Contrastive pretraining tutorial #106
                
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Adds a tutorial script,
tutorial_sus.py, demonstrating how to use EEGDash and Braindecode for contrastive learning on EEG data from a surround suppression task.Key components:
Contrastive Learning Utilities:
ContrastiveSamplerandContrastiveDatasetclasses to generate and handle pairs of EEG samples for contrastive learning, ensuring correct pairing logic and reproducibility.Model Architecture and Training:
ShallowFBCSPNet) and a classification head, and provided a full training loop using binary cross-entropy loss for the contrastive task, including normalization, optimizer, and scheduler setup. (F