Feat/joint sampler - #157
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- Add BaseSampler as common abstract base for all samplers - Split old Sampler into SamplerStochastic (random node selection) and SamplerSequential (all nodes in order) - Add MSampler/MTrainSampler/MValidationSampler for sequential sampling - Make TrainSampler.sample() and ValidationSampler._register_data() abstract so subclasses provide the correct _sample() call signature
- BaseMethod.compute_loss and train_step accept list[StepData] | StepData - _train_step_forward maps _match_observations over list inputs - Trainer type hints updated to use base TrainSampler/ValidationSampler
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Added Multi-Input Sampling & Tests