Changing the `_get_param_names` method to return a list instead of a
generator to fix the exception error message when passing unknown
parameters to `set_params`. Before the error message just included
the generator `repr`-string as the list of possible parameters.
Now the string contains the possible parameter names instead.

Changing the `_get_param_names` method to return a list instead of a
generator to fix the exception error message when passing unknown
parameters to `set_params`. Before the error message just included
the generator `repr`-string as the list of possible parameters.
Now the string contains the possible parameter names instead.

Preparation for release of version 0.13.0

Release text:

The new skorch release is here and it has some changes that will be exiting for
some users.

- First of all, you may have heard of the [PyTorch 2.0
  release](https://pytorch.org/get-started/pytorch-2.0/), which includes the
  option to compile the PyTorch module for better runtime performance. This
  skorch release allows you to pass `compile=True` when initializing the net to
  enable compilation.
- Support for training on multiple GPUs with the help of the
  [`accelerate`](https://huggingface.co/docs/accelerate/index) package has been
  improved by fixing some bugs and providing a dedicated [history
  class](https://skorch.readthedocs.io/en/latest/user/history.html#distributed-history).
  Our documentation contains more information on [what to consider when training
  on multiple
  GPUs](https://skorch.readthedocs.io/en/latest/user/huggingface.html#caution-when-using-a-multi-gpu-setup).
- If you have ever been frustrated with your neural net not training properly,
  you know how hard it can be to discover the underlying issue. Using the new
  [`SkorchDoctor`](https://skorch.readthedocs.io/en/latest/helper.html#skorch.helper.SkorchDoctor)
  class will simplify the diagnosis of underlying issues. Take a look at the
  accompanying
  [notebook](https://nbviewer.org/github/skorch-dev/skorch/blob/master/notebooks/Skorch_Doctor.ipynb)

Apart from that, a few bugs have been fixed and the included notebooks have been
updated to properly install requirements on Google Colab.

We are grateful for external contributors, many thanks to:

- Kshiteej K (kshitij12345)
- Muhammad Abdullah (abdulasiraj)
- Royi (RoyiAvital)
- Sawradip Saha (sawradip)
- y10ab1 (y10ab1)

Find below the list of all changes since v0.12.1 below:

### Added
- Add support for compiled PyTorch modules using the `torch.compile` function,
  introduced in [PyTorch 2.0
  release](https://pytorch.org/get-started/pytorch-2.0/), which can greatly
  improve performance on new GPU architectures; to use it, initialize your net
  with the `compile=True` argument, further compilation arguments can be
  specified using the dunder notation, e.g. `compile__dynamic=True`
- Add a class
  [`DistributedHistory`](https://skorch.readthedocs.io/en/latest/history.html#skorch.history.DistributedHistory)
  which should be used when training in a multi GPU setting (#955)
- `SkorchDoctor`: A helper class that assists in understanding and debugging the
  neural net training, see [this
  notebook](https://nbviewer.org/github/skorch-dev/skorch/blob/master/notebooks/Skorch_Doctor.ipynb)
  (#912)
- When using `AccelerateMixin`, it is now possible to prevent unwrapping of the
  modules by setting `unwrap_after_train=True` (#963)

### Fixed
- Fixed install command to work with recent changes in Google Colab (#928)
- Fixed a couple of bugs related to using non-default modules and criteria
  (#927)
- Fixed a bug when using `AccelerateMixin` in a multi-GPU setup (#947)
- `_get_param_names` returns a list instead of a generator so that subsequent
  error messages return useful information instead of a generator `repr` string
  (#925)
- Fixed a bug that caused modules to not be sufficiently unwrapped at the end of
  training when using `AccelerateMixin`, which could prevent them from being
  pickleable (#963)