step + fix decoupled).
- Given more flexibility to p2e finetuning scripts regarding the fabric configs.
- MineDojo Wrapper: avoid modifying the kwargs (to always save consistent configs in the `<log_dir>/config.yaml` file).
- Tensorboar Logger creation: update logger configs to always save consistent configs in the `<log_dir>/config.yaml` file.
- Added `as_dict()` method (to `dotdict` class) to get a primitive python dictionary from a `dotdict` object.

* The following config keys have been moved in 158 :
* `cnn_keys`, `mlp_keys`, `per_rank_batch_size`, `per_rank_sequence_length`, `per_rank_num_batches` and `total_steps` have been moved to the specifig `algo` config
* We have added the integration of the [MLflowLogger](https://lightning.ai/docs/pytorch/stable/api/lightning.pytorch.loggers.mlflow.html) in #159 . This comes with new documentation and notebooks under the `example` folder on how to use it.

* SheepRL is now on PyPI: every time a release is published, the new version of SheepRL is published also in PyPI (155)
* Torchmetrics is no longer installed from the [github main branch](https://github.com/Lightning-AI/torchmetrics) (#155).
* Moviepy is no longer installed from the [github main branch](https://github.com/Zulko/moviepy) (#155).
* box2d-py is not a mandatory dependency anymore, it is possible to install `gymnasium[box2d]` with the `pip install sheeprl[box2d]` command (156)
* The `moviepy.decorators.use_clip_fps_by_default` function is replaced (in the `./sheeprl/__init__.py` file) with the method in the [moviepy main branch](https://github.com/Zulko/moviepy/blob/master/moviepy/decorators.py#L118) (156).

* The exploration amount of the Dreamer's player has been moved to the Actor in 150
* All the P2E scripts have been split into `exploration` and `finetuning` in 151
* The hydra version has been fixed to `1.3` in 152
* SheepRL is now published on PyPi in 155