40 support dataset with missing timesteps

[JPXKQX]

Describe your changes
This PR introduces support for datasets with missing timesteps.

A "valid_times" attribute is added to the NativeGridDataset. This attribute contains the indices of the samples valid for training. It is computed based on 4 parameters:

• Number of input timesteps.
• Steps to roll out.
• Time increments.
• Missing timesteps, if any.

Please also include relevant motivation and context.
We need to support training with datasets containing missing time steps.

List any dependencies that are required for this change.
No new dependencies.

Type of change
Please delete options that are not relevant.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

Issue ticket number and link
Issue #40

Checklist before requesting a review

• I have performed a self-review of my code
• My code follows the style guidelines of this project
• I have commented my code, particularly in hard-to-understand areas
• I have updated the documentation and docstrings to reflect the changes
• I have added tests that prove my fix is effective or that my feature works
• I have ensured that the code is still pip-installable after the changes and runs
• I have not introduced new dependencies in the inference partion of the model
• I have run this on a single GPU
• I have run this on multi-GPU or multi-node
• I have run this to work on LUMI (or made sure the changes work independently.)
• I have run the Benchmark Profiler against the old version of the code

Thanks to @Magnus-SI and the rest of the MetNorway team for their contribution to this feature.

[FussyDuck]

All committers have signed the CLA.

The merge-base changed after approval.

[mchantry]

Great work, approved.