Feature add activation to BlockRNN (#2492)

[SzymonCogiel]

Checklist before merging this PR:

• [x] Mentioned all issues that this PR fixes or addresses.
• [x] Summarized the updates of this PR under Summary.
• [x] Added an entry under Unreleased in the Changelog.

Fixes #2492 .

Summary

• Added support for specifying PyTorch activation functions (ReLU, Sigmoid, Tanh, or None) in the BlockRNNModel.
• Ensured that activation functions are applied between fully connected layers, but not as the final layer.
• Implemented a check to raise an error if an activation function is set but the model only contains one linear layer.
• Updated documentation to reflect the new activation parameter and usage examples.
• Added test cases to verify the correct application of activation functions and to handle edge cases.

Other Information

Consider using a logging warning instead of raising an error if an activation function is set but the model only contains one linear layer.

[codecov[bot]]

Codecov Report

Attention: Patch coverage is 58.33333% with 5 lines in your changes missing coverage. Please review.

Project coverage is 93.75%. Comparing base (26c5f39) to head (e94b3c7). Report is 1 commits behind head on master.

Files with missing lines	Patch %	Lines
darts/models/forecasting/block_rnn_model.py	58.33%	5 Missing :warning:

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #2504      +/-   ##
==========================================
- Coverage   93.79%   93.75%   -0.05%     
==========================================
  Files         139      139              
  Lines       14741    14738       -3     
==========================================
- Hits        13827    13818       -9     
- Misses        914      920       +6     

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[eschibli]

Should a warning be raised if activation is None and hidden_fc_sizes isn't? That would always be suboptimal and users who don't read the changelog might not be aware the default activation is None.